14 results about "Riccati equation" patented technology

The invention discloses a flexible joint mechanical arm AISMC compensation control method under singular perturbation decomposition, and belongs to the field of flexible joint mechanical arm control, and the method comprises the following steps: S1, building a flexible joint mechanical arm dynamic model containing uncertain composite disturbance, and decoupling the model into a slow variable subsystem and a fast variable subsystem; s2, estimating lumped matching disturbance in the slow varying subsystem by using a compensation function observer; s3, constructing an integral sliding mode surface and a self-adaptive reaching law with dead zone correction for the slow-varying subsystem; designing a linear quadratic regulator for the quick-change subsystem, defining a performance index, and solving a Riccati equation to obtain an optimal control law; s4, superposing the slow-varying subsystem control law and the fast-varying subsystem control law to obtain integral control input; and S5, performing simulation verification. By adopting the flexible joint mechanical arm AISMC compensation control method under singular perturbation decomposition, trajectory tracking precision, robustness and stability are considered, and the method has a wide application prospect.

The invention discloses an efficient numerical solution method for a steady-state water head field of a dam containing a complex foundation, and relates to the technical field of geotechnical engineering. The method comprises the following steps: establishing a seepage mathematical model in a Cartesian coordinate system by acquiring foundation parameters and boundary conditions, introducing similar lines parallel to a far-field boundary to construct an improved proportional boundary finite element coordinate system mapping relation, and discretizing and deducing a variable coefficient control equation by adopting a one-dimensional high-order spectrum unit; an equation is simplified into a Riccati equation by analyzing the characteristics of a coefficient matrix, an infinite seepage matrix is solved in combination with Schur decomposition, a seepage matrix at a boundary is obtained through iteration of a fourth-order Runge-Kutta method with the infinite seepage matrix as an initial value, and finally steady-state water head field distribution is obtained. According to the method, the continuity of the interface water head and the flowing boundary condition is guaranteed, the precision and efficiency of complex foundation seepage solving are greatly improved, and reliable technical support is provided for engineering seepage-proofing design and stability evaluation.

The invention discloses a vehicle interaction decision-making method based on an unprotected intersection and a related device, and the method comprises the steps: obtaining a system state matrix, an own vehicle control matrix and an other vehicle control matrix in linear system state equations of an own vehicle and an other vehicle, first to fourth positive semi-definite matrixes and first and second positive definite matrixes are arranged in the optimization target of the linear quadratic differential game problem of the own vehicle and the other vehicle; taking the first positive semidefinite matrix and the third positive semidefinite matrix as a first intermediate matrix and a second intermediate matrix at the Nth moment respectively; according to the first intermediate matrix, the second intermediate matrix, the first positive definite matrix, the second positive definite matrix, the system state matrix, the self-vehicle control matrix, the other-vehicle control matrix, the second positive definite matrix and the fourth positive definite matrix at the Nth moment, reverse recursion is carried out on an optimal control gain matrix equation set of the two vehicles and a coupling Riccati equation of the first intermediate matrix and the second intermediate matrix at the kth moment; and obtaining an optimal control gain matrix sequence of the vehicle, and controlling the vehicle according to a control quantity sequence determined based on the optimal control gain matrix sequence.

The application discloses a spacecraft magnetic moment attitude control method based on a non-inverse iteration algorithm, and the method establishes a linear periodic model for a spacecraft attitude control system which only relies on a magnetic moment; on the basis, according to a linear quadratic optimal control theory, an optimal controller design problem is converted into a solution problem of a discrete periodic Riccati equation associated with the optimal controller design problem; on the basis of a gradient descent principle, an error function is constructed, and a non-inverse iteration algorithm based on the gradient descent principle is proposed to solve the discrete periodic Riccati equation, so that a matrix inversion operation in a traditional solution method is avoided, and the calculation efficiency and the numerical stability are effectively improved; the obtained Riccati equation solution is used to obtain an optimal state feedback control law, so that the spacecraft attitude optimal control only using the magnetic moment is realized, and a new solution scheme is provided for an attitude control problem of a limited actuator in a space task.

The invention discloses an unmanned tracked vehicle trajectory tracking method based on H infinity model prediction hybrid control, which comprises the following steps: firstly, establishing a tracked vehicle dynamics model, and discretizing through a forward Euler method; an H infinity and MPC double-controller parallel computing architecture is adopted, and an MPC controller combines a reference trajectory and a prediction state to generate an optimal control quantity of an adaptive constraint through rolling optimization to minimize a tracking error and a control cost; multi-source interference is introduced into the H infinite controller, and disturbance compensation control quantity is generated through interference modeling, linear processing and Riccati equation solving; and the optimal control quantity and the disturbance compensation control quantity are fused, a crawler executing mechanism is driven, a new state is fed back, and closed-loop feedback control is achieved. The method not only has the dynamic optimization capability of the MPC controller, but also has the strong anti-interference capability of the H infinite controller, realizes synchronous consideration of optimization and robustness, and ensures that the system always keeps trajectory tracking precision and stability under complex working conditions through closed-loop feedback control.

The invention relates to the technical field of intelligent compensation control, in particular to a linear motor driving system control method based on robust baseline control and adaptive compensation. The method comprises the following steps: establishing a linear motor state space model; a dynamic output feedback baseline controller is obtained by iteratively solving a Riccati equation set based on a disturbance suppression level index, a closed-loop matrix is extracted, and a baseline control signal is output; calculating a steady-state gain and filtering the reference input to generate a steady-state feed-forward control signal; estimating the total uncertainty on line through a state predictor, constructing a projection operator to decompose the total uncertainty into a matched component and an unmatched component, performing output equivalent mapping on the unmatched component, and performing band-limiting processing through a low-pass filter to synthesize a self-adaptive compensation signal; and after the three paths of signals are superposed, the linear motor is driven through amplitude saturation and change rate limitation. According to the method, the robustness and the online compensation capability are fused, and the tracking precision and the anti-interference robustness of the linear motor are remarkably improved.

The invention discloses a vehicle control method and device, equipment, a medium and a vehicle, and the method comprises the steps: obtaining vehicle state data; estimating a system state by adopting Kalman filtering based on the vehicle state data to obtain an optimal state estimation value; obtaining a feed-forward gain according to the REPS system state-space equation and the motor torque; obtaining a feedback gain according to the REPS system state space equation and the Riccati equation; and determining an optimal control gain according to the feedforward gain and the feedback gain, and obtaining an optimal control law according to the optimal control gain and the optimal state estimation value, so as to control a motor to drive a steering wheel to rotate through the optimal control law. The method can reduce the external interference influence on the system, accelerates the response speed of the system, enables the actual steering wheel rotation angle and rotation speed to closely track the target steering wheel rotation angle and rotation speed, reduces the tracking error, and achieves the stable control.

The application relates to a kind of multi-channel networked control system asymptotic stability control law design method and system, comprising: establishing the first system model of networked control system with delay and packet loss simultaneously and equivalent expansion to the first system model to obtain the second system model;Establishing intermediate state and equivalent constraint condition to build the third system model;According to the expression of the control law designed by the third system model;Construct Riccati equation and obtain positive definite solution, substitute the positive definite solution into the expression of the control law, obtain the third system control law;Delete the channel information not transmitting information in the third system control law to obtain the first system control law;According to the first system control law, multi-channel information transmission can be carried out, so as to solve the problem of multiple transmission delay and random packet loss coexistence, improve the integrity of transmission information during channel transmission.

The invention discloses a spacecraft magnetic moment attitude control method based on a non-inverse iterative algorithm, and the method comprises the steps: building a linearized periodic model for a spacecraft attitude control system which only depends on magnetic moment; on the basis, according to a linear quadratic form optimal control theory, an optimal controller design problem is converted into a solving problem of a discrete period Riccati equation connected with the optimal controller design problem; on the basis of the gradient descent principle, by constructing an error function, a non-inverse iterative algorithm based on the gradient descent principle is provided to solve a discrete period Riccati equation, matrix inversion operation in a traditional solving method is avoided, and calculation efficiency and numerical stability are effectively improved; and an optimal state feedback control law is obtained by using the obtained Riccati equation solution, so that spacecraft attitude optimal control only using the magnetic moment is realized, and a new solution is provided for the attitude control problem of a limited actuator in a space task.

This invention relates to an integral optimal control method and system for ship adaptive rudder track holding, belonging to the field of ship adaptive rudder track control technology. It is proposed to address the problems of low track tracking accuracy and poor performance in indirect track control, as well as yaw issues encountered by wind, waves, and currents during straight track tracking. Key technical points: Based on the ship's speed u0 and the target heading deviation ψ... r Update system matrix A; select accuracy and energy consumption balance parameter matrices, solve the ILQR Riccati equation to obtain the optimal control variance matrix; calculate the ILQR controller proportional differential coefficient matrix, and calculate the integral coefficient matrix according to the critical damping principle; set the noise variance matrix, solve the GESO Riccati equation to obtain the observation equation matrix; calculate the GESO observation gain, and calculate the observation integral gain matrix according to the critical damping principle; calculate the GESO state observation result x and the ILQG control law; repeat the above steps to control the ship to travel along the set straight track. This invention can effectively solve the yaw problem encountered by wind, waves and current interference when tracking a straight track, making the closed-loop system have good robust stability, while reducing the number of steering operations per unit time and reducing steering energy consumption; after extensive testing, it has advanced performance.

The application discloses an AISMC compensation control method for a flexible joint mechanical arm under singular perturbation decomposition and belongs to the field of flexible joint mechanical arm control, and comprises the following steps: S1, a dynamic model of the flexible joint mechanical arm containing uncertain composite disturbance is established, and is decoupled into a slow subsystem and a fast subsystem; S2, a lumped matching disturbance in the slow subsystem is estimated by using a compensation function observer; S3, for the slow subsystem, an integral sliding mode surface and an adaptive approaching law with a dead zone correction are constructed; for the fast subsystem, a linear quadratic regulator is designed, a performance index is defined, and Riccati equation is solved to obtain an optimal control law; S4, the control law of the slow subsystem and the control law of the fast subsystem are superposed to obtain an overall control input; and S5, simulation verification is performed. The AISMC compensation control method for the flexible joint mechanical arm under singular perturbation decomposition has wide application prospects by taking into account the trajectory tracking accuracy, robustness and stability.

The invention relates to the technical field of robot motion control and heterogeneous calculation acceleration, in particular to an optimal control Riccati equation solving method based on TPU heterogeneous parallelism, which is characterized in that heterogeneous division of labor is carried out on a host side and a TPU equipment side, the host side is only responsible for input issuing and result recovery, and the equipment side is used for managing and controlling an iterative process and operator scheduling by a coprocessor; the multiple neural network processing units execute intensive linear algebraic calculation in parallel; designing a general matrix multiplication parallel acceleration operator and a parallel Gaussian elimination inversion operator, optimizing a storage layout of an on-chip local memory and a working area reuse strategy, completing Riccati equation solution based on Hamiltonian matrix sign function iteration, recovering a stable solution matrix and calculating an optimal feedback gain; for a multi-independent system scene, a system dimension parallel or batch rotation strategy is adopted to improve the batch processing throughput rate. The method solves the problems that in the prior art, intermediate data carrying overhead is large, and parallel support of key links is insufficient.

The invention discloses a risk sensitive control optimization method for energy management of a hybrid flying car, belongs to the technical field of nonlinear system control, is used for energy management of the hybrid flying car, and comprises the following steps: constructing a random nonlinear system model of the hybrid flying car; a Hamiltonian equation of an exponential cost function with risk sensitive parameters is constructed, logarithmic transformation is performed on a corresponding risk neutral problem, sufficient and necessary conditions for establishment of a risk sensitive maximum principle are obtained, a nonlinear system is converted into a linear system with additive noise, and the risk sensitive maximum principle is obtained. And deducing a Riccati equation and an optimal control strategy by adopting a measure change method. According to the method, a Hamiltonian function is constructed, logarithmic transformation is carried out on a corresponding risk neutral problem, a risk sensitive type zero-sum game strategy of a random nonlinear system is popularized to a cooperative game, and on the premise that multi-objective optimization is achieved, overall optimization is achieved by considering the situation that risk participants are mutually coupled.

This invention discloses a fault-tolerant control optimization method for vehicle platooning. The method constructs a performance function for the vehicle platooning system, providing the constructed performance function and the Riccati equation. A fault-tolerant controller is designed, and the feedback gain and topology are optimized by using a policy iteration method and a projection gradient algorithm, respectively, with the initial topology fixed. Finally, this process is repeated to obtain the suboptimal control input and topology, thereby achieving vehicle platooning.