76 results about "State constraint" patented technology

A schedule for a complex activity is obtained by a scheduling system using a method of constraint-based iterative repair. A predetermined initial schedule is iteratively repaired, repairs being made during each iteration only to portions of the schedule that produce a constraint violation, until an acceptable schedule is obtained. Since repairs are made to the schedule only to repair violated constraints, rather than to the entire schedule, schedule perturbations are minimized, thereby reducing problems with the dynamic performance of the scheduling system and minimizing disruption to the smooth operation of the activity. All constraints on the scheduling activity can be evaluated simultaneously to produce a solution that is near optimal with respect to all constraints. In particular, consumable resource constraints can be evaluated simultaneously with other constraints such as, for example, reusable resource constraints, temporal constraints, state constraints, milestone constraints and preemptive constraints. The scheduling system of the invention is much quicker than previous scheduling systems that use, for example, constructive scheduling method. The system of the invention can also be easily modified to add, delete or modify constraints. Because of the minimization of schedule perturbation, coupling of all constraints, speed of operation, and ease of modification, the scheduling system of the invention is particularly useful for scheduling applications that require frequent and rapid rescheduling.

The invention provides an unmanned surface vessel full state constraint trajectory tracking control method based on the saturation compensation technology, relates to the unmanned surface vessel fullstate constraint trajectory tracking control method, and aims at solving the problem of high control error caused by the fact that the present control method for unmanned surface vessel trajectory tracking control does not process the problem of state constraints and saturation. The unmanned surface vessel full state constraint trajectory tracking control method comprises the steps that step one,the kinetic model of the unmanned surface vessel is established; step two, a saturation compensation auxiliary system is designed according to the kinetic model of the unmanned surface vessel established in the step one; step three, the saturation function of the unmanned surface vessel control law is established according to the saturation compensation auxiliary system designed in the step two; step four, the closed-loop system of the unmanned surface vessel is established; step five, the external interference is processed by using the adaptive method so as to obtain the adaptive estimation error; and step six, full state constraint trajectory tracking control of the unmanned surface vessel can be realized according to the adaptive estimation error obtained in the step five. The unmannedsurface vessel full state constraint trajectory tracking control method based on the saturation compensation technology is used for the field of trajectory tracking control.

The invention discloses a pedestrian autonomous navigation calculation algorithm based on an MEMS-IMU. Two IMU systems are simultaneously and fixedly connected with the two feet of the user of a pedestrian navigation system; the two systems respectively perform a strapdown inertial navigation calculation algorithm and a zero-speed correcting algorithm on the basis of Kalman filtering, and then the positioning information of the two feet is fused; when the calculation distance between two feet exceeds the largest step size gamma between the two feet, inequality constraint is performed on navigation results of two IMUs by adopting a state constraint Kalman filtering algorithm, so that vague human physiological property problem is converted into a rigid mathematical problem, the optimal estimation of navigation results is achieved, and pedestrian navigational positioning function with higher accuracy is achieved.

The invention discloses a cooperative optimization and control method for a mixed traffic flow of an expressway. The cooperative optimization and control method for the mixed traffic flow of the expressway is applied to vehicle optimal control under a merging scene of a ramp of the expressway. The cooperative optimization and control method for the mixed traffic flow of the expressway comprises the steps of predicting a vehicle track by using a microscopic vehicle following model; determining an optimization and control target vehicle; determining an optimization track section of a controllable vehicle; controlling a decision point and an admissible state set under each time; and carrying out optimization and control on the vehicle track. The cooperative optimization and control method forthe mixed traffic flow of the expressway has the beneficial effects that a microscopic traffic flow simulation environment based on the microscopic vehicle following model is established, and trafficeffects of different traffic states and different automatic driving vehicle permeability are analyzed; a brand-new cooperative merging model is proposed on the basis of the microscopic following model, traffic characteristics, geometric constraint and security constraint of the expressway are considered, and a cooperative merging problem is concluded into an optimization and control problem aboutdiscrete time state constraint; and a solving method based on dynamic programming is proposed to effectively solve the problem.

The invention relates to a small celestial body attachment detection descending trajectory optimization method, and belongs to the field of aviation and aerospace. According to the method, an internal spherical harmonic gravitational field model is adopted for estimating gravitational acceleration near a target small celestial body, and a convex optimization algorithm is adopted for solving the optimal control problem. By adopting the internal spherical harmonic gravitational field model for estimating the gravitational acceleration near the target small celestial body, the advantage of being high in computational efficiency is achieved. By adopting the convex optimization algorithm for solving the optimal fuel control problem, the problems that derivation of a indirection method is complicated, and co-state variables are free of physical meaning and not likely to guess are avoided, the derivation step is simple, the computing time is saved, the estimation optimization method is rapid and high in precision, and the obtained result conforms to initial and end state constraint, dynamic constraint and control constraint.

The invention provides an urban intersection mixed traffic flow collaborative optimization underlying control method, and belongs to the field of traffic engineering. The method comprises the following steps: a microcosmic car following model is determined; an initial trajectory of a car is predicted; a conflict cooperation model is established for the conflict type of an intersection; a cooperative control strategy set is drawn up; whether the car can smoothly pass through a conflict area or not is judged; if the car can smoothly pass through the conflict area, the car continues to run according to the speed of the microcosmic car following model; if the car cannot smoothly pass through the conflict area, the specific situation of the car in the process of passing through the conflict area needs to be judged, and a corresponding cooperative control strategy needs to be made; and the running track of a target car is optimized according to the cooperative control strategy, the optimization problem is summarized into an optimal control problem of discrete time state constraints, the problem is solved by the idea of dynamic programming to obtain a cooperative optimization control strategy about the target car, and the cooperative optimization control strategy is applied to the target car to control the running of the target car.

The invention provides a nonlinear system filter design method based on a self-adaption event triggering mechanism. The method comprises the steps of firstly building a state equation of a non-linear system; setting self-adaption event triggering conditions; building a filter model and a system error model of the non-linear system and obtaining an optimal filter of the non-linear system. The method employs the self-adaption event triggering mechanism for the non-linear system which is characterized by random nonlinearity, multiplicative noise and state constraints, so that the performance of filters is improved.

The invention discloses an aircraft tracking control direct method with input saturation to solve the technical problem that input saturation tracking control is difficult to realize if an aircraft has uncertain parameters and external disturbance exists. The method includes the steps: firstly, establishing an aircraft model with a time-varying uncertain parameter and external disturbance, and converting a non-linear system into a linear parameter varying error system through linearization along a time-varying path; then, obtaining a convex polyhedron description form of the error system through a tensor product model transform method, and directly describing a saturation effect of a control quantity also through a convex polyhedron structure if the state of the system is restricted within some local scope; and finally, on the basis of the robustness H-infinite theory, obtaining an input saturation controller by solving linear matrix inequations with limited number, the controller accurately tracking instructions and effectively inhibiting disturbance within the system state local range. In particular, if state constraint matrixes are made to be equal to control matrixes, saturation of the controller can be prevented.

The invention discloses an input saturation-considered unmanned surface vehicle full-state constraint trajectory tracking control method, relates to an unmanned surface vehicle control method, and aims at solving the problem that existing unmanned surface vehicle trajectory tracking control-oriented control methods do not process state constraint and saturation problems. According to the method, akinetic model of a 3-degree of freedom and multiple-input-multiple-output unmanned surface vehicle; a saturated closed-loop system is established and a self-adaptive method is selected to estimate squares of unknown interference upper limits and control input difference upper limits; and self-adaptive laws are designed for unknown interferences and control inputs according to the self-adaptive method, and a controller is designed according to a pseudo-inverse condition so as to control the unmanned surface vehicle. The method is suitable for the control of unmanned surface vehicles.

The invention relates to an under-actuated surface ship trace tracking control method based on model predication control, which can be used for obtaining optimized tracking performance for ensuring the stability of a system according to given performance indexes on the basis of meeting under-actuated system input and state constraints. The under-actuated surface ship trace tracking control methodcomprises the following steps: 1) projecting a trace tracking error model to a body coordinate system; designing by utilizing a Lyapunov direct method and a backstepping method and enabling tracking errors to be gradually close to a converged control rule; combining system constraints to solve a terminal invariant set; 2) acquiring a system state of a current moment and constructing an MPC (Multi-point Constraint) optimization problem containing terminal constraints of a limited time domain; 3) solving the MPC optimization problem and acquiring an optimal control sequence which is predicted atthe current moment; taking first optimal control to act on the system; 4) acquiring a new system state at a new sampling moment and updating the MPC optimization problem; carrying out rolling iteration until a tracking control process is finished. The method provided by the invention not only considers actual constraints of the system, but also can acquire optimized tacking performance by utilizing a relatively short predication time domain according to the given indexes.

The invention discloses a method for generating a flight track of a multi-rotor unmanned aerial vehicle based on second-order cone programming, belonging to the technical field of track planning. Themethod is realized by the following steps: establishing an optimal control problem model including performance indexes, kinematical constraints, state constraints, thrust constraints, inclined angle constraints and obstacle avoidance constraints aiming at the track generation problem of the multi-rotor unmanned aerial vehicle; and converting an optimal control problem into a second-order cone programming problem based on a discretization method and successive linearization, and carrying out iteration solving on the second-order cone programming problem, so as to obtain the flight track of a multi-rotor unmanned aerial vehicle which meets complex constraints. According to the method, the flight track of a multi-rotor unmanned aerial vehicle which meets complex constraints is established based on a second-order cone programming method according to the requirements of actual tasks; and the method has the advantages that the track generation efficiency is high, and the optimality of a track result is good.

The invention discloses an adaptive neural network control method for an arc micro-electromechanical system, which comprises the steps of a, building a system model of the arc micro-electromechanicalsystem based on the Bernoulli beam; b, constructing an adaptive neural network controller used for suppressing chaotic oscillation of the arc micro-electromechanical system and guaranteeing state constraints of the system, wherein when the adaptive neural network controller is constructed, output constraints of the arc micro-electromechanical system are ensured not to be violated by using a symmetrical obstacle Lyapunov function, an unknown non-linear function is estimated with an arbitrary small error by adopting an RBF neural network with an adaptive law, an extension state tracking differentiator is introduced to process a problem that virtual control items in backstepping control need to be derived repeatedly, a state observer is designed to obtain unmeasured state information, the extension state tracking differentiator and the state observer are integrated in the backstepping framework. The adaptive neural network control method has the characteristics of convenient stability analysis and proving, low requirement for the modeling precision, low computation complexity, high operation speed, good operation stability of the system and high motion accuracy.

The invention discloses a full-state constraint rigid mechanical arm safe and reliable control method based on defining learning. The method includes the following steps that a kinetic model and an expected period track of a full-state constraint rigid mechanical arm are established; a state converter is established; a non-affine model is configured into an affine model; the track error of the angle position of the converted mechanical arm is defined; a compensation track error signal is designed; a neural network controller based on defining learning is designed; and a static neural network controller based on experiential knowledge is established. By means of the method, it can be ensured that the track error is finally converged into a small neighborhood of zero, the mechanical arm can also be limited to run in a given safe work zone, a defining learning theory is adopted, uncertain closed-loop dynamic learning of the rigid mechanical arm is achieved, the converged neural network weight is stored, redundancy training is avoided due to the stored experience knowledge, the responding speed of a system is increased, and the tracking performance on the transient state process of the rigid mechanical arm is improved.

The invention provides a spinning unfolding and folding optimum control method of a dual-body star space tethered formation system. The method includes the steps that first, constraint conditions are determined, wherein the constraint conditions comprise a controlled quantity constraint, a state constraint, a terminal constraint and a dynamics constraint; secondly, performance indexes are selected according to task requirements; afterwards, the optimum control quantity M and the optimum ideal condition are acquired through an hp-self-adaptation pseudo-spectral method; at last, a state error measuring controller and an executing mechanism error controller are designed to control errors of the ideal condition and the optimum control and errors of the virtual condition and practical control respectively. According to the spinning unfolding and folding optimum control method of the dual-body star space tethered formation system, a spinning kinetic model is established based on spinning motion, the dual-body star space tethered formation system can be controlled to complete a spinning unfolding and folding task smoothly under the certain performance indexes and the constraint conditions, and certain theoretical reference is provided for spinning unfolding and folding control of a general dual-body star space tethered formation system.

The invention discloses a new energy consumption evaluation method based on a minimum load shedding model. The method mainly comprises the following steps: 1) obtaining data of an electric power system within T years, and constructing an electric power system N-1 preconceive fault set; 2) building a typical operation scene of the electric power system; 3) performing optimized dispatching on a hydropower station of the electric power system, so that the power system can meet a normal operation constraint condition in a normal operation state; 4) inputting electric power system data into a minimum load shedding model to obtain an expected value of the minimum load reduction amount, so that the electric power system meets a fault state constraint condition under the N-1 preconceive fault state; 5) calculating to obtain a new energy penetration rate upper limit and a new energy consumption capacity; and 6) establishing a relation curve of the new energy penetration rate and the expected value of the minimum load reduction amount. The method is suitable for hydroelectric rich regions. According to the method in the invention, the power supply flexibility in the system is fully considered, the new energy consumption level is improved, and the new energy consumption capability of the system is accurately evaluated.

The invention puts forward a photothermal power station with electric heating devices and a modeling and operation optimization method of the photothermal power station. A model is applicable to the independent operation photothermal power station, a multi-energy complementary system with wind power, photovoltaic and photothermal power generation functions and other scenes, and multiple operationconstraints are considered and comprise a thermal power balance constraint with hot salt tanks as nodes, a thermoelectric conversion relation constraint of the electric heating devices, a heat tank hourly heat accumulation state constraint, a constraint that stored heat is equal to released heat in a calculation cycle, a thermoelectric conversion constraint of a turbonator, a starting heat constraint and an electric power balance constraint of a steam turbine, a wind curtailment and photoelectric power constraint used for the electric heating devices, and other constraints. The mixed integer linear optimization technology is adopted to solve the optimization problem. By additionally installing an appropriate amount of electric heating devices in the photothermal power station, the electricquantity curtailment of new energy can be effectively reduced, the photothermal electric energy production is increased, and the operation economy of the photothermal power station and the multi-energy complementary system is improved.

The invention provides a collaborative positioning system and method based on node motion state constraint. All nodes in the network are positioned through position information of nodes with self-positioning information and relative distance information of nodes. According to the collaborative positioning algorithm, first, state information of nodes are predicted based on motion state constraint of the nodes; then, relative distance information of the nodes are fused based on all prior information, so as to obtain observation information of node positions; and finally, the predicted information is modified by using the observation information of the node positions, so as to obtain posterior estimate of the node state. According to the method, the position information of the node is predicted by using node motion state constraint, so that the node position is predicted more accurately, and the node is positioned more precisely; when the node speed is high or the network connectivity ispoor, the method is more stable than traditional positioning methods.

The invention relates to a cooperative control method for full-state constraint mechanical arm trajectory tracking, and belongs to the technical field of control engineering. The method combines ABLF-based thrust-reversing control with Hamilton energy theory-based control, and builds a cooperative controller: establishing a mechanical arm system dynamics equation of n-joint constraint, and performing coordinate transformation on the equation to obtain a state-space equation of the system; designing an ABLF-based thrust-reversing controller, so as to improve system initial response speed, and prevent constraint from being damaged at the same time; designing the Hamilton energy theory-based controller, so as to improve tracking stability of a later period of system response; and designing the cooperative controller to realize rapid and stable control of a full-state constraint mechanical arm system. ON the premise of not damaging a full-state constraint condition, the cooperative controlmethod provided by the invention can improve dynamic-state and steady-state performance of the system, ensure fast mechanical arm system response speed and high positioning precision, and can effectively improve working performance of the mechanical arm in a robot system.

The invention provides an electric peak regulation method and an apparatus thereof and relates to the electric power energy field. In the prior art, when an electric quantity which needs to be adjusted is large, a regulation method has a great influence on a service life of energy storage equipment. In order to solve the above problem, the invention provides the electric peak regulation method. The method comprises the following steps of calculating an average electricity power prediction value Pave of a load center in a load center adjusting time period and an adjustable total power amount R; acquiring one adjusting coefficient un corresponding to each time slice tn in the load center adjusting time period acquired and calculated by an electric power company control system; and according to the un and a preset constraint condition, determining an adjusting parameter of each piece of equipment, wherein the preset constraint condition includes an energy storage equipment health state constraint condition; and in the time slice tn corresponding to the un, according to the adjusting parameter, adjusting power of each piece of equipment. The method and the apparatus are applied to a process of an electric peak regulation participation auxiliary service of a load center.

The present invention relates to a modification method of a space camera on-orbit micro-vibration simulation model, belonging to the field of the space camera on-orbit micro-vibration tests, and filling the gap of modification of the space camera on-orbit micro-vibration simulation model. The method comprises the following steps of building a space camera finite element model; acquiring installation interface actual input of the space camera in a whole start state; acquiring internal vibration source actual input of the space camera; performing modal test to modify the space camera finite element model; building a space camera dynamics model; performing individual incentive to modify the space camera dynamics model; performing full incentive to modify the space camera dynamics model; and removing ground test state constraints, and adding a space camera on-orbit state constraint, so as to obtain a space camera on-orbit micro-vibration simulation model. Through adoption of the method, the space camera micro-vibration simulation model comprising the optical imaging characteristic model is modified through simulation tests, so that the simulation model is more accurate, and a foundation is laid for time domain and frequency domain response prediction of the space camera in the micro-vibration environment.

The invention discloses an orderly charging and discharging control method for an electric automobile considering the operation constraints of a transmission network. Coordinated control of a power grid and the electric automobile is realized through the two-level scheduling mechanism of a transmission network power scheduling control center and a distribution network scheduling control station under the consideration of N-1 power flow constraint of a transmission network, the power constraint of a charging and discharging facility, the charge state constraint of the electric automobile, the user charging and discharging demand and the scheduling willingness based on wireless communication, a GPS (Global Positioning System), a GIS (Geographic Information System) and electric automobile V2G. Compared with an existing orderly charging and discharging control method for the electric automobile, the method has the advantages that the peak-shaving effect and scheduling flexibility of charging and discharging for large-scale electric automobiles can be brought into better play; the interaction between the electric automobile and the power grid is expanded to the level of the transmissionnetwork; the charging and discharging behaviors of the electric automobile respond to the operation state of transmission network; and the N-1 static security of the power grid can be further enhanced.

The invention relates to a personal goal video capture method and system, and the method comprises the steps: obtaining the 3D positions of basketballs at all moments after the goal is identified, andobtaining a goal track according to the 3D positions of the basketballs at all moments, the basket position, the goal moment, and the motion state constraint; obtaining and determining the throwing time and throwing position of the current player based on the obtained goal track, determining the goal player according to the throwing time and throwing position based on the position of each playerat each moment, and outputting a goal video. Compared with the prior art, , the goal track is obtained through the 3D position of the basketball at each moment, the basket position, the goal moment and the motion state constraint, then the goal player is obtained based on the goal track, and the method can be achieved through simple and mature equipment such as a common monitoring camera and a common computer, so that it is achieved that the method is low in implementation cost, high in reliability and suitable for installation of a common court.

The invention discloses an asynchronous motor command filtering fuzzy control method based on state constraints. An obstacle Lyapunov function is constructed to ensure that the rotor angular velocity,stator current and other state variables of an asynchronous motor drive system are always within a given state interval. A command filtering technology is introduced to overcome the 'computation explosion' problem which cannot be avoided by the traditional back-stepping method, and a filtering error compensation mechanism is introduced to eliminate the influence of filtering error. A fuzzy logicsystem is adopted to approximate a nonlinear term in the system, and a command filtering fuzzy controller is constructed. In addition, a more accurate model is used in view of the iron loss of the asynchronous motor. The simulation results show that the method not only can achieve an ideal position tracking effect, but also can avoid safety problems caused by the violation of state constraints byconstraining the rotor angular speed, stator current and other state variables within a given constraint interval.

The invention provides an auto-disturbance-rejection control method for a motor servo system with consideration of the state constraint. The method comprises: step one, establishing a motor position servo system model; step two, designing an auto-disturbance-rejection controller of a motor servo system with consideration of the state constraint; and step three, adjusting parameters of an auto-disturbance-rejection control law of the motor servo system with consideration of the state constraint to enable the system to meet a control performance index.

The invention belongs to the technical field of asynchronous motor position tracking control, and specifically discloses a state constraint based asynchronous motor fuzzy position tracking control method. The method is characterized in that state variables and controlled variables of a motor system are constrained based on a Barrier Lyapunov function in allusion to control accuracy requirements for an asynchronous motor and a nonlinear problem in a driving system, a fuzzy logic system is utilized at the same time to approach to a nonlinear function in the system at the same time, and a fuzzy adaptive position tracking controller is built. According to the method, a tracking error of the system can be ensured to converge to a small enough neighborhood of the origin, simulation results show that the new control method ensures each state variable of the motor to be within a constraint space of the system, and controller input ud and controlled input uq are stabilized within a bounded region. The method disclosed by the invention realizes fast and effective response for asynchronous motor position tracking control.

The invention discloses a wheeled mobile robot point stabilization rolling optimization control method which comprises the following steps of: based on a dynamic model of a mobile robot of a global coordinate system, combining control constraint and state constraint into design of a point stabilization controller by using a state feedback model prediction control method; finally designing a smooth stabilization control rule expression equation of a mobile robot control system through variable substitution. Therefore, the problem of point stabilization control stability caused by incomplete constraint of the mobile robot self, the problem of point stabilization control stability caused by inevitable acceleration and speed constraint of a movement execution system of the mobile robot self, and the problem of point stabilization control stability caused by uncertainty of various external environments can be solved, and movement rapidness and accuracy can be effectively improved while good mobile robot movement tracks are ensured.

The invention discloses a quick gradient algorithm for solving a model prediction control law in real time, and belongs to the technical field of model prediction control. Firstly a general MPC problem is converted into a standard quadratic programming problem; inequality constraints are relaxed by utilizing an augmented Lagrangian multiplier method; a dual problem of the problem is solved by utilizing an original quick gradient algorithm; in the process of solving the dual problem, an internal QP problem with equality constraints needs to be solved; KKT conditions can be used for performing solving; and a Lipschitz constant is obtained by offline solving an SDP problem, so that the algorithm has different step lengths in different solving directions during iteration. The MPC problem withgeneral input state constraints is solved; an objective function is not required to be a strict convex function; the MPC problem types which a quick gradient method is suitable for are expanded; and the convergence speed of the algorithm is greatly increased.

The invention relates to a virtual synchronous control method and a rotor-side frequency converter controller. The method comprises the steps of determining a virtual inert mass response state constraint factor of a doubly-fed wind turbine generator according to a system frequency change of the doubly-fed wind turbine generator; correcting a rotation speed of a virtual synchronous machine of the doubly-fed wind turbine generator by use of a correction equation for the rotation speed of the virtual synchronous machine of the doubly-fed wind turbine generator; and performing virtual synchronouscontrol on the doubly-fed wind turbine generator according to the corrected rotation speed of the virtual synchronous machine, wherein the correction equation for the rotation speed of the virtual synchronous machine of the doubly-fed wind turbine generator is determined according to the virtual inert mass response state constraint factor of the doubly-fed wind turbine generator. According to themethod provided by the invention, for the problem of reduction of inertia of a grid-connected system caused by grid connection of the large-scale doubly-fed wind turbine generators, the anti-interference capability and stability of the doubly-fed wind turbine grid-connected system can be improved.

The invention relates to a peak-valley price driven optimized dispatching method before an energy storage peak shaving day. The method is characterized by comprising the steps of charge and dischargeinterval priority establishment, an optimized dispatching process before the energy storage peak shaving day, to-be-met constraint conditions in an operation process of an energy storage system, charge and discharge state constraint of the energy storage system, a power optimization method based on a particle swarm algorithm, and dispatching scheme evaluation indexes. According to the method, theenergy storage system is fully utilized, so that a peak clipping valley filling effect and the economy of the energy storage system are improved.

The invention discloses a fault-tolerant control method for a hypersonic aircraft elevator with state limitation. For the longitudinal model of a hypersonic aircraft, an adaptive fault-tolerant controller is proposed to realize state constraint under consideration of the internal coupling of a system. The complexity caused by aerodynamic uncertainty, external disturbances and elastic modes is considered throughout the controller design process. The method comprises the steps that a sliding mode control method is introduced in the first step of a backstepping process to handle the coupling of the system; the obstacle Lyapunov function is applied to the subsequent backstepping process to ensure that the angle of attack and pitch rate are limited; moreover, due to the introduction of the dynamic surface method, the problem of differential explosion is avoided; and finally, the fault-tolerant controller structure is designed for the unknown fault of the elevator. According to the invention, the coupling problem and the state limitation problem of the system can be simultaneously handled, and the accuracy of the control system is improved.