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61 results about "Distributed model predictive control" patented technology
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Multi-agent cluster coordination method and multi-UAV cluster coordination system
InactiveCN107179777APredictiveImprove efficiencyPosition/course control in three dimensionsDistributed control systemAerial photography
The invention belongs to the technical field of a distributed control system and relates, specifically, to a multi-agent cluster coordination method and a multi-UAV cluster coordination system. The multi-agent cluster coordination method of the invention allows agents to exchange information with neighbors within their respective interaction ranges and to form a cluster in a self-organized manner by solving for the control input through distributed mode predictive control. The method further allows the presence of a leader agent in the system to lead the overall motion trajectory of the agent cluster. The multi-UAV cluster coordination system provided by the invention enables multiple UAVs to autonomously achieve cluster flight through data exchange thereamong, enhances the efficiency of executing the tasks that need the coverage of a large area, such as aerial photography, monitoring, search and rescue, and the like, and has high adaptivity and redundancy.
Owner:FUDAN UNIV
Cooperative control method of multi-unmanned aerial vehicle formation based on model predictive control
ActiveCN109871032AAchieve stabilityAchieve efficiencyPosition/course control in three dimensionsSimulationUncrewed vehicle
The present invention relates to a cooperative control method of a multi-unmanned aerial vehicle formation based on model predictive control. The method comprises the following steps of I, initializing task requirements, related control parameters and the like; II, conducting preliminary route planning for a pilot unmanned aerial vehicle; III, detecting the condition of an environment of a flightarea in real time through a sensor, judging and selecting a proper flight formation, and calculating (updating) a virtual formation guidance point; IV, calculating a reference value according to the calculated virtual formation guidance point by using the guidance point as a cost, calculating a cost function, and conducting flight control by adopting a particle swarm optimization strategy based ondistributed model predictive control; and V, repeating the step II, the step III and the step IV, and controlling the multi-unmanned aerial vehicle formation to conduct cooperative flight until a target position is reached. The method effectively solves the problem of cooperative control over the formation in a complex environment, and enables a multi-unmanned aerial vehicle system to have stableformation retention capability and efficient formation transformation capability during flight.
Owner:CAS OF CHENGDU INFORMATION TECH CO LTD
Distributed model predictive control method for urban road network system based on neighborhood optimization
ActiveCN104575021AImpact of traffic conditionsPractical applicationControlling traffic signalsMathematical modelDecomposition
The invention relates to a distributed model predictive control method for an urban road network system based on neighborhood optimization. The distributed model predictive control method comprises the following steps: 1) establishing a road section mathematical model; 2) establishing an urban traffic network system model and an urban traffic road network system distributed model: introducing a control component G (k) on the basis of the road section model and performing decomposition and deformation on the road network system model to obtain the road network system distributed model; 3) establishing performance indexes and constraint conditions of each subsystem and constructing subsystem performance indexes based on the neighborhood optimization; 4) firstly calculating a local optimal control variable through each subsystem, continuously iterating through performing information exchange with a neighborhood subsystem according to a Nash game theory principle to enable the whole system to converge Nash equilibrium points at last and obtaining a Nash optimal control input quantity at the same time. The distributed model predictive control method is simple and clear, convenient to realize and better in control effect and improves the traffic congestion conditions in the urban road network system under a saturated or supersaturated state.
Owner:ZHEJIANG UNIV OF TECH
Multi-region cooperative joint frequency modulation control method based on dual-layer model predictive structure
PendingCN108964087AEnsure safetyReduce joint FM costsSingle network parallel feeding arrangementsPower oscillations reduction/preventionEconomic model predictive controlEngineering
The invention provides a multi-region cooperative joint frequency modulation control method based on a dual-layer model predictive structure. The method realizes the steady-state power optimized application of cross-regional AGC units under the multi-constraint condition on the basis of the economic model predictive control in the upper layer; and the dynamic frequency optimization control of themulti-region AGC units on the basis of the distributed model predictive control is realized in the lower layer. On the slow time scale (minutes), the steady-state power optimized allocation of the cross-regional AGC units considering the safety constraints of tie line sections is realized. On the short time scale (seconds), the dynamic frequency optimization control of the AGC units in each regionis realized.
Owner:WIND POWER TECH CENT OF GANSU ELECTRIC POWER +2
Frequency control method and system for interconnected power system containing energy storage resources
ActiveCN112531792AQuickly smooth out frequency fluctuationsSafe and stable operationSingle network parallel feeding arrangementsAc network load balancingNew energyElectric power system
The invention discloses a frequency control method and system for an interconnected power system containing energy storage resources. The control method comprises the following steps: establishing a frequency response model of a regional interconnected power system containing energy storage frequency modulation resources; performing frequency division processing on the ACE signal to obtain a powerreference value borne by a traditional unit and an energy storage resource; establishing a space state model and discretizing the space state model; designing a distributed model prediction controller, and establishing an optimization objective function and constraint conditions; and solving a quadratic programming problem formed by the optimal objective function and the constraint condition to determine an optimal control sequence, and enabling a first control variable in the control sequence to act on a traditional unit and energy storage resources to realize optimal control. The control strategy provided by the invention can reasonably allocate the frequency modulation responsibilities of a traditional unit and the energy storage resources, gives play to the advantages of quick outputof energy storage and large frequency modulation capacity of the unit, and can quickly stabilize the frequency fluctuation caused by load and new energy injection in a power system.
Owner:JIANGSU FRONTIER ELECTRIC TECH
Underactuated multi-unmanned ship formation tracking method based on master-slave distributed model predictive control
ActiveCN109032136ASolving Thrust Constrained ProblemsSolve the problem of not being detected by each drone shipAdaptive controlPosition/course control in two dimensionsNODALPerformance index
The invention relates to an optimized formation tracking control method based on distributed model predictive control and belongs to the field of motion control of underactuated multi-surface unmannedships. The method comprises the following steps: 1) establishing an underactuated unmanned ship motion model and a tracking error model; 2) establishing a performance index of a master unmanned ship,proposing a model predictive tracking control algorithm, and calculating an optimal input at the current time according to the performance index thereof; 3) based on the acquired neighbor node information, establishing the performance index of each unmanned ship, respectively, proposing a distributed model predictive control algorithm and calculating an optimized input of the current time according to the performance index; 4) updating the predictive information and continuously and iteratively optimizing the formation of the whole unmanned ship so that a certain formation is kept between theunmanned ships so as to track the target unmanned ship.
Owner:NORTHWESTERN POLYTECHNICAL UNIV
Optimized mowing type formation control method for unmanned ship guided underwater vehicle group
ActiveCN109521797AImplementing Trajectory Tracking Optimization ProblemsSolving Constrained Control ProblemsAdaptive controlPosition/course control in three dimensionsMarine engineeringPerformance index
Owner:NORTHWESTERN POLYTECHNICAL UNIV
Series-structure light-storing-type multi-micro-grid economical operation system and method
ActiveCN105337310AAchieve economical operationReduce computational complexitySingle network parallel feeding arrangementsEnergy storageControl systemEngineering
The invention discloses a series-structure light-storing-type multi-micro-grid economical operation system and a method. The series-structure light-storing-type multi-micro-grid economical operation system comprises a primary system and a control system. The primary system is formed in the mode that two sub-micro-grids are connected in series through a grid-connection and off-grid switch K1, and the primary system comprises a photovoltaic power generation array, a storage battery and local loads. The control system is formed by sub-micro-grid controllers, photovoltaic controllers, energy storing controllers, load controllers and a communication network. According to the series-structure light-storing-type multi-micro-grid economical optimization method, a distributed model prediction control algorithm considering a peak-valley electricity price is adopted, and according to the source load characteristic and the operating characteristic in the multiple micro-grids, a micro-grid prediction model and an optimized objective function are established. The established series-structure light-storing-type multi-micro-grid economical operation system and the method have the important engineering application value in developing researching of planning, design, mode switching and optimizing operation of the light-storing-type multi-micro-grid system.
Owner:SOUTH CHINA UNIV OF TECH +1
Wind power cluster system advanced frequency control method and system based on distributed model prediction control
InactiveCN109085755AAchieving Power FluctuationMeet the speed requirements of online scrolling optimizationAdaptive controlElectric power systemOptimal control
The invention discloses a wind power cluster system advanced frequency control method based on distributed model prediction control. The method comprises the steps that 1, a multi-dimensional state space equation of each control region in a multi-region interconnected electric power system is determined; 2, a corresponding control variable sequence is controlled by means of a Laguerre function ina distributed model prediction controller, so that parameter dimensionality reduction processing is carried out on the multi-dimensional state space equation of each control region in the multi-regioninterconnected electric power system; 3, the minimum output variable and variable quantity weighting inhibition control are determined as an optimization objective; 4, corresponding additional constraint conditions are determined according to the basic principle of wind power participating in frequency modulation and the present actual value of the active power of a time-step wind power plant; 5,an optimal control Laguerre coefficient sequence is determined as an optimal control sequence, and the optimal control sequence is applied to the system at the current time-step to carry out correction; and 6, the multi-dimensional state space equation of each control region is updated as a multi-dimensional state space equation of the next time-step.
Owner:CHINA ELECTRIC POWER RES INST +3
Comprehensive energy system multi-time scale optimization scheduling method and system, and storage medium
ActiveCN112072712ASolve complex and difficult technical problems onlineReduce difficultyGeneration forecast in ac networkLoad forecast in ac networkIntegrated energy systemLoad following power plant
The invention discloses a comprehensive energy system multi-time scale optimization scheduling method and system, and a storage medium. The method comprises the following steps: building an energy storage side model, an energy conversion side model, an energy storage side model and a load side model according to a comprehensive energy system architecture; according to renewable energy and load day-ahead prediction information, gas purchase price and time-of-use electricity price, establishing a day-ahead optimization model by taking the lowest daily operation cost of the comprehensive energy system as a target; according to the intra-day renewable energy and the load day-ahead prediction information, establishing an intra-day optimal scheduling model with the minimum system operation costand the minimum start-stop punishment cost of all the units as targets; and according to the real-time prediction information, solving by adopting a distributed model prediction control algorithm withthe minimum total adjustment amount of system controllable equipment at the next moment of an intra-day scheduling plan as a target to obtain a final scheduling plan. According to the method, the distributed model prediction control algorithm is adopted to solve the scheduling model in the implementation stage, the complexity of the model can be reduced, the difficulty of online solving is reduced, and meanwhile the control performance of the system can be considered.
Owner:HEFEI UNIV OF TECH
Cooperative motion method for robot cluster in obstacle scene
ActiveCN110162035ARealize path planningImplement navigationPosition/course control in two dimensionsCouplingObstacle avoidance
The invention relates to the technical field of robots, more particularly to a cooperative motion method for a robot cluster in an obstacle scene. The method provided by the invention is used for enabling multiple robots to realize formation transformation, dynamic and static obstacle avoidance and cooperative motion in the obstacle scene. The method defines the cooperative control of the robot cluster in a complex environment as a distributed model predictive control problem. Each robot solves an optimization equation independently based on the information of local neighbors, which has betterrobustness and flexibility. At the same time, the method proposes the concept of a formation diagram, and uses a directed diagram to represent the robot formation. Under the premise of ensuring the connectivity of the diagram, local transformation of the desired formation can be realized by changing the edges and weights of the formation, and at the same time, the connectivity and the flexibilityof the cluster can be ensured. Besides, the method provided by the invention has a hierarchical structure. By adopting the hierarchical structure, the coupling between modules can be reduced, and algorithm design and expansion can be facilitated.
Owner:SUN YAT SEN UNIV
Wind power cluster integrated frequency control method and system based on hierarchical distributed model predictive control
PendingCN109167372ARealize closed-loop operationSingle network parallel feeding arrangementsPower oscillations reduction/preventionElectricityGranularity
The invention discloses a wind power cluster integrated frequency control method based on hierarchical distributed model predictive control, which comprises the following steps of: establishing a hierarchical distributed model predictive control H-DMPC controller; The multi-time scale coordinated variable granularity frequency control framework of wind power cluster is established in the tertiaryfrequency modulation layer, the secondary frequency modulation layer and the primary frequency modulation layer. The rolling optimization models are established on the spatial scale in the tertiary frequency modulation layer, the secondary frequency modulation layer and the primary frequency modulation layer respectively. In the aspect of wind power prediction error correction, the feedback correction link is established to realize the closed-loop operation of integrated frequency control through the feedback correction of grid operation state and prediction data. The invention establishes a feedback correction link according to the real-time operation state of the system, realizes the closed-loop operation of the integrated frequency control strategy, and the proposed control strategy caneffectively realize the wind power cluster to participate in the system frequency modulation, and can consider both the economy and the safety objectives of the system.
Owner:CHINA ELECTRIC POWER RES INST +3
Distributed model predictive control method based on hierarchical decomposition
ActiveCN105511263ASolve the problem of high communication loadReduce communication burdenAdaptive controlOptimal controlNetwork structure
The invention discloses a distributed model predictive control method based on hierarchical decomposition, comprising the following steps: for a distributed system, an adjacency matrix of the distributed system is acquired according to a communication network structure, and each subsystem is divided into a plurality of connected sets by the adjacency matrix by using an adjacent matrix based path search method; a reachable matrix of the connected sets is constructed, the level of each connected set is determined based on a hierarchical decomposition method in an interpretative modeling method, all the connected sets of the same level are combined into one connected set, and therefore, a connected-set set of a serial structure is constructed; and at each sampling moment, the optimal control input sequence of each subsystem in each connected set is solved in sequence according to the series order, and predictive control is performed on the distributed system. By using the method, communication between connected sets not correlated directly is avoided, the communication burden is reduced greatly while the system stability is ensured, and the problem that the traditional collaborative distributed model predictive control method is of high necessary communication burden is solved.
Owner:ZHEJIANG UNIV
Multi-ocean-robot cooperative circular scanning method based on distributed model predictive control
The invention relates to a multi-ocean-robot cooperative circular scanning method based on distributed model predictive control, and belongs to the field of multi-ocean-robot control. The method is mainly used for multi-ocean-robot cooperative circular scanning, and is characterized by firstly achieving the following of real targets to respective trajectories by using the real targets to track moving virtual targets on the trajectories; and then in consideration of a relationship between the travel angles between virtual targets in a cooperative circular scanning process, introducing a cooperative performance index, and online optimizing an optimal control sequence by using a distributed model predictive control algorithm. The method, by using the distributed model predictive control algorithm, greatly reduces the communication pressure between systems, and solves two problems including path following and cooperative control by using one controller, thereby reducing the design difficulty of a control system.
Owner:NORTHWESTERN POLYTECHNICAL UNIV
Virtual power plant distributed model prediction control method under active power distribution network environment
ActiveCN105631549ARealize dynamic optimization configurationReduce optimization complexityForecastingSystems intergating technologiesAutomatic controlSystem optimization
The invention discloses a virtual power plant distributed model prediction control method under the active power distribution network environment, and belongs to the technical field of power system automatic control. A virtual power plant integral dynamic optimization model is established according to the distributed characteristic and the randomness characteristic of all energy resources; the integral dynamic optimization model is converted into subsystem models with all energy groups acting as main bodies according to the geographical distribution characteristics of all the distributed energy; and dynamic optimization of the output process of all the subsystem models is performed by adopting the distributed model prediction control method so that complexity of system optimization can be reduced and dynamic optimization configuration of the energy resources in a virtual power plant can also be realized.
Owner:NANJING UNIV OF POSTS & TELECOMM +1
Large-scale irrigation system control method based on distributed model prediction control
ActiveCN103651064AReduce trafficReduce communication costsWatering devicesCultivating equipmentsMathematical modelWater flow
A large-scale irrigation system control method based on distributed model prediction control comprises the following steps that 1) a mathematical model of each canal in an irrigation system is built, and it is taken into consideration how many water inlets and water outlets may each canal have in practical situations; 2) performance indexes of each canal system are built, performance indexes of each canal are taken into consideration under partial cooperation situations, and therefore the system can be converged rapidly, communication traffic is reduced, and meanwhile overall performance can be improved; 3) the distributed MPC algorithm is provided, the optimal input quantity of each canal is calculated under the current situation by means of partial communication, the system is finally converged to a Nash equilibrium point by conducting iteration continuously on the basis of the Nash game theory, and therefore the optimal input quantity at the moment is reached.
Owner:ZHEJIANG UNIV OF TECH
Chaos grey wolf optimization-based unmanned aerial vehicle formation control method
ActiveCN111443728ALow communication requirementsReduce computational complexityChaos modelsArtificial lifeControl engineeringUncrewed vehicle
The invention proposes a chaos grey wolf optimization-based unmanned aerial vehicle formation control method. A distributed model predictive control (MPC) frame of unmanned aerial vehicle formation control is built, each unmanned aerial vehicle only shares information with a neighbor, and the communication requirement and the computational complexity are reduced; a chaos optimization algorithm iscombined with a grey wolf optimization algorithm, and thus, the algorithm performance is improved; and the algorithm is combined with the distributed MPC, finite horizon optimal control problem (FHOCP) is solved, so that unmanned aerial vehicle formation control is achieved.
Owner:BEIHANG UNIV
Heavy-load locomotive adhesion control method and device based on distributed model predictive control
InactiveCN110955146AReal-time prediction of optimal traction torqueGood Adhesive UtilizationLocomotivesAdaptive controlDynamic modelsCreep rate
The invention provides a heavy-load locomotive adhesion control method based on distributed model predictive control, which comprises the following steps: acquiring operating parameters in the locomotive operating process, and establishing a locomotive kinetic model according to the operating parameters; constructing a creep rate calculation model according to the relationship among the creep rateof the locomotive, the angular speed of wheels and the speed of the locomotive; a distributed state space model is obtained by combining the locomotive dynamic model, the creep rate calculation modeland the vehicle rail model; acquiring real-time traction torque of a corresponding shaft through an MPC adhesion controller arranged at each shaft of the locomotive, and calculating to obtain a predicted traction torque value and a predicted creep rate value through a distributed state space model and a preset cost function according to the real-time traction torque; and the predicted creep ratevalue is compared with a preset creep rate value, and when the predicted creep rate value is equal to the preset creep rate value, the traction torque of each shaft is adjusted according to the predicted traction torque value.
Owner:CHINA ACADEMY OF RAILWAY SCI CORP LTD +2
Design method of distributed model prediction controller of automatic power generation control system
InactiveCN110932320AImprove dynamic performanceSafe and stable operationSingle network parallel feeding arrangementsWind energy generationReliability engineeringWind power generation
The invention relates to a design method of a distributed model prediction controller of an automatic power generation control system. The design method comprises the following steps: building simulation models of the automatic power generation control system of a regional interconnection power system, wherein the simulation models comprise a wind power generation model and a photovoltaic power generation model; according to the simulation models of the automatic power generation control system, designing a distributed model prediction control algorithm and establishing and optimizing a targetfunction; determining a constraint condition according to the actual operation condition of the automatic power generation control system, and processing the constraint; and according to the target function and the constraint condition, optimizing by adopting a guided firework algorithm to obtain controller output. According to the design method, the dynamic performance of the interconnected power grid automatic power generation control system is effectively improved, and the safe and stable operation of a power system is ensured.
Owner:NORTH CHINA ELECTRIC POWER UNIV (BAODING)
Hybrid vehicle queue distributed model prediction and control method
The invention discloses a hybrid vehicle queue distributed model prediction and control method. The method comprises the following steps of firstly, dividing a hybrid vehicle queue into a plurality of mutually associated local hybrid vehicle queues; then establishing a model of each local hybrid queue based on a car-following model of networked automatic driving vehicles and human-drive vehicles; secondly, based on the local hybrid queue model, according to a model prediction control algorithm, establishing an overall control problem of the hybrid vehicle queue; and finally, in combination with an alternating direction multiplier method, constructing a distributed model prediction controller for each local hybrid queue to realize the overall formation control of the hybrid vehicle queue. The effectiveness of the method provided by the invention is verified by performing an experiment on an MATLAB simulation platform. Experimental results show that the method can ensure that the networked automatic driving vehicles and the human-driven vehicles in the hybrid vehicle queue achieve a good formation effect, and the networked automatic driving vehicles can be driven in a formation manner at a smaller inter-vehicle distance, so that the traffic capacity is effectively improved.
Owner:BEIJING UNIV OF TECH
Variable formation incomplete mobile robot consistency control method based on prediction
PendingCN114237247AEfficient execution efficiencyIncrease profitPosition/course control in two dimensionsVehiclesMultirobot systemsConsistency control
The invention discloses a variable formation incomplete mobile robot consistency control method based on prediction, and the method comprises the steps: determining a virtual leader to leader all other followers in a multi-robot system; establishing a kinematic model of the incomplete mobile robot; defining a control object of the leader-follower time-varying consistency formation; establishing an auxiliary consistent formation maneuvering trajectory subsystem and a formation tracking subsystem on a Cartesian coordinate level according to the definition of the consistent error; a mathematical language is used for expression, and an optimized formation model neural dynamic optimization distributed model predictive control formation controller is established. According to the method, the time-varying consistency formation problem of structure change of the incomplete mobile robot under the information transformation topology and the constraint problem of system physics are solved.
Owner:GUANGDONG UNIV OF TECH
Distributed formation control system and method in disturbance three-dimensional environment
InactiveCN108829133AReduce computational overheadStrong uncertaintyPosition/course control in three dimensionsControl systemThree-dimensional space
The present invention discloses a distributed formation control system and method in a disturbance three-dimensional environment. The method combines model predictive control with extended Kalman filter, realizes the formation control over multiple controlled objects in the case that great uncertainty exists in the modeling of the controlled objects and the output measurement of the controlled objects has noise, integrates a swarm intelligence optimization algorithm library to realize the formation control over the multiple controlled objects in the case that the controlled objects have complex and coupled three-dimensional space dynamic characteristics and are limited by complex constraints. In addition, the method is achieved by distributed model predictive control so as to further reduce the computational cost of the control law solution and enhance the anti-strike capability of the formation control.
Owner:BEIJING SIMULATION CENT
Intelligent tensegrity structure vibration multi-level distributed model prediction control method based on substructure technology
ActiveCN109739091ADecomposition modeling process is flexibleDecomposition modeling process is simpleAdaptive controlDecompositionControl system
The invention discloses an intelligent tensegrity structure vibration multi-level distributed model prediction control method based on a substructure technology. The method comprises the following steps: S1, building an intelligent tensegrity structure distributed model prediction control system; S2, based on the substructure technology, decomposing the intelligent tensegrity structure distributedmodel prediction control system into a series of multi-level subsystems; S3, selecting substructure systems at different levels, and independently designing corresponding local subcontrollers; S4, considering input saturation constraints, and converting the original distributed model prediction control problem into a series of linear complementary problems; and S5, solving the linear complementary problem in the step S4, and obtaining input voltage of each subcontroller as well as controlled dynamic response. Compared with existing distributed model prediction control, the method disclosed bythe invention is based on the substructure technology, a decomposition modeling process on the whole structure system is more flexible and simpler, and the method has a uniform multilevel distributedframework.
Owner:DALIAN UNIV OF TECH
Unmanned aerial vehicle cluster collaborative flight path planning method considering communication time delay
PendingCN114791743AGuaranteed reliabilityImprove collaborative task capabilitiesMathematical modelsForecastingGlobal planningSimulation
The invention discloses an unmanned aerial vehicle cluster collaborative flight path planning method considering communication time delay, and belongs to the technical field of flight path planning. Under the condition of considering communication time delay, a'global planning-local obstacle avoidance 'cooperative track planning framework is constructed, in the global planning stage, probability distribution of adjacent unmanned aerial vehicle positions caused by random communication time delay is considered, the probability distribution situation of the adjacent unmanned aerial vehicle positions caused by the communication time delay is combined into a sparse A * search algorithm, and the probability distribution situation of the adjacent unmanned aerial vehicle positions caused by the random communication time delay is combined into the sparse A * search algorithm. A priority decoupling mechanism is introduced to improve the algorithm search efficiency; in the local collision avoidance stage, the local collision risk still exists in the global flight path due to the uncertainty of communication time delay and the uncertainty of the position of an adjacent vehicle is considered, the optimal control problem of distributed model predictive control is solved, and flight path tracking and local adjustment of the unmanned aerial vehicle in the pipeline are achieved. Based on double-level cooperative flight path planning, the timeliness and reliability of unmanned aerial vehicle cluster cooperative flight path planning under communication time delay are ensured, and the cooperative capability of an unmanned aerial vehicle cluster in a real scene is improved.
Owner:BEIJING INSTITUTE OF TECHNOLOGYGY
Neutral buoyancy robot attitude and trajectory control method based on distributed model predictive control
ActiveCN108829109AImprove performanceSmall amount of calculationAttitude controlPosition/course control in two dimensionsRobot controlControl theory
The invention discloses a neutral buoyancy robot attitude and trajectory control method based on distributed model predictive control and belongs to the field of microgravity robot control. The methodmakes a study for the coupling problem and optimization problem of a plurality of neutral buoyancy robots having different sampling periods, and simulates a unified sampling period for the neutral buoyancy robots having different sampling periods through the Delta operator theory at the controller side; and when one or more neutral buoyancy robots need to update control quantity, states of otherneutral buoyancy robots can be obtained through a predictive mode, so that the states of other neutral buoyancy robots can be taken into account in constraints to solve their control quantity, and thewhole system is allowed to ensure that coupling probability constraint is met nonconservatively, and ensure that the system performance is good. The method combines the characteristics of computer control and converts the complex on-line optimization problem into quadratic programming, thereby greatly reducing calculation amount; and the method is suitable for engineering application.
Owner:NORTHWESTERN POLYTECHNICAL UNIV
Multi-agent distributed model prediction control method and system
ActiveCN112684781AGuaranteed iterative feasibilityVehicle position/course/altitude controlPosition/direction controlControl engineeringKinetics equation
The invention discloses a multi-agent distributed model prediction control method and system. The method comprises the steps that 1 a kinetic equation of an intelligent agent is described, and parameters are defined; 2 the intelligent agent broadcasts the assumed state track of the future Np + 1 step of the intelligent agent and receives the assumed state track broadcasted by the intelligent agent in a neighbor set to the intelligent agent out of the neighbor set; 3 a future Np step optimal control input sequence and a future Np + 1 step optimal state sequence are solved; 4 the intelligent agent uses the first element of the optimal control input sequence for the current moment t, the second to Np-1 elements of the optimal control input sequence are used as assumed input tracks of the moment t + 1, and the second to Np elements of the optimal state sequence are used as assumed state tracks of the moment t + 1; and 5 a join terminal is input, and the steps 2 to 5 are repeated through single-step recursion. The method can guarantee the iteration feasibility, is suitable for a wide range of communication topology types, and simplifies the implementation and parameter adjustment in practical application.
Owner:HUNAN UNIV
Cluster collaborative deployment method based on distributed optimal energy MPC
ActiveCN112882493AIncrease capacityRealize generationComplex mathematical operationsPosition/course control in three dimensionsControl setUncrewed vehicle
The invention discloses a cluster collaborative deployment method based on distributed optimal energy MPC, and the method achieves the collaborative deployment of an unmanned aerial vehicle group through the ad hoc network communication of a plurality of unmanned aerial vehicles and the autonomous generation of a control instruction by each unmanned aerial vehicle. According to the cluster collaborative deployment method based on the distributed optimal energy MPC, an optimal control equation is established based on the distributed model predictive control method, and a suboptimal analytical solution is obtained by solving a Hamiltonian equation, so that the calculation amount of the optimization process is greatly reduced, the generation of a real-time track is realized, the method has the advantages of no need of central server control, large number of cluster unmanned aerial vehicles, high unmanned aerial vehicle density and the like.
Owner:BEIJING INSTITUTE OF TECHNOLOGYGY
Coordination control method for off-grid phosgene combined heat and power generation integrated energy system
PendingCN113159983AGuaranteed control qualityLighten the computational burdenBatteries circuit arrangementsForecastingEnergy balancingIntegrated energy system
The invention relates to a coordination control method for an off-grid phosgene combined heat and power generation integrated energy system. An integrated energy system model with subsystems representing overall dynamic characteristics of the system is constructed through overall analysis of the system and serves a distributed model prediction control algorithm. A single-layer control structure based on direct energy balance is provided according to a user energy demand analysis system control target, and thermoelectric energy supply and demand real-time balance can be achieved without an upper layer optimization scheduling instruction. Furthermore, according to the characteristics of a coordination control object, cooperative distributed model predictive control is adopted to achieved thermoelectric coordination control. Through simulation verification, the control strategy provided by the invention can realize real-time balance of thermoelectric energy supply and demand under various disturbances, and the calculation burden is significantly reduced compared with a centralized model prediction control algorithm.
Owner:SOUTHEAST UNIV
Traditional Chinese medicine preparation process operation optimization method based on distributed model predictive control
ActiveCN114200840AImplement trackingLow costTotal factory controlAdaptive controlControl engineeringData-driven
The invention discloses a traditional Chinese medicine preparation process operation optimization method based on distributed model predictive control, and the method comprises the steps: building an operation control process model of each link of a traditional Chinese medicine preparation process, and the operation control process model comprises a bottom layer process control loop model and an operation index and bottom layer controller output model; constructing a controller of a bottom-layer process control ring; designing a suboptimal set value of a controller of a bottom process control loop in the pharmaceutical process by adopting a data driving method; wherein the upper-layer operation control ring is updated by using a set value based on Q-learning according to a set value of an operation index and is transmitted to the bottom-layer process control ring through a zero-order retainer, and a controller of the bottom-layer process control ring gives a controlled quantity to control a controlled object to track a set value by solving an optimization problem. According to the method, the set value is updated by using the data of the operation process of traditional Chinese medicine preparation, and the bottom layer uses the DMPC to track the set value, so that the ideal value of operation index tracking is realized.
Owner:GUANGDONG UNIV OF TECH
DFIG active power control method based on distributed model predictive control
ActiveCN114844126AImprove controlImprove protectionGeneration forecast in ac networkGenerator control circuitsControl signalVoltage reference
The invention discloses a DFIG active power control method based on distributed model prediction control, and the method comprises the steps: obtaining the historical data of a DFIG, obtaining a wind speed sequence in a prediction time domain, constructing a control model of a variable pitch controller based on random model prediction, predicting to obtain a control input variable sequence in the prediction time domain, and carrying out the prediction of a wind speed sequence in the prediction time domain; the current wind wheel rotating speed serves as the optimal wind wheel rotating speed, then an optimal active power reference value is obtained through calculation, and a rotor current reference value is obtained through a stator outer ring control ring in a rotor side variable flow controller according to the optimal active power reference value; and a rotor inner ring control ring in the rotor side variable current controller obtains a rotor voltage reference value according to the rotor current reference value, and generates a control signal of the motor according to the rotor voltage reference value so as to control the rotor current value, thereby realizing active power control. According to the invention, a control architecture based on distributed model predictive control is adopted, so that the control effect is improved.
Owner:UNIV OF ELECTRONIC SCI & TECH OF CHINA
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