51results about How to "Guaranteed asymptotic stability" patented technology

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.

The invention provides a tracking control method of plane paths of a self-managing airship. The method comprises the following steps of: (1) giving an expected track value; giving an expected plane path; giving an expected pitch angle Theta c and an expected rolling angle Phi c; and giving an expected speed; (2) calculating navigation: calculating and removing an expected yaw angle Psi c needed by an error between an expected position and an actual position; (3) controlling and calculating a posture kinesiology: calculating and removing an expected angle speed Omega c needed by the error between an expected posture and an actual posture; (4) horizontally and longitudinally disintegrating a kinesiology: horizontally and longitudinally disintegrating a kinetic equation and an expected speedvalue; (5) longitudinally controlling and calculating the kinesiology: calculating and removing a control quantity mu 1on needed by the error between an expected longitudinal speed and an actual longitudinal speed; and (6) horizontally controlling and calculating the kinesiology: calculating and removing the control quantity mu 1at needed by the error between an expected horizontal speed and an actual horizontal speed. By the method of the invention, any parameter plane paths can be tracked for ensuring the stable property of a closed-ring system and simplifying the control calculation.

The invention discloses an attitude control method of a flexible spacecraft. The attitude control method comprises the following steps: establishing a kinematics model and a dynamics model of the flexible spacecraft with multi-source interference; adopting two groups of T-S fuzzy models to perform modeling on second interference described by the flexible spacecraft system and the exogenous nonlinear system; constructing a flexible vibration observer for estimating a flexible mode, and constructing a fuzzy disturbance observer with an asynchronous prerequisite variable for obtaining an estimated value of external disturbance modeled by the T-S fuzzy model, and respectively obtaining a flexible mode error system and a disturbance error system; and based on the output value of the observer, designing an event-triggered anti-interference controller for controlling the attitude of the flexible spacecraft. According to the method, the influence of flexible vibration and multi-source interference on the flexible spacecraft can be effectively reduced, vibration suppression and attitude stabilization are realized, the anti-interference capability of the spacecraft is improved, communication resources can be saved, and the method is suitable for attitude control of the flexible spacecraft.

The invention discloses an LMI linear inequality-based micro gyroscope H-infinity control method. The method includes the following steps that: S101, the ideal dynamic model of a micro gyroscope is established; S104, a dimensionless vector model of the micro gyroscope is established; S103, a robust adaptive neural network H-infinity controller is designed based on an linear inequality according to the ideal dynamic model and the dimensionless vector model; and S104, a neural network weight adaptive law is designed based on based on the lyapnov stability theorem, so that the established controller can be updated online. The LMI linear inequality-based micro gyroscope H-infinity control method of the invention has the advantages of high robustness and high stability.

The invention relates to an optimal synchronous control method for a coupled fractional-order chaotic electromechanical device, which belongs to the field of automation. A synchronization model of fractional-order electromechanical devices with capacitive-resistance coupling is established, and the phase diagram shows that its dynamic behavior is closely related to physical parameters, coupling coefficients and fractional orders. In order to transfer the passive system from the original track to the track of the active system, an optimal synchronization control method consisting of an adaptive feedforward controller and an optimal feedback controller is proposed. Under the frame of combining fractional backstepping method and hierarchical type 2 fuzzy neural network, a feedforward controller for unknown function estimation of dynamic system is proposed. At the same time, an adaptive dynamic programming method is proposed to solve the zero-sum differential game problem in the optimal feedback controller. The invention not only ensures the asymptotic stability of the closed-loop system, realizes optimal synchronization, but also minimizes the cost function.

The invention discloses a man-machine co-driving type electric power steering system based on a hybrid theory and a control method, and belongs to the field of unmanned steering of an intelligent car. The man-machine co-driving type electric power steering system comprises a front torque / angle sensor, a rear torque / angle sensor, a man-machine co-driving type electric power steering hybrid controller, a switching monitoring controller, a steering motor, a steering shaft, a speed reduction mechanism and a gear and rack mechanism. The invention further provides the control method for the man-machine co-driving type electric power steering system based on the hybrid theory, a man-machine co-driving type electric power steering system steering adjustment control system in the optimal operation state is built based on a hybrid switching system, a complex problem in the whole operation project is decomposed into a synthesis of control problems under single work conditions, and therefore complex modeling and control of the man-machine co-driving type electric power steering system are realized. The control system is high in stability, the control method is easy to realize, and different steering conditions of the car can be met.

The invention provides a saturation problem moving body attitude event-triggered control method with an actuator. The steps are listed as follows: 1, expected tracking values are given: expected attitude angles phi<d>, theta<d> and psi<d>, and expected attitude angle speed p<d>, q<d>, r<d>; 2, attitude angle tracking error is calculated: attitude angle error phi<e>, theta<e> and psi<e>, and attitude angle speed error q<e>, p<e> and r<e>; 3, an event-triggered controller is designed: feedback gain K<c> is calculated; 4, event-triggered controller output quantity y<c> for eliminating the attitude angle is calculated; and event conditions are designed; 5, control quantity limit is given: saturation control quantity sat(mu) for eliminating the expected attitude angle and attitude angle speed error is calculated; 6, an LQ anti-saturation control compensator is designed: the feedback terms v<aw> and y<aw> of correction control quantity and state quantity are calculated; and 7, input and output mu<c,aw> and y<c,aw> of an event-triggered controller after correction of the LQ anti-saturation control compensator are calculated and applied to a moving body control model. According to the method, problems of actuating mechanism saturation and system data load can be solved, any expected attitude can be tracked and closed loop system asymptotical stability can be guaranteed.

A fault-tolerant tracking control method for nonlinear active suspension based on proportional integral observer. First, in order to describe the model uncertainty of the suspension system, a 1 / 2 vehicle suspension model based on the Takagi-Sugeno (T-S) fuzzy model is established; Second, based on this model, a robust H ∞ An output feedback controller is used to enhance the performance of the suspension in the normal actuator mode, and its output response is regarded as an ideal reference trajectory; finally, a proportional-integral observer is designed to accurately estimate the actuator failure online, and an active fault tolerance is further designed The controller is tracked to compensate the performance loss caused by actuator failure; the invention is used for nonlinear active suspension control of actuator failure, and solves the problem of being unable to cope with external uncertain interference and actuator failure.