50 results about "Riccati equation" patented technology

The invention relates to an optical integral sliding-mode attitude control method of a reentry vehicle and a controller, and belongs to the technical field of vehicle control. The optical-integral sliding-mode attitude control method comprises the following steps of: firstly designing an SDRE (State-dependent Riccati Equation) nominal attitude control law according to a nominal model of the vehicle, and enabling the performance of a nominal system to meet the proposed optimal indexes; then considering the uncertainty of the system, designing an integral sliding-mode control law on the basis of the SDRE nominal attitude control law, enabling the system to have robustness while meeting the performance index requirement; and in order to weaken the buffeting, introducing a design idea of a second-order sliding mode and enabling the output of the controller to be smoother. The attitude controller designed by the invention not only can guarantee the expected indexes, but also has better robustness.

The invention discloses a spacecraft automatic rendezvous obstacle avoidance method and system. The method comprise the steps of solving the shortest Euler distance under the ellipsoid, constructing atarget attraction potential function, constructing an obstacle avoidance potential function under the sigmoid function, designing a controller based on a speed artificial potential function, and designing a suboptimal speed artificial function controller based on the state dependent Riccati equation. The method is applicable to spacecraft automatic rendezvous obstacle avoidance control, and can calculate the distance between the spacecraft and a target spacecraft or an obstacle more accurately through determining the shortest Euler distance under the ellipsoid, thereby being capable of more accurately controlling the trajectory of the spacecraft, and reducing unnecessary fuel consumption; and meanwhile, the sigmoid function is introduced into the aerospace field for the first time to define the obstacle avoidance potential function so as to form the overall potential function and thus design appropriate control laws, thereby being capable o more accurately controlling the trajectory of the spacecraft when being away from or getting close to the obstacle, and having more accurate flight trajectory and higher response speed.

The invention discloses an optimal integral sliding mode control method, relates to an integral sliding mode control method, and belongs to the technical field of control. The optimal integral sliding mode control method includes the steps: firstly, building a dynamic model of a second-order nonlinear system; secondly, realizing system state finite-time convergence through an ISDRE (improved state-dependent Riccati equation), and effectively compromising the contradiction between system response time and overshoot; thirdly, combining the ISDRE with an integral sliding mode to further improve robustness of the system under disturbance. The optimal integral sliding mode control method has universality, and can be applied to control systems such as an aircraft and an inverted pendulum.

The present invention discloses a robust-adaptive neural network H-infinity control method of a MEMS gyroscope. A controller is designed based on a Riccati equation, and includes two parts of a basic neural network controller constructed by utilizing a strong online approximating capability of the neural network and a robust control item used for overcoming influences of external disturbance and parameter uncertainty on MEMS gyroscope system output tracking errors and ensuring system closed-loop stabilization. Parameters in a adaptive adjustment neural network system based on a Lyapunov stability theory are adopted, thus to ensure stability of the system. The controller is based on the Riccati equation, such that non-linear phenomena in the system are compensated, the precise tracking aim is achieved, stability of the system and robustness to external disturbance are raised, and industrial utility values are achieved.

Systems and methods for adaptive control are disclosed. The systems and methods can control uncertain dynamic systems. The control system can comprise a controller that employs a parameter dependent Riccati equation. The controller can produce a response that causes the state of the system to remain bounded. The control system can control both minimum phase and non-minimum phase systems. The control system can augment an existing, non-adaptive control design without modifying the gains employed in that design. The control system can also avoid the use of high gains in both the observer design and the adaptive control law.

The invention discloses a multipoint pre-aiming LQR transverse control method based on a Fiala brush tire model. The method comprises the steps that 1, establishing a vehicle two-degree-of-freedom kinetic model and a tracking error model based on a vehicle striking center; 2, establishing a state space equation of the system; 3, combining the path curvature serving as disturbance quantity with a state vector of the system to construct an augmented LQR control problem; 4, solving a Riccati equation of the augmented LQR system to obtain an optimal feedforward control quantity and an optimal feedback control quantity; and 5, utilizing the obtained optimal control quantity, namely the front wheel lateral deviation force. According to the invention, curvature information of a plurality of roadpoints can be pre-aimed through the LQR controller in a limited time domain; in addition, the front wheel lateral deviation force can be restrained through the front wheel rotating angle under the condition that the vehicle has large transverse acceleration, so that the vehicle can keep good transverse stability and path tracking precision, and the situation that the vehicle is unstable due to tire force saturation under the limit working condition is avoided.

The invention discloses a rolling time domain tracking control method for a batch injection molding process. The method comprises the steps: building an input and output model by collecting input and output data, selecting an appropriate state variable to build a state space model, further converting the state space model into an expansion state space model containing output and tracking errors, then selecting a performance index containing terminal state, and solving an optimal control law according to a Riccati equation and a boundary condition. Different from a conventional state space model, the novel model of the method takes both a state variable and a tracking error into consideration. On the basis of the newly-designed model, a controller is more flexible to adjust by increasing an adjustable weight coefficient, and then a system can have the better control performance.

A method for processing acoustic waveforms comprises acquiring acoustic waveforms in a borehole traversing a subterranean formation and transforming at least a portion of the acoustic waveforms to produce frequency domain signals. Then model dispersion curves are generated based on an anisotropic borehole-formation model having a set of anisotropic borehole-formation parameters and by specifying governing equations and using a matrix Riccati equation approach. The frequency-domain signals are back-propagating using the model dispersion curves to correct dispersiveness of the signals and coherence of the back-propagated signals is calculated. Alternatively the difference between the measured and the model dispersion curves is determined. Model parameters are iteratively adjusted until the coherence reaches a maximum or exceeds a selected value, or alternatively until the difference between the measured and the model dispersion curves becomes minimal or is reduced to below a selected value. Then at least a portion of the set of anisotropic borehole-formation parameters is obtained.

The invention discloses a PMSM (permanent magnet synchronous motor) coordination control optimization method based on mechanical connection, and the method comprises the steps: designing a single PMSMcontrol algorithm, determining a synchronous control structure of a dual-motor drive system, building a dual-PMSM dynamic mathematic model, writing the mathematic model into a singular perturbation system form, carrying out the decomposing of the subsystems, decomposing an optimal state adjustment problem and a performance index, solving a subsystem Riccati equation, combining optimal solutions of the subsystems into the optimal solution of a main system, and achieving the optimization of the dual-PMSM coordination control. The method can achieve the dual-PMSM coordination control through thereduction of the synchronization error between motors, and does not depend on the tracking error and control precision of a single motor for achieving the coordination control between motors. The method is simple in design, is easy to understand, is small in calculation burden, and is high in practicality. The method reduces the solving orders of the system through the singular perturbation theory, and reduces the calculation burden during system design.

The invention discloses a BTT guidance control method for a near-space hypersonic flight vehicle. The guidance control method includes the steps that S1, a combined control model of a rolling channel and a yawing channel is established based on the aileron control quantity of the rolling channel, and a control model of a pitching channel is established based on the pitching control quantity; S2, a nonlinear state equation of BTT guidance is established based on the kinetic parameters of the flight vehicle, and the nonlinear state equation is transformed into a state-dependent linear-like structure; S3, by adopting a Riccati equation control method, a guidance law model of the rolling channel, the yawing channel and the pitching channel of the flight vehicle is obtained according to the state-dependent linear-like structure. The guidance control method solves the problem of multichannel cross coupling in BTT control of the near-space hypersonic flight vehicle and can meet the demand for high-precision control of the near-space hypersonic flight vehicle.

The invention provides a design method of an optimal secondary regulator of a dynamic reactive power compensation device. The design method of the optimal secondary regulator of the dynamic reactive power compensation device comprises the following steps: sampling a reactive power output by the reactive power compensation device and a thyristor amplification coefficient, and obtaining a transfer function of the reactive power compensation device by utilizing a model identification algorithm; in the form of observable standard form of a control system theory, designing a continuous time state equation of the reactive power compensation device; setting up an optimizing index function; solving a Riccati equation; calculating a gain matrix of the optimal secondary regulator of the reactive power compensation device; and obtaining an input thyristor amplification coefficient of a control system of the reactive power compensation device. According to the dynamic and static performance required by a designer, the design method of the optimal secondary regulator of the dynamic reactive power compensation device can obtain the optimal parameters of a controller by solving the Riccati equation, guarantees the system to have the optimal control performance, achieves the tracing control of an output reactive power by utilizing the function of the optimal secondary regulator, and has quite excellent system performance.

The invention provides a method for implementing arbitrary linear controller by using an active disturbance rejection control structure. According to the method, under the premise of a known strict regular controller K, linear transformation is introduced to describe the controller K and a conventional LADRC controller in a state space to obtain an asymmetric Riccati equation between the parameters of the two controllers, the asymmetric Riccati equation is solved to obtain an adjustable LADRC controller with the same anti-interference and robust performance as the controller K, and online adjustment is performed on the adjustable LADRC controller to obtain ideal control performance. According to the method provided by the invention, the control of the arbitrary linear controller is achieved by using the active disturbance rejection control structure, so that the control system is simple and reliable; and based on the linear system theory, and under the state space description of the control theory, the implementation of the corresponding LADRC is obtained through a linear transformation manner, which is more accepted by engineering designers.

The invention relates to the field of system fault detection, and particularly relates to a fault detection method for a vehicle crosswise power remote measurement and control system. The method comprises the steps that the state space model of the vehicle crosswise power remote measurement and control system is established; the data packet loss characteristic of a multi-measurement channel under a TCP class protocol is described by a Bernoulli random variable; the quantization error of the channel is represented by a logarithmic function; measurements with data packet loss and quantization errors are used to design a fault detection filter based on an observer to generate residuals; data packet information in intermittent measurements is used to define an index as described in the description based on a generalized transfer function operator, and the index is maximized; a filter parameter matrix is acquired by solving a modified Riccati equation; a residual evaluation function value is calculated; and decision logic is set to realize fault detection. According to the invention, the fault detection of the vehicle crosswise power remote measurement and control system with data packet loss and quantization errors under the TCP class protocol is realized, and the detection reliability is improved.

The invention provides a continuous time state estimation method based on a Kalman-Bucy filter. The continuous time state estimation method is characterized in that a continuous time state equation of a reactive compensation device under the white noise interfering condition is obtained; a process interfering noise matrix and a measurement noise matrix in the continuous time state equation are substituted into a Riccati equation, and gain coefficients of the Kalman-Bucy filter are obtained through the Riccati equation; and the Kalman-Bucy filter is constructed, and a continuous time state estimation value of the reactive compensation device is obtained. By the method, an unbiased estimation value of the reactive compensation device can be obtained, and process noise and measurement noise interference of the reactive compensation device can be effectively filtered; and the method has a better filtering effect compared with the conventional method in which an observer is used and very suitable for electrical equipment such as the reactive compensation device which is complex in electromagnetic interference.

The invention discloses a self-driving automobile transverse motion self-adaptive parameter control method. The method comprises the following steps: (1) acquiring vehicle motion parameters, and establishing a two-degree-of-freedom vehicle dynamics model; (2) discretizing a coefficient matrix of the vehicle dynamics model, establishing a Riccati equation, and solving a feedback matrix K through an LQR algorithm; (3) performing mean filtering and limiting on the transverse error matrix; and (4) calculating the front wheel turning angle of the vehicle according to the feedback matrix and the error matrix, and controlling the transverse movement of the vehicle through the size of the front wheel turning angle. According to the method, the feedback matrix K is solved through the discretization speed, time waste caused by repeated iteration in the solving process of the LQR algorithm is avoided, the parameter table of the speed and the value of the feedback matrix K is established in advance, and the solving speed of the LQR algorithm is increased.

The invention belongs to the advanced control field of the industrial process and relates to a limited rolling time-domain hybrid tracking control method for a batch injection molding process. Input and output data are collected to establish input and output models at different stages; a multi-stage state space model is established by selecting proper state variables, the state space model is further converted to an extended state space model containing state variables and output tracking errors, and the model is expressed by a switching system model; and performance indexes including terminalstates are selected for different stages and an optimal hybrid control law is calculated by combining a Riccati equation and a boundary condition. The control law has an added adjustable weighting coefficient, so that adjustment becomes flexible and the system obtains the improved control performance. At different stages, a residence time method depending on the Lyapunov function is designed; andthe result obtained by the method does not need to introduce any other variables, so that the method becomes simple and is easy to implement and the system operation time is shortened and the production efficiency is improved.

The invention discloses a switching controller design method of constrained space spacecraft orbital rendezvous. A switching controller based on residence time is designed by means of mathematical modeling of a space spacecraft rendezvous system, conversion of an asymmetric saturation function, a residence time method of a switching controller, a parametric Riccati equation method and the like. A control system with asymmetric input saturation is equivalently expressed as the control system with a plurality of asymmetric input saturation. In fact, the obtained equivalent symmetric input saturation system is essentially a switching system. The designed controller only needs to solve the parametric Riccati equation in an offline mode, which is simple and easy to operate, and a calculation amount is low. By using the control method provided in the invention, a convergence speed of a control system state can be effectively increased and a requirement of an aerospace field to fast convergence performance of the control system can be satisfied.

The invention relates to a method for regulating speed of an intelligent vehicle by using an energy dissipation theory. The method for regulating the speed of the intelligent vehicle by using the energy dissipation theory is characterized by comprising the steps of regulating and converting the speed of the intelligent vehicle into a dissipation control problem with an energy storage function as an optimization object by using a common Gamma dissipation inequality in a dissipation system; constructing the energy storage function for guaranteeing Gamma dissipation by using an Lyapunov method designed on the basis of Backstepping; and calculating an optimal control law of vehicle speed regulation by gradually approaching the Gamma dissipation inequality. The method for regulating the speed of the intelligent vehicle by using the energy dissipation theory has the beneficial effects that the optimal control law of the vehicle speed regulation is obtained by converting the speed regulationand control of the intelligent vehicle into the dissipation control problem with the energy storage function as the optimization target, by using the Lyapunov direct method to replace a Riccati equation with complicated calculation and by gradually approaching the Gamma dissipation inequality.

The invention discloses a Kalman filtering method based on an analog circuit and the analog circuit. The method is characterized in that based on the continuous-time Kalman filter equation, and according to a solution method of Riccati equation, a steady-state solution of the Kalman filter equation is obtained; and after entering a steady state, filtering parameters become constants, such that various operation links can be achieved with analog devices such as an operational amplifier. Experiments show that the estimated result obtained by using the method of the invention is consistent with the result of the Kalman filter achieved in a digital form, so the method of the invention is feasible.

The invention relates to a multi-soliton implement method based on a simultaneous schrodinger equation, and belongs to the technical field of optical fiber communication. According to the multi-soliton implement method, through introduction of topologies and nonlinear transformation and by utilization of a Riccati equation mapping method, the simultaneous schrodinger equation is researched to construct a precise solution of a system. Through proper setting for an arbitrary function in an equation analytical solution, a novel oscillating soliton structure is obtained, and eventually multi-solitons of different numbers can be obtained by utilization of a Weierstrassp function. The problem that the multi-solitons are difficult to generate in the optical fiber communication technology is solved. The multi-soliton implement method based on the simultaneous schrodinger equation is simple, easy to understand, convenient to implement, strong in practicability, and capable of being adjustable in relevant parameters according to actual situations, providing powerful support for in-depth study of the filed of optical fiber communication systems and promoting the development of the subject.

The invention discloses a design method for an LQG controller of an LPV system based on data driving. The method comprises steps of S1, building a system equation, carrying out the equal-time-intervalsampling of sensor inputs under different parameter conditions, carrying out the order reduction of the sensor inputs through a POD method, and obtaining an order reduction basis; S2, under the condition of different parameters, a system filtering algebra Riccati equation and a controller algebra Riccati equation being calculated respectively, and a filter gain and a controller gain being obtained; S3, a database being established, reduced-order bases of all prior parameters and the two gains obtained in the S2 being in one-to-one correspondence and stored in the database, the reduced-order bases serving as learning bases of a machine learning classifier, a proper machine learning model being selected, the learning bases in the database serving as a training set, the two corresponding gain parameters serving as labels, and the classifier model being designed; wherein the classifier model is the LQG controller. The controller can be used online in real time. According to the method, the stable reaction speed and control precision of the system are effectively improved, and the interference can be greatly reduced.

The invention discloses a power system controller determination method. The method comprises the following steps of constructing a state equation model of the power system; determining a state coefficient matrix and a control coefficient matrix of the power system state equation model; determining a stability correlation constant n according to the expected closed-loop pole distribution; solving an improved Riccati equation based on the power system state equation model with the parameters to obtain a solution matrix; determining an optimal controller based on stability according to the solution matrix, and enabling all closed-loop poles to be located at the left side of s =-n through the action of the controller, thereby improving the stability of the power system.

The invention provides an optimal secondary Gauss controller of a dynamic reactive power compensation device. A thyristor control angle of the reactive power compensation device is sampled and serves as an input quantity, a reactive power of the reactive power compensation device is sampled and serves as an output quantity, model orders of the reactive power compensation device are selected, and a continuous time state equation of the reactive power compensation device is obtained by utilizing a model identification algorithm according to input data and output data, a Kalman filter is designed according to the obtained continuous time state equation of the reactive power compensation device, and an estimated value of a state variable of the reactive power compensation device is obtained by utilizing the Kalman filter; an indicator function is established and optimized, an emphasis matrix of state energy and an emphasis matrix of control energy are set according to empirical and actual dynamic and static requirements; a Riccati equation is solved to obtain a positive definite symmetric matrix; a gain matrix of the optimal secondary Gauss controller of the reactive power compensation device is calculated according to the positive definite symmetric matrix; a given gain matrix of the reactive power is calculated; and the optimal secondary Gauss controller of the reactive power compensation device is constructed to obtain the input of the thyristor control angle.

The invention discloses a Kalman filtering method based on an analog circuit and the analog circuit. The method is characterized in that based on the continuous-time Kalman filter equation, and according to a solution method of Riccati equation, a steady-state solution of the Kalman filter equation is obtained; and after entering a steady state, filtering parameters become constants, such that various operation links can be achieved with analog devices such as an operational amplifier. Experiments show that the estimated result obtained by using the method of the invention is consistent with the result of the Kalman filter achieved in a digital form, so the method of the invention is feasible.

The invention discloses a robust consensus method based on an LPV multi-agent system. The method comprises the following steps of establishing an uncertain linear LPV multi-agent system, introducing anew upper bound of a P matrix in a continuous Riccati equation into the system, applying a static protocol controller to the multi-agent system to obtain a multi-agent robust model, applying an edge-based adaptive strategy to the system to obtain an adaptive model, and applying a node-based adaptive strategy to the system to obtain an adaptive model. According to the method, a time-varying linearparameter is introduced into a multi-agent system to serve as external disturbance, and a new upper bound of a P matrix in a continuous algebra Riccati equation is utilized to obtain a sufficient condition, related to algebra connectivity, of the system; and an edge-based adaptive strategy and a node-based adaptive strategy are introduced, so that the multi-agent system can reach a consensus moreeasily.

The invention provides a design method of an optimal secondary regulator of a dynamic reactive power compensation device. The design method of the optimal secondary regulator of the dynamic reactive power compensation device comprises the following steps: sampling a reactive power output by the reactive power compensation device and a thyristor amplification coefficient, and obtaining a transfer function of the reactive power compensation device by utilizing a model identification algorithm; in the form of observable standard form of a control system theory, designing a continuous time state equation of the reactive power compensation device; setting up an optimizing index function; solving a Riccati equation; calculating a gain matrix of the optimal secondary regulator of the reactive power compensation device; and obtaining an input thyristor amplification coefficient of a control system of the reactive power compensation device. According to the dynamic and static performance required by a designer, the design method of the optimal secondary regulator of the dynamic reactive power compensation device can obtain the optimal parameters of a controller by solving the Riccati equation, guarantees the system to have the optimal control performance, achieves the tracing control of an output reactive power by utilizing the function of the optimal secondary regulator, and has quite excellent system performance.

The invention discloses the fault diagnosis method of catalytic cracking main draught fan group closed-loop control in petrochemical equipment. The method comprises the following steps that step1, ifthe uncertainty and nonlinear structure information of a model are known, an unknown input observer method can be adopted so that a gain from a control signal to a residual signal is zero, which meansthat the residual signal is decoupled from the control signal; and step2, if decoupling can not be realized, the affects of the residual signal and uncontrollable factors can be minimized in the sense of mathematical expectation or a robustness rule, and a forward or backward recursive Riccati equation is used to solve. In the invention, under the condition of a closed loop, different operationscan be performed depending on whether feedback can be completely decoupled so that an equipment fault can be effectively diagnosed under the closed-loop state.

The invention discloses a differential game guidance law design method considering the observation of the target acceleration direction. The steps are: 1) Obtain the dynamic equation of the missile and the target based on the terminal guidance premise; 2) Assume that the target maneuver includes disturbance maneuver and escape maneuver, and the missile maneuver includes Disturbance maneuvers and pursuit maneuvers, combined with related payoff functions to obtain a differential game problem considering disturbance maneuvers; 3) Using the state-dependent Riccati equation method to solve the above differential game problems, and obtaining a differential game guidance law considering disturbance maneuvers; 4 ) Assuming that the target only performs disturbance maneuvers and the missile only conducts pursuit maneuvers, the guidance law in 3) is simplified to obtain the differential game guidance law including real-time target acceleration; 5) Under the condition of delayed information, the target acceleration is obtained by compensating the target acceleration direction observation method Predicted value; 6) Replace the real-time target acceleration value in 4) with the predicted value of the target acceleration, and obtain the differential countermeasure guidance law considering the observation of the target acceleration direction.