197 results about "Liapunov function" patented technology

The invention provides a steering engine saturation resistant self-adaptive control method for ship courses. The method comprises performing a mathematical description on ship course motion, and constructing a dynamic saturation-resistant compensator, a first state vector z1 of a self-adaptive backstepping controller and a Lyapunov function of the z1 to obtain virtual control; calculating a second state vector z2 of the self-adaptive backstepping controller through subtraction through combining ship course angle information, the course angular speed and the compensation state which is output by a dynamic saturation-resistant compensator module, constructing an overall Lyapunov function in the control method, and obtaining a ship course non-linear self-adaptive controller provided with the saturation-resistant compensator through combining ship course stability conditions to complete the ship course non-linear self-adaptive control method provided with the saturation-resistant compensator. The self-adaptive control method is explicit in thinking, clear and reasonable in structure and prone to engineering implementation.

The invention belongs to the control field and provides a design method of a robustness fault detection filter of a linear uncertain system. A Lyapunov function method on which a homogeneous polynomial parameter depend is introduced into robustness fault detection of a linear time invariant system with convex polyhedron nondeterminacy. Firstly, existence of an HPPDL function used for designing an RFDF can be verified through feasibility of a linear matrix inequality; secondly, maximal fault sensitivity is obtained through solving a generalized eigenvalue problem, and an optimal RFDF is obtained. With increase of polynomial time, quantity of the linear matrix inequality and a free variable are increased, and conservation of verification is reduced substantially. The design method comprises two phases: (1) designing an optimal RFDF for a residual error generator with certain interference attenuation and largest fault sensitivity; (2) carrying out threshold design for a residual error generated by estimation. Compared with a previous analogy method, the design method in the invention has generality.

The invention discloses a guidance and control integrated design method considering all-strapdown seeker view field constraint, and aims at solving the technical problem that an existing guidance and control integrated design method is poor in practicability. According to the technical scheme, the guidance and control integrated design method comprises the steps that a missile longitudinal channel attitude control system model, a longitudinal plane missile-target relative motion model and an all-strapdown seeker longitudinal channel sight decoupling model are built; the state variable and the system output variable are selected, and a guidance and control integrated state space mathematical model considering view field angle constraint is built; a control method combining an obstacle Lyapunov function, an expansion state observer and dynamic surface control is adopted. The control method combining the obstacle Lyapunov function, the expansion state observer and dynamic surface control is adopted, and meanwhile the guidance precision and the all-strapdown seeker view field angle constraint conditions are met, so that it is guaranteed that the body sight angle detected by an all-strapdown seeker in the missile guidance and control process meets the seeker view field constraint.

The invention provides a UUV trajectory tracking control method for preventing the differential explosion based on the differential output characteristics of a biological instructive model. The method comprises the following steps of 1, conducting the initialization; 2, obtaining position and attitude error variables based on an under-actuated UUV mathematical model; 3, calculating a virtual control law, and replacing a virtual expectancy control law with the output value of the biological instructive model; 4, constructing a Lyapunov function, and transferring the ballast of a position error to the ballast of a speed error, avoiding the differential explosion phenomenon through the real-time derivation of replacing a virtual control variable with the output of the biological instructive model, and realizing the ballast of the speed error; and 5, designing a trajectory tracking controller. According to the technical scheme of the invention, the differential explosion phenomenon caused by the repeated derivation of the traditional back-stepping method can be avoided, and the complexity of the controller is simplified. Meanwhile, in combination with the controller of the biological instructive model, the time constraint requirements of the thrust constraints and the under-actuated UUV trajectory tracking of a propeller on position, speed and attitude can be met.

The invention discloses an active formation fault-tolerant control method based on a fast adaptive technology. The active formation fault-tolerant control method comprises the steps that a laplacian matrix and a leader-following connection matrix of distributed multi-agent systems are achieved by constructing a connection diagram of multi-agent systems; according to a four-rotor aircraft model ofan existing nonlinear term, a corresponding observer and a fast adaptive fault estimator are constructed to predict the actual size of faults;alocal augmented system error dynamic equation and a wholeaugmented system error dynamic equation are constructed; Lyapunov function is constructed, the method that parameters in a computational controller and the fault estimator are calculated is derived and achieved through corresponding theories, and the requirements of formation control are finished under the action of actuator failure of the system and external interference. According to the activeformation fault-tolerant control method, adverse influence of the external interference on fault-tolerant control is completely eliminated at the theoretical level, performance of fault estimation isimproved, and the fault-tolerant control when the actuator fault occurs at any node of four-rotor aircraft formation or when the actuator fault occurs at multiple nodes at the same time is achieved.

The embodiment of the invention provides an Internet of Vehicles transmission method and device based on information freshness, applied to the technical field of the Internet of Vehicles. The method comprises the following steps: obtaining an update objective function according to an initial objective function and the fact that information age of the vehicle collection node is a fixed value, whenvehicle collection node does not send a data packet within a preset time period T; constraining the network by minimizing the change rate of a Lyapunov function to obtain a final objective function, calculating an upper limit of the final final objective function at T=1, determining a second-best solution of the minimum final objective function by minimizing the upper limit to obtain an update strategy function and a routing algorithm function, determining the update strategy according to the update strategy function, determining a measurement factor according to the Q-learning algorithm andthe routing algorithm function, performing, by the vehicle collection node, information update decision making according to the update strategy, and selecting a neighbor node with the maximum measurement factor to transmit the data packet. By adoption of the Internet of Vehicles transmission method and device provided by the invention, the computational complexity and the information age can be reduced.

Provided is a network control system dynamic switching control method based on average residence time. The method based on the average residence time is characterized by converting the influence of uncertain and randomly-changing time delay and packet loss on dynamic property of a network control system into a kind of discrete switching event, and establishing a discrete switching control model of the network control system allowing to comprise an unstable subsystem; ensuring that the network-induced time delay is always smaller than one sampling period, and meanwhile, guaranteeing that a new control variable in the current sampling period can be acted on a controlled object by utilizing an improved initiative variable sampling hybrid node driving mechanism; and providing a sufficient condition for solving the existence of a modal dependence switching controller based on a multiple-Lyapunov function method, and providing a design method of the switching controller meeting indefinite subsystem switching sequence allowing the average residence time by adopting an optimal cycle algorithm, and ensuring the stability of the network control system under the condition of limited communication and incomplete information.

A method controls an operation of an elevator system using a control law to stabilize a state of the elevator system using a tension of an elevator rope. A derivative of a Lyapunov function along dynamics of the elevator system controlled by the control law is negative definite. The control law is a function of amplitude of a sway of the elevator rope and a velocity of the sway of the elevator rope. The method determines the amplitude of the sway of the elevator rope and the velocity of the sway of the elevator rope during the operation, and determines a magnitude of the tension of the elevator rope based on the control law, and the amplitude and the velocity of the sway of the elevator rope.

The invention relates to a method for controlling a backstepping neural network for tracking a three-dimensional flight path of an airship. In order to control tracking of the flight path of the airship, a nonlinear kinetic model of the airship is established; the nonlinear kinetic model of the airship serves as a controlled object and is divided into two subsystems, a Lyapunov function and a middle virtual controlled quantity are designed for each subsystem by using a backstepping method, proper virtual feedback is determined, and the previous state of a system is gradually stable until the whole system is gradually stable in an inverse deducing mode; and in order to solve the problem that the kinetic model of the airship is uncertain, an unknown kinetic model of the airship is estimated accurately by a neural network approximator, and the control precision and the system performance are improved. A closed-loop system controlled by the method can track an optional parameterized command flight path precisely and has high stability, adaptability, robustness and dynamic performance, and an effective scheme is provided for an airship flight path control project.

The invention belongs to the field of control over a permanent magnet synchronous motor, and relates to a speed regulating control strategy for a sensorless permanent magnet synchronous motor. The speed regulating control strategy is characterized in that a three-phase current of the permanent magnet synchronous motor is detected, the current under an alpha and beta coordinate system is obtained through Clarke conversion, and the current under the dq coordinate system is obtained through Park conversion; a sliding-mode observer is designed according to a mathematic model of the permanent magnet synchronous motor under the alpha and beta two-phase static coordinate system; a hyperbolic tangent function is used as a switching function; a sliding-mode face is selected; the estimation value of the rotor position is obtained through counter electromotive force; a speed estimator is adopted for estimating the speed; a Lyapunov function is selected, and an adaptive law is obtained through the stability condition; According to the speed regulating control strategy, the structural switching discontinuity is relieved, the buffeting is obviously weakened, the rapidness, the robustness and the dynamic performance are improved, when an error exists in the estimation value of the rotor position, the speed estimation error is made to be within the controllable range, and the rotating speed estimation precision is improved.

The invention discloses a micro gyroscope robust self-adaptive control method, and the method is applied to a controller comprising a micro gyroscope. The method includes the following steps of establishing an ideal dynamics model, establishing a dimensionless dynamics model of the micro gyroscope, designing a sliding mode function and making the derivative of the sliding mode function to time be zero to acquire a control law, adding a feedback item and a robust item to the control law, wherein the control law with feedback item and the robust item is used as a robust self-adaptive control law, controlling the micro gyroscope based on the Lyapunov function method, and designing an self-adaptive law. According to the micro gyroscope robust self-adaptive control method, the feedback item is added to the control law, so that micro gyroscope two axle vibration trajectory tracking and parameter estimation speed is greatly improved, and vibration amplitude is reduced; the robust item is added to the control law, so that external interference and parameter uncertainty are removed, and robustness and dynamic characteristics of a system are improved; the self-adaptive law is designed based on the Lyapunov function method, so that globally asymptotic stability of the whole system is guaranteed, and reliability of the system and robustness to parameter change are improved.

The invention discloses a nonlinear networked control system non-fragile H-infinity fault tolerance control method. Firstly a closed-loop nonlinear networked control system model is established for considering the situation of parameter perturbation, time delay and packet loss of the nonlinear networked control system and random fault of an actuator, and then a Lyapunov function including packet loss information is constructed. The sufficient conditions of nonlinear networked control system stochastic stability and existence of an H-infinity fault tolerance controller are obtained by using the theory of Lyapunov stability and a linear matrix inequality analysis method. Solving is performed by using a Matlab LMI tool box, a non-fragile fault tolerance controller gain matrix K=YP<-1><011> is given, the conditions for optimization of the minimum disturbance suppression ratio gamma are given, and the optimized controller gain matrix K* under the minimum disturbance suppression ratio gamma<min> (the square root of e) is acquired. The situation of the random fault of the actuator is considered, and the probability of the random fault meets BerRoulli distribution so as to have more practical meaning.

The present invention discloses a non-fragile dissipative filtering method of a nonlinear networked control system. The method comprises the steps of firstly establishing a nonlinear networked filtering error system model on the conditions of considering the time delay and the packet loss of the nonlinear networked control system and the perturbation of the filter parameters, then constructing a Lyapunov function, and then utilizing a Lyapunov stability theory and a linear matrix inequality analysis method to obtain the sufficient conditions of the mean square exponential stability of a nonlinear networked filtering error system and the existence of a non-fragile dissipative filter, utilizing a Matlab LMI tool kit to solve, and definding a non-fragile dissipative filter parameter matrix. The method of the present invention considers the random time delay and the pocket loss situations between the sensors and the filters, is suitable for the general dissipative filtering including the H-infinite filtering, and enables the conservatism of the non-fragile dissipative filter design to be reduced. Moreover, a non-modeling state of the system is considered when a full-order filter is designed, thereby being able to reduce the calculation burdens and the design cost.

The present invention relates to a contragradience limited time bilateral remote operation control method and a computer readable storage medium. The method comprises the steps of S1 establishing a bilateral remote operation dynamical model not considering a gravity item for a bilateral remote operation control robot system of n degrees of freedom; executing the steps S2 to S6 from a master terminal and a slave terminal respectively; S2 extracting the joint position variables of a robot, carrying out the variable substitution and establishing a state variable equation; defining an undetermined virtual switching controller in the state variable equation; S3 extracting a to-be-stabilized system based on the state variable equation; S4 selecting a first Lyapunov function to stabilize the to-be-stabilized system; S5 carrying out the derivation on the first Lyapunov function and defining a nonsingular integral terminal sliding mode surface according to a derivation result; S6 selecting a second Lyapunov function to calculate the convergence time of a state variable at a sliding stage of the sliding mode surface; S7 constructing a bilateral controller to enable a non-sliding mode to reach the nonsingular integral terminal sliding mode surface within the limited time; estimating the upper limit of the convergence time of the state variable.

The invention provides a permanent magnet linear synchronous motor second type fuzzy fractional order sliding mode control system and method. According to the control technology, error amount is obtained according to subtracting of the given speed signals and the feedback speed signals of a permanent magnet linear synchronous motor servo system, a fractional order sliding mode surface is designed according to the error amount, a sliding mode control switching item is designed based on the fractional order theory, the product of the gain and the discontinuous function in the switching item is replaced by using an interval second type fuzzy controller, and the system is verified to be stable according to the Lyapunov function. The interval second type fuzzy controller and the fractional order sliding mode surface are introduced in the design, and the switching item based on the fractional order differential and integral theory is adopted so that buffeting can be effectively reduced. Meanwhile, the uncertainty problem existing in the fuzzy rules of the first type fuzzy system can also be solved so that the robustness of the system can be enhanced. Finally the robustness of the system can be enhanced by the method and the buffeting phenomenon of the system can be weakened.

The invention discloses an active power filter global sliding mode control method based on a double-feedback fuzzy neural network. The active power filter global sliding mode control method based on the double-feedback fuzzy neural network comprises the following steps: (1) establishing a mathematical model of an active power filter; (2) establishing an active power filter global sliding mode controller based on the double-feedback fuzzy neural network, designing a control law, and taking the control law as control input of the active power filter; and (3) designing an adaptive law on the basis of a Lyapunov function, and verifying the stability of the active power filter global sliding mode controller based on the double-feedback fuzzy neural network. Compensating current tracking performance of the active power filter system under the circumstances of existing of parameter perturbation and external disturbance and system robustness can be improved.

The invention discloses a self-adaptive fractional order sliding-mode control method. The self-adaptive fractional order sliding-mode control method comprises the following steps: building a mathematical model and a reference model of a system ; building a fractional order sliding-mode surface according to the mathematical model and the reference model of the system; designing a fractional order self-adaptive law according to the fractional order sliding-mode surface; designing a controlling force according to the fractional order sliding-mode surface and the fractional order self-adaptive law; verifying the stability of the designed self-adaptive fractional order sliding-mode control method on the basis of a Lyapunov function. The self-adaptive fractional order sliding-mode control method improves the control effect and the parameter estimation effect.

The invention discloses a bridge crane error tracker with an initial load swing angle and trolley displacement and a method. According to the method, an underactuation bridge crane system initial dynamical model is established; an expected trolley error trace and an expected swing angle error trace are given; error tracking signals for trolley positioning and load swinging are determined; an underactuation bridge crane system error tracking dynamical model is obtained; a target system model enabling a Lyapunov function to be stable is established, and the bridge crane error tracker with the initial load swing angle and trolley displacement is obtained according to the target system model and the underactuation bridge crane system error tracking dynamical model. The bridge crane error tracker has the advantages that under the condition that the initial load swing angle and initial trolley displacement which are zero in a conventional control method are expanded, the initial swing angle of a load and the initial displacement of a trolley are allowed to be of any values.

The invention discloses a non-linear amplitude phase detection method suitable for a single-phase distortion power grid, and the method comprises the steps: extracting a fundamental wave signal of a single-phase signal through employing a stationary coordinate system phase locking ring method according to a mode of the single-phase distortion power grid, and building an orthogonal signal; building a liapunov function according to the fundamental wave signal of the single-phase signal and the orthogonal signal, and obtaining an adaptive orthogonal generator and a frequency locking ring because the differential coefficient of the liapunov function is less than zero, i.e., system global stability and convergence; and the fundamental wave amplitude and phase of the single-phase signal are obtained according to the adaptive orthogonal generator and the frequency locking ring. The method is designed according to the mode of the single-phase distortion power grid, achieves the estimation of a diagonal frequency signal through employing a liapunov method, does not depend on a conventional linearization method, and guarantees the signal integrity through employing a non-linear method.

The invention discloses an RBF dual neural network adaptive sliding mode control method for an active power filter. The method is characterized by comprising the following steps: step (1), establishing a mathematical model of the active power filter; (2) designing an adaptive RBF dual neural network based on a fractional order sliding mode surface, and separately approximating the nonlinear function and the upper bound of interference of the system by using the two RBF neural networks; and step (3) controlling the active power filter according to a fractional order RBF dual neural network sliding mode controller. According to the method disclosed by the invention, the characteristics that the fractional order can get rid of the dependence of system functions and improve the control response of the system are adopted; on this basis, the nonlinear function and the upper bound of interference values of the system can be approximated by adopting the characteristic that the RBF neural networks do not relay on the model of the system; and moreover, the stability of a system controller can be proved by designing the Lyapunov function, the real-time tracking compensation can be performed for the instruction current, and high reliability, high robustness to parameter variation and high stability can be achieved.

The invention discloses a current reference value automatic adjustment switchover control method of a power electronic converter. The current reference value automatic adjustment switchover control method of the power electronic converter comprises the steps that 1 a switchover system model of the power electronic converter is built according to the work state of the converter; 2 a Lyapunov function of a switchover subsystem i is defined, a related matrix is calculated, and a Lyapunov function value of the subsystem i is obtained; 3 a switchover control rule is selected, and the subsystem with the maximum Lyapunov function is selected as the current subsystem; a current reference value is adjusted according to an output error, when a parameter is uncertain or input voltage and a load change, the current reference value is adjusted according to the rule, and the control method is achieved. The current reference value automatic adjustment switchover control method of the power electronic converter is simple in control process, is good in effect, guarantees overall control stability of the converter, has robustness on changes of the input voltage, the load and the like, and improves the response speed of output voltage.

Provided is a terminal guidance method for maneuvering aircraft multi-terminal constraint backstepping sliding mode. The method comprises three main steps: step 1, analyzing terminal constraint of a terminal guidance problem and number; step 2, determining a sliding mode variable structure control order, designing a sliding variable quantity; step 3, and designing limited time backstepping, to obtain the guidance law of the whole system. The design basis of the method is the backstepping design of reaching in limited time, and the design of the terminal guidance law is a problem of reaching in a limited time. The backstepping design in variable structure control is a regression design method combining selection of a Lyapunov function and the design of a controller. Beginning from a minimum order differential equation of the system, the method designs in a stabilization manner layer by layer, and finally global stabilization is realized, so as to provide the control law of the whole system.

The invention discloses a design method of aeronautical engine integral tangent fuzzy self - adaptive sliding mode controller, which comprises the following steps: obtaining a model near a steady point to output data according to a nonlinear component level model of an aeroengine system, establishing a linear model of the aeroengine by using a least squares method; defining a tracking error of the aeroengine system, a reference signal for a given system, and assuming that a derivative of a reference signal is 0; designing a hyperbolic tangent plane by using a hyperbolic tangent function similar to a function of a saturation function; saturating an error for a case where the error is large, and enlarging a system error for a case where the error is small; improving a dynamic quality of a system approach motion by using an exponential approaching law; utilizing an adaptive control method to realize an adaptive estimation of an uncertainty upper bound, and the uncertainty upper bound is obtained; designing a sliding mode control law by means of the Lyapunov function verifying a stability of the system.