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1.
In this paper, a novel composite controller is proposed to achieve the prescribed performance of completely tracking errors for a class of uncertain nonlinear systems. The proposed controller contains a feedforward controller and a feedback controller. The feedforward controller is constructed by incorporating the prescribed performance function (PPF) and a state predictor into the neural dynamic surface approach to guarantee the transient and steady-state responses of completely tracking errors within prescribed boundaries. Different from the traditional adaptive laws which are commonly updated by the system tracking error, the state predictor uses the prediction error to update the neural network (NN) weights such that a smooth and fast approximation for the unknown nonlinearity can be obtained without incurring high-frequency oscillations. Since the uncertainties existing in the system may influence the prescribed performance of tracking error and the estimation accuracy of NN, an optimal robust guaranteed cost control (ORGCC) is designed as the feedback controller to make the closed-loop system robustly stable and further guarantee that the system cost function is not more than a specified upper bound. The stabilities of the whole closed-loop control system is certified by the Lyapunov theory. Simulation and experimental results based on a servomechanism are conducted to demonstrate the effectiveness of the proposed method.  相似文献   

2.
In this paper, an adaptive quantized control method with guaranteed transient performance is presented for a class of uncertain nonlinear systems. By introducing the Nussbaum function technique, the difficulty caused by quantization is handled and a novel adaptive control scheme is designed. In comparing with the existing adaptive control scheme, the key advantages of the proposed control scheme are that the controller needs no information about the parameters of the quantizer and the stability of the closed-loop system and the transient performance are independent of the coarseness of the quantizer. Based on Lyapunov stability theory and Barbalat’s Lemma, it is proven that all the signals in the resulting closed-loop system are bounded and the tracking error converges to zero asymptotically with the prescribed performance bound at all times. Simulation results are presented to verify the effectiveness of the proposed control method.  相似文献   

3.
In this study, the problem of observer-based control for a class of nonlinear systems using Takagi-Sugeno (T-S) fuzzy models is investigated. The observer-based model predictive event-triggered fuzzy reset controller is constructed by a T-S fuzzy state observer, an event-triggered fuzzy reset controller, and a model predictive mechanism. First, the proposed controller utilizes the T-S fuzzy model and is constructed based on state observations and discrete sampling output, which can greatly reduce the occupation of communication resources. Then, the model predictive strategy for reset law design is designed in this paper. With a reasonable reset of the controller state at certain instants, the performance of the reset control systems is improved. Finally, the validity of the proposed method is illustrated by simulation. The merits of the proposed controller in improving transient performance and reducing the communication occupation are demonstrated by comparing its results with the output feedback fuzzy controller and the first-order fuzzy reset controller.  相似文献   

4.
This paper proposes an adaptive approximation design for the decentralized fault-tolerant control for a class of nonlinear large-scale systems with unknown multiple time-delayed interaction faults. The magnitude and occurrence time of the multiple faults are unknown. The function approximation technique using neural networks is employed to adaptively compensate for the unknown time-delayed nonlinear effects and changes in model dynamics due to the faults. A decentralized memoryless adaptive fault-tolerant (AFT) control system is designed with prescribed performance bounds. Therefore, the proposed controller guarantees the transient performance of tracking errors at the moments when unexpected changes of system dynamics occur. The weights for neural networks and the bounds of residual approximation errors are estimated by using adaptive laws derived from the Lyapunov stability theorem. It is also proved that all tracking errors are preserved within the prescribed performance bounds. A simulation example is provided to illustrate the effectiveness of the proposed AFT control scheme.  相似文献   

5.
In this paper, the appointed-time prescribed performance and finite-time tracking control problem is investigated for quadrotor unmanned aerial vehicle (QUAV) in the presence of time-varying load, unknown external disturbances and unknown system parameters. For the position loop, a novel appointed-time prescribed performance control (ATPPC) strategy is proposed based on adaptive dynamic surface control (DSC) frameworks and a new prescribed performance function to achieve the appointed-time convergence and prescribed transient and steady-state performance. For the attitude loop, a new finite-time control strategy is proposed based on a new designed sliding mode control technique to track the desired attitude in finite time. Some assumptions of knowing system parameters are canceled. Finally, the stability of the closed-loop system is proved via Lyapunov Theory. Simulations are performed to show the effectiveness and superiority of the proposed control scheme.  相似文献   

6.
In this paper, a novel event-triggered adaptive fault-tolerant control scheme is proposed for a class of nonlinear systems with unknown actuator faults. Multiplicative faults and additive faults are taken into account simultaneously, both of which may vary with time. Different from existing results, our controller fuses static reliability information and dynamic online information, which is helpful to enhance the fault-tolerant capability. With the aid of an event-triggering mechanism, an actuator switching strategy and a bound estimation approach, the communication burden is significantly reduced and the impacts of the actuator faults as well as the network-induced error are effectively compensated for. Moreover, by employing the prescribed performance control technique, the system tracking error can converge to a predefined arbitrarily small residual set with prescribed convergence rate and maximum overshoot, which implies that the proposed scheme is able to ensure rapid and accurate tracking. Simulation results are presented to illustrate the effectiveness of the proposed scheme.  相似文献   

7.
This article studies adaptive prescribed performance tracking control problem for a class of strict-feedback nonlinear systems with parametric uncertainties and actuator failures. Firstly, in order to compensate the multiple uncertainties and eliminate the influence of actuator failure, a new adaptive tracking controller based on first-order filter technology will be proposed, which simplifies the algorithm design process. Then, by introducing an asymmetric state transition function, the transient and steady performances of the output tracking error are both constrained such that the predetermined performance control goal is achieved. Moreover, to reduce the communication burden from the controller to the actuator, the event-triggered mechanism is designed, and there will be no Zeno phenomenon. Based on Lyapunov stability theory, it is strictly proved that output signal can track the reference signal and all the signals of the closed-loop system are bounded. Finally, a simulation example is performed and the results demonstrate effectiveness of the proposed strategy.  相似文献   

8.
In this study, an adaptive fractional order sliding mode controller with a neural estimator is proposed for a class of systems with nonlinear disturbances. Compared with traditional sliding mode controller, the new proposed fractional order sliding mode controller contains a fractional order term in the sliding surface. The fractional order sliding surface is used in adaptive laws which are derived in the framework of Lyapunov stability theory. The bound of the disturbances is estimated by a radial basis function neural network to relax the requirement of disturbance bound. To investigate the effectiveness of the proposed adaptive neural fractional order sliding mode controller, the methodology is applied to a Z-axis Micro-Electro-Mechanical System (MEMS) gyroscope to control the vibrating dynamics of the proof mass. Simulation results demonstrate that the proposed control system can improve tracking performance as well as parameter identification performance.  相似文献   

9.
Modeling uncertainties including parameter uncertainty and unmodeled dynamics hinder the development of high-performance tracking controller for hydraulic servo system. The observation for the unknown state is another issue worthy of attention. In this paper, a new seamless observer-controller scheme for hydraulic servo system is proposed with partial feedback. The position signal and the pressure signal are firstly used to build an extended structure estimation system for the unknown state. The advantage of this estimation system is that the state observer provides an extended structure for the parameter adaptation compared to other state observers. Thus the parameter uncertainty can be handled. An adaptive robust controller is synthesized in this paper which includes the adaptive part and the robust part. The adaptive part is used to eliminate the parameter uncertainty. Then the residuals coming from the parameter adaption and the errors coming from the state observation are taken into consideration in the robust part. Moreover, the unmodeled dynamics is also handled by the robust part. Theoretical analysis proves that a prescribed transient performance and the final tracking accuracy can be guaranteed by the proposed observer-controller scheme in the presence of both parameter uncertainty and unmodeled dynamics. Furthermore, the convergence of the closed-loop controller-observer system is achieved with the parametric uncertainty existed only. Extensive comparative experiments performed on a hydraulic actuator demonstrate the effectiveness of the proposed observer-controller scheme.  相似文献   

10.
This paper investigates the problem of asymptotic tracking control of nonlinear robotic systems with prescribed performance. The control strategy is developed based on a modified prescribed performance function (PPF) to guarantee the transient behavior, while the requirements on the accurate initial tracking error in the classical PPF can be remedied. The fuzzy logic system (FLS) is used to approximate the unknown dynamics. In the existing PPF based adaptive control schemes with FLSs, the tracking error does not achieve asymptotic convergence. To address this issue, a robust integral of the sign of the error (RISE) term is incorporated into the control design to reject the FLS approximation errors and external disturbances, such that the asymptotic convergence is achieved. Finally, numerical simulation and experimental results validate the effectiveness of the proposed control scheme.  相似文献   

11.
In this paper, the development and experimental validation of a novel double two-loop nonlinear controller based on adaptive neural networks for a quadrotor are presented. The proposed controller has a two-loop structure: an outer loop for position control and an inner loop for attitude control. Similarly, both position and orientation controllers also have a two-loop design with an adaptive neural network in each inner loop. The output weight matrices of the neural networks are updated online through adaptation laws obtained from a rigorous error convergence analysis. Thus, a training stage is unnecessary prior to the neural network implementation. Additionally, an integral action is included in the controller to cope with constant disturbances. The error convergence analysis guarantees the achievement of the trajectory tracking task and the boundedness of the output weight matrix estimation errors. The proposed scheme is designed such that an accurate knowledge of the quadrotor parameters is not needed. A comparison against the proposed controller and two other well-known schemes is presented. The obtained results showed the functionality of the proposed controller and demonstrated robustness to parametric uncertainty.  相似文献   

12.
This paper addresses the adaptive fuzzy event-triggered control (ETC) problem for a class of nonlinear uncertain systems with unknown nonlinear functions. A novel ETC approach that exhibits a combinational triggering (CT) behavior is proposed to update the controller and fuzzy weight vectors, achieving the non-periodic control input signals for nonlinear systems. A CT-based fuzzy adaptive observer is firstly constructed to estimate the unmeasurable states. Based on this, an output feedback ETC is proposed following the backstepping and error transformation methods, which ensures the prescribed dynamic tracking (PDT) performance. The PDT performance indicates that the transient bounds, over-shooting and ultimate values of tracking errors are fully determined by the control parameters and functions chosen by users. The closed-loop stability is guaranteed under the framework of impulsive dynamic system. Besides, the Zeno phenomenon is circumvented. The theoretical analysis indicates that the proposed scheme guarantees control performance while considerably reducing the communication resource utilization and controller updating frequency. Finally, the numerical simulations are conducted to verify the theoretical findings.  相似文献   

13.
Traditional approximate/adaptive dynamic programming (ADP) methods can handle a very special class of systems subject to symmetry constraints. In this study, I extend the exiting ADP to a broader class of nonlinear dynamic systems with asymmetry constraints. Firstly, I propose a novel nonquadratic cost function, based on which the developed optimal controller by solving Hamilton–Jacobi–Bellman equation can limit its value to arbitrarily prescribed bound. Then, to avoid “curse of dimensionality”, I approximately implement the addressed controller via single-network adaptive critic design. Fuzzy Hyperbolic Model is introduced to construct the single critic network by approximating optimal cost function, from which I further derive the optimal control law. The potential advantages are that the control structure is simple and the computational load is low. Lyapunov synthesis proves the ultimately uniformly bounded stability of closed-loop control system. Finally, numerical simulation results verify the efficiency and superiority of the proposed approach.  相似文献   

14.
In this paper, the problem of adaptive fuzzy fault-tolerant control is investigated for a class of switched uncertain pure-feedback nonlinear systems under arbitrary switching. The considered actuator failures are modeled as both lock-in-place and loss of effectiveness. By utilizing mean value theorem, the considered pure-feedback systems are transformed into a class of switched nonlinear strict-feedback systems. Under the framework of backstepping design technique and common Lyapunov function (CLF), an adaptive fuzzy fault-tolerant control (FTC) method with predefined performance bounds is developed. It is proved that under the proposed controller, all the signals of the close-loop systems are bounded and the state tracking error for each step remains within the prescribed performance bound (PPB) regardless of actuator faults and the system switchings. In addition, the tracking errors and magnitudes of control inputs can be reduced by adjusting the PPB parameters of errors in the first and last steps. The simulation results are provided to show the effectiveness of the proposed control scheme.  相似文献   

15.
This paper focuses on the problem of adaptive tracking quantized control for a class of interconnected pure feedback time delay nonlinear systems. To satisfy the requirement of prescribed performance on the output tracking error, a novel asymmetric tangent barrier Lyapunov function is developed. The decentralized adaptive controller is designed via backstepping method. To deal with the uncertain interconnected nonlinear functions, we design a new virtual control input in the first step. Instead of estimating the bound of each unknown function, we use the adaptive method to estimate the bound of the composite function which is composed of the unknown functions. Thus the over parameterization problem is avoided. It is proved that the output of each subsystem satisfies the prescribed performance requirement and other state variables are bounded. Finally, the simulations are performed and the results verify the effectiveness of the proposed method.  相似文献   

16.
This paper studies the sampled outputs-based adaptive fault-tolerant control problem for a class of strict-feedback uncertain nonlinear systems, where the nonlinear functions are allowed to include the unmeasured system states. Within the framework, a sampled output observer is introduced to jointly estimate the system states and parameters. By combining the estimated states and the supervisory switching strategy, an adaptive fault-tolerant controller is designed to achieve the desirable tracking performance. By using Lyapunov stability theory, it is proved that all the signals of the closed-loop systems are bounded and the tracking error converges to an adjustable neighbourhood of the origin eventually both in the fault free and faulty cases. Especially, if the outputs are available all the time, the proposed output feedback fault-tolerant control method can ensure the tracking error satisfy the prescribed performance bounds regardless of the faults. Finally, two examples are used to illustrate the effectiveness of the proposed method.  相似文献   

17.
This paper proposes a robust adaptive control strategy for a class of state-constrained uncertain nonlinear systems with prescribed transient and steady-state behavior. The prescribed tracking performance can be characterized by constraints on an output tracking error. Both state and output constraints are achieved by bounding integral barrier Lyapunov functions in the backstepping procedure. A robust adaptive term is designed to compress auxiliary system uncertainties without the knowledge of their bounds. The satisfaction of control constraints and tracking error convergence are verified by theoretical analysis and are illustrated by simulation results.  相似文献   

18.
In classical model reference adaptive control (MRAC), the adaptive rates must be tuned to meet multiple competing objectives. Large adaptive rates guarantee rapid convergence of the trajectory tracking error to zero. However, large adaptive rates may also induce saturation of the actuators and excessive overshoots of the closed-loop system’s trajectory tracking error. Conversely, low adaptive rates may produce unsatisfactory trajectory tracking performances. To overcome these limitations, in the classical MRAC framework, the adaptive rates must be tuned through an iterative process. Alternative approaches require to modify the plant’s reference model or the reference command input. This paper presents the first MRAC laws for nonlinear dynamical systems affected by matched and parametric uncertainties that constrain both the closed-loop system’s trajectory tracking error and the control input at all times within user-defined bounds, and enforce a user-defined rate of convergence on the trajectory tracking error. By applying the proposed MRAC laws, the adaptive rates can be set arbitrarily large and both the plant’s reference model and the reference command input can be chosen arbitrarily. The user-defined rate of convergence of the closed-loop plant’s trajectory is enforced by introducing a user-defined auxiliary reference model, which converges to the trajectory tracking error obtained by applying the classical MRAC laws before its transient dynamics has decayed, and steering the trajectory tracking error to the auxiliary reference model at a rate of convergence that is higher than the rate of convergence of the plant’s reference model. The ability of the proposed MRAC laws to prescribe the performance of the closed-loop system’s trajectory tracking error and control input is guaranteed by barrier Lyapunov functions. Numerical simulations illustrate both the applicability of our theoretical results and their effectiveness compared to other techniques such as prescribed performance control, which allows to constrain both the rate of convergence and the maximum overshoot on the trajectory tracking error of uncertain systems.  相似文献   

19.
In this paper, an adaptive output feedback fault tolerant control (FTC) based on actuator switching is proposed for a class of single-input single-output (SISO) nonlinear systems with uncertain parameters and possible actuator failures, for which a set of healthy actuators are available as backups. While high-gain K-filters are utilized to estimate the unmeasured states, an adaptive control law is designed to compensate for the parameter uncertainties and certain actuator failures, an actuator switching strategy based on a set of appropriately designed monitoring functions (MFs) is proposed to tackle those serious actuator failures, make tracking error satisfy prescribed transient and steady-state performance and guarantee closed-loop signal boundedness.  相似文献   

20.
This paper is concerned with the high performance adaptive robust control problem for an aircraft load emulator (LE). High dynamic capability is a key performance index of load emulator. However, physical load emulators exist a lot of nonlinearities and modeling uncertainties, which are the main obstacles for achieving high performance of load emulator. To handle the modeling uncertainty and achieve adjustable model-based compensation, firstly, the mathematical model of the load emulator is built, and then a nonlinear adaptive robust controller only with output feedback signal is proposed to improve the tracking accuracy and dynamic response capability. The controller is constructed based on the adaptive robust control framework with necessary design modifications required to accommodate uncertainties and nonlinearities of hydraulic load emulator. In this approach, nonlinearities are canceled by output feedback signal; and modeling errors, including parametric uncertainties and uncertain nonlinearities, are dealt with adaptive control and robust control respectively. The resulting controller guarantees a prescribed disturbance attenuation capability in general while achieving asymptotic output tracking in the absence of time-varying uncertainties. Experimental results are obtained to verify the high performance nature of the proposed control strategy, especially the high dynamic capability.  相似文献   

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