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1.
In this paper, a learning-based active fault-tolerant control (FTC) scheme for robot manipulators with uncertainties and actuator faults is proposed. Unlike traditional FTC methods, with dynamic learning theory, both uncertainties and actuator faults can be accurately identified/learned by radial basis function networks. Based on the learned knowledge, dynamical classifiers and experience-based controllers corresponding to different fault modes are constructed. With the help of dynamical classifiers, fault detection and isolation can be obtained rapidly and accurately, and the correct experience-based controller (instead of the controller reconfigured online) corresponding to the current fault system is selected to compensate for faults, and superior control performance is achieved, even in the presence of faults. The simulation studies demonstrate the feasibility of the proposed FTC method.  相似文献   

2.
This paper focuses on the problem of direct adaptive neural network (NN) tracking control for a class of uncertain nonlinear multi-input/multi-output (MIMO) systems by employing backstepping technique. Compared with the existing results, the outstanding features of the two proposed control schemes are presented as follows. Firstly, a semi-globally stable adaptive neural control scheme is developed to guarantee that the ultimate tracking errors satisfy the accuracy given a priori, which cannot be carried out by using all existing adaptive NN control schemes. Secondly, we propose a novel adaptive neural control approach such that the closed-loop system is globally stable, and in the meantime the ultimate tracking errors also achieve the tracking accuracy known a priori, which is different from all existing adaptive NN backstepping control methods where the closed-loop systems can just be ensured to be semi-globally stable and the ultimate tracking accuracy cannot be determined a priori by the designers before the controllers are implemented. Thirdly, the main technical novelty is to construct three new nth-order continuously differentiable switching functions such that multiswitching-based adaptive neural backstepping controllers are designed successfully. Fourthly, in contrast to the classic adaptive NN control schemes, this paper adopts Barbalat׳s lemma to analyze the convergence of tracking errors rather than Lyapunov stability theory. Consequently, the accuracy of ultimate tracking errors can be determined and adjusted accurately a priori according to the real-world requirements, and all signals in the closed-loop systems are also ensured to be uniformly ultimately bounded. Finally, a simulation example is provided to illustrate the effectiveness and merits of the two proposed adaptive NN control schemes.  相似文献   

3.
Unmanned surface vehicles (USVs) are a promising marine robotic platform for numerous potential applications in ocean space due to their small size, low cost, and high autonomy. Modelling and control of USVs is a challenging task due to their intrinsic nonlinearities, strong couplings, high uncertainty, under-actuation, and multiple constraints. Well designed motion controllers may not be effective when exposed in the complex and dynamic sea environment. The paper presents a fully data-driven learning-based motion control method for an USV based on model-based deep reinforcement learning. Specifically, we first train a data-driven prediction model based on a deep network for the USV by using recorded input and output data. Based on the learned prediction model, model predictive motion controllers are presented for achieving trajectory tracking and path following tasks. It is shown that after learning with random data collected from the USV, the proposed data-driven motion controller is able to follow trajectories or parameterized paths accurately with excellent sample efficiency. Simulation results are given to illustrate the proposed deep reinforcement learning scheme for fully data-driven motion control without any a priori model information of the USV.  相似文献   

4.
In this paper, an adaptive Takagi–Sugeno (T–S) fuzzy controller based on reinforcement learning for controlling the nonlinear dynamical systems is proposed. The parameters of the T–S fuzzy system are learned using the reinforcement learning based on the actor-critic method. This on-line learning algorithm improves the controller performance over the time, which it learns from its own faults through the reinforcement signal from the external environment and tries to reinforce the T–S fuzzy system parameters to converge. The updating parameters are developed using the Lyapunov stability criterion. The proposed controller is faster in learning than the T–S fuzzy that parameters learned using the gradient descent method under the same conditions. Moreover, it is able to handle the load changes and the system uncertainties. The test is carried out based on two mathematical models. In addition, the proposed controller is applied practically for controlling a direct current (DC) shunt machine. The results indicate that the response of the proposed controller has a good performance compared with other controllers.  相似文献   

5.
In this work, finite time position and heading control based on backstepping based fast terminal sliding mode control is proposed for coaxial octorotor subjected to external wind disturbances. First, mathematical model of the coaxial octorotor is developed and then a new learning-based technique, an extended inverse multi-quadratic radial basis function network (EIMRBFN) is proposed to estimate the unmodeled dynamics of the octorotor. The external disturbance observer is also designed to encompass the realistic disturbance effect in the dynamical model and to allow the controller handle external disturbances, effectively. Backstepping controller based on fast terminal sliding model control is then proposed and also applied on the resultant dynamical model that provides finite time convergence of system's states. The stability of the proposed controller and complete system is analyzed using Lyapunov stability theory. Finite time convergence analysis of the desired trajectory is also provided. Simulations are carried out to validate the effectiveness of the proposed control scheme. Comparison with traditional PID and LQR controllers also verifies that the proposed controller achieves improved performance.  相似文献   

6.
This paper presents an effective approach to stabilize nonlinear multiple time-delay (NMTD) interconnected systems via a composite of fuzzy controllers and dithers. First, a neural-network (NN) model is employed to approximate each subsystem. Then, the dynamics of the NN model is converted into a linear differential inclusion (LDI) state-space representation. Next, in terms of Lyapunov?s direct method, a delay-dependent stability criterion is derived to guarantee the exponential stability of the NMTD interconnected system. Subsequently, the stability conditions of this criterion are reformulated into a linear matrix inequality (LMI). Based on the LMI, a robustness design of fuzzy control is synthesized not only to stabilize the NMTD interconnected system but also to achieve the optimal H∞ performance by minimizing the disturbance attenuation level. A set of high-frequency signals (commonly referred to as dithers) is simultaneously injected to stabilize the NMTD interconnected system when the designed fuzzy controllers cannot stabilize it. If the dithers’ frequencies are high enough, the outputs of the dithered interconnected system and those of its corresponding mathematical model, the relaxed interconnected system, can be made as close as desired. This makes it possible to get a rigorous prediction of the stability of the dithered interconnected system by establishing the stability of the relaxed interconnected system. Finally, a numerical example with simulations is given to illustrate the feasibility of our approach.  相似文献   

7.
The synchronous control of a class of disturbed chaotic Lurie systems is probed in. The conception of Lr-synchronization of drive-respond systems is presented. Via Lyapunov function analysis and comparison principle, Lr synchronous controller of the drive-respond systems under perturbation is given and its robustness is also discussed. Barbalat lemma is further used to derive the adaptively synchronous controller for the unknown disturbance situation and the globally asymptotical synchronization is realized. All designed controllers are verified by the simulations and the given controllers are linear, which are convenient and can produce rapid convergence speed of the error systems.  相似文献   

8.
This paper investigates the finite-time control problems for a class of discrete-time nonlinear singular systems via state undecomposed method. Firstly, the finite-time stabilization problem is discussed for the system under state feedback, and a finite-time stabilization controller is obtained. Then, based on which, the finite-time H∞ boundedness problem is studied for the system with exogenous disturbances. Finally, an example of population distribution model is presented to illustrate the validity of the proposed controller. Because there is no any constraint for singular matrix E in the paper, controllers can be designed for more discrete-time nonlinear singular systems.  相似文献   

9.
This work is dedicated to solving the adaptive fuzzy decentralized tracking control issue of large-scale nonlinear systems with full-state constraints. Different with barrier Lyapunov function, the main difference is that a novel nonlinear state-dependent function (NSDF) is introduced to prevent the state constraints being overstepped. Based on NSDF, the necessary feasibility conditions for virtual controllers are completely removed. Then, the prior knowledge of the unknown virtual control coefficients is no longer required since the original system is transformed via the new affine variable. Under the control strategy, three objectives on system performance are achieved: (a) all signals of the closed-loop system are bounded; (b) the subsystem output closely tracks the reference trajectory and original error is ultimately uniformly bounded; (c) the full-state constraints are not violated for all the time. At the end, two simulation examples are shown to verify the effectiveness of the control method.  相似文献   

10.
In this paper two robust controllers for a multivariable vertical short take-off and landing (VSTOL) aircraft system are designed and compared. The aim of these controllers is to achieve robust stability margins and good performance in step response of the system. LQG/LTR method is a systematic design approach based on shaping and recovering open-loop singular values while mixed-sensitivity H∞ method is established by defining appropriate weighting functions to achieve good performance and robustness. Comparison of the two controllers show that LQG method requires rate feedback to increase damping of closed-loop system, while H∞ controller by only proper choose the weighting functions, meets the same performance for step response. Output robustness of both controllers is good but H∞ controller has poor input stability margin. The net controller order of H∞ is higher than the LQG/LTR method and the control effort of them is in the acceptable range.  相似文献   

11.
In this paper, the simultaneous H∞ stabilization problem is investigated for a physically interconnected large-scale system which works in multiple operation modes. A distributed wireless networked control framework is introduced, in which the distributed dynamic output feedback controllers not only use the local measurements, but also receive the neighboring controllers’ broadcasts via wireless networks. The channel fading in wireless communications is described as the Rice fading model. Our focus is on the design of the distributed controllers such that the large-scale system is mean-square stable in each operation mode and achieves a prescribed H∞ disturbance attenuation level. By employing the Lyapunov functional method and related stochastic analysis techniques, a sufficient condition on the existence of desired controllers is presented, and the parameterization of the controller gains is derived. Finally, a numerical example is utilized to illustrate the feasibility of the proposed scheme.  相似文献   

12.
This paper deals with the problem of delay-dependent dissipative control for a class of linear time-delay systems. We develop the design methods of dissipative static state feedback and dynamic output feedback controllers such that the closed-loop system is quadratically stable and strictly (Q,S,R)-dissipative. Sufficient conditions for the existence of the quadratic dissipative controllers are obtained by using linear matrix inequality (LMI) approach. Furthermore, a procedure of constructing such controllers from the solutions of LMIs is given. It is shown that the solvability of a dissipative controller design problem is implied by the feasibility of LMIs. The main results of this paper unify the existing results on H∞ control and passive control.  相似文献   

13.
This paper proposes an adaptive data-driven fault-tolerant control scheme using the Koopman operator for unknown dynamics subjected to nonlinearities, time-varying loss of effectiveness, and additive actuator faults. The main objective of this method is to design a virtual actuator to hide actuator faults from the view of the system’s nominal controller without having any prior knowledge about the system’s underlying dynamics. The designed virtual actuator is placed between the faulty plant and the nominal controller of the system to keep the dynamical system’s performance consistent before and after the occurrence of actuator faults. Based on the Koopman operator theory, an equivalent Koopman predictor is first obtained using the process data only, without knowing the governing equations of the underlying dynamics. Koopman operator is an infinite-dimensional, linear operator which takes the nonlinear process data into an infinite-dimensional feature space where the dynamic data correlations have linear behavior. Next, based on the approximated system’s Koopman operator, a virtual actuator is designed and implemented without knowing the system’s nominal controller. Needless to use a separate fault detection, isolation, and identification module to perform fault-tolerant control, the current method leverages the adaptive framework to keep the system’s desired performance in facing time-varying additive and loss of effectiveness actuator faults. Finally, the approach’s efficacy is demonstrated using simulation on a two-link manipulator benchmark, and a comparison study is presented.  相似文献   

14.
To control MIMO systems with unmatched uncertainties, two sliding-mode controllers are presented in this paper. Firstly, a terminal sliding-mode controller is presented to force the output of an MIMO system to a region near zero in finite-time. With the analysis on the effect of the unmatched uncertainties, a full-order terminal sliding-mode control is further proposed to force the output of the MIMO system to converge to zero rather than a region. The virtual control is utilized to establish the reference for the part of the system states, which can reject unmatched uncertainties completely. To generate continuous virtual control signals, the proposed full-order terminal sliding-mode controller makes the ideal sliding motion as the full-order dynamics rather than the reduced-order dynamics in traditional sliding-mode control systems. Finally, the simulations on the control of an L-1011 fixed wing aircraft at cruise flight conditions validate the effectiveness of the proposed method.  相似文献   

15.
This study presents application of a fuzzy controller to a nonlinear two-mass system control. The proposed controller structure is strengthened with a gray estimator. Firstly, a complete state-space mathematical model for a nonlinear two-mass system is developed and numerically simulated. Then, a fuzzy controller is designed to regulate the speed of the system. In order to perform a dynamic and powerful control action, future error values are estimated by gray modeling technique. The gray estimators of the torsional torque and the load machine speed are tested with open-loop and closed-loop control structures to test the robustness of the proposed method for step changes in input parameters. It is observed that the tracking ability of the gray estimators is not influenced for different operation modes. The performances of the control structures, which are supported with gray estimators, are given and no additional feedbacks are required for robust control action. The simulation results are confirmed by experimental results and conclusions are given.  相似文献   

16.
This paper addresses the optimal controller problem for a linear system over linear observations with respect to different Bolza–Meyer criteria, where (1) the integral control and state energy terms are quadratic and the non-integral term is of the first degree or (2) the control energy term is quadratic and the state energy terms are of the first degree. The optimal solutions are obtained as sliding mode controllers, each consisting of a sliding mode filter and a sliding mode regulator, whereas the conventional feedback LQG controller fails to provide a causal solution. Performance of the obtained optimal controllers is verified in the illustrative example against the conventional LQG controller that is optimal for the quadratic Bolza–Meyer criterion. The simulation results confirm an advantage in favor of the designed sliding mode controllers.  相似文献   

17.
This paper is concerned with the problem of robust synchronization of a class of complex dynamical networks with time-varying delays and reaction–diffusion terms. To reflect most of the dynamical behaviors of the system, the parameter uncertainties are considered. A sampled-data controller with m stochastically varying sampling periods whose occurrence probabilities are given constants is considered. The control objective is that the trajectories of the system by designing suitable control schemes track the trajectories of the system with sample-data control. It is shown that, through Lyapunov stability theory, the proposed sample-data controllers are successful in ensuring the achievement of robust synchronization of complex dynamical networks even in the case of uncertainity and Markovian jumping parameters. By utilizing the Lyapunov functional method, Jensen’s inequality, Wirtinger’s inequality and lower bounds theorem, we establish a sufficient criterion such that, for all admissible parameter uncertainties, the complex dynamical network is robustly synchronized. The derived criteria are expressed in terms of linear matrix inequalities that can be easily checked by using the standard numerical software. Illustrative examples are presented to demonstrate the effectiveness and usefulness of the proposed results.  相似文献   

18.
This paper is concerned with reliable H∞?control for saturated linear Markov jump systems with uncertain transition rates and asynchronous jumped actuator failure. The actuator failures are assumed to occur randomly under the Markov process with a different jumping mode from the system jumping mode. In considering the mixed-mode-dependent state feedback controller, both H∞ stochastic stability analysis for closed-loop system with completely accessible transition rates and uncertain transition rates are investigated. Moreover, based on the obtained stability conditions, the H∞?control problems are investigated, and the controller gains can be obtained by solving a convex optimization problem with minimizing H∞ performance as objective and linear matrix inequalities (LMIs) as constraints. The problem of designing state feedback controllers such that the estimate of the domain of attraction is enlarged is also formulated and solved as an optimization problem with LMI constraints. Simulation results are presented to illustrate the effectiveness of the proposed results.  相似文献   

19.
In this paper, we consider the H2-optimal control problem subject to the constraint that the resulting controller be strictly positive real. A direct numerical optimization approach is adopted in conjunction with a controller parametrization that is linear in the unknown parameters. The SPR constraint is easily expressed at each frequency in the form of a linear inequality. The method is applied to a numerical example from the literature and good results are achieved. In particular, the proposed method is particularly adept at determining low order controllers.  相似文献   

20.
In this work, dynamic controllers are designed for reactor power, pressurizer water level, and pressure control in the primary circuit of a pressurized water reactor. These nonlinear controllers use super-twisting sliding-mode estimators to enhance their robustness versus parameter variations and external disturbances. Hence, the perturbative terms can be canceled by the control, thus improving the dynamic behavior of the controlled system. The designed controllers ensure good performances and better transient behavior, also in the presence of uncertainties and disturbances. A performance study of the proposed controllers is carried out in the presence also of unmodeled dynamics.  相似文献   

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