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1.
This paper is concerned with the problem of dynamic surface asymptotic tracking for a class of uncertain nonlinear systems preceded by Bouc–Wen type of hysteresis nonlinearity. By introducing the nonlinear filters with a positive time-varying integral function, a novel robust adaptive control algorithm is presented without constructing the hysteresis inverse. Unlike some existing adaptive control schemes for systems with input hysteresis, the proposed controller not only solves the issue of “explosion of complexity” inherent in the recursive procedure, but also produces the asymptotic tracking in spite of input hysteresis and external disturbances. Finally, two simulation examples are presented to confirm the effectiveness of the developed control strategy.  相似文献   

2.
In this paper, an asymptotic adaptive dynamic surface tracking control strategy is investigated for uncertain full-state constrained nonlinear systems subject to parametric uncertainties and external disturbances. A novel disturbance estimator (DE) is firstly used to compensate for external disturbances. The parametric uncertainties are accordingly handled via a synthesized adaptive law. Then, by using the barrier Lyapunov function (BLF) and dynamic surface control (DSC), an appropriate backstepping design framework employing a novel adaptive-gain nonlinear filter is given, which avoids the “explosion of complexity” and relieves the conservatism of filter gain selection. The theoretical analysis reveals the asymptotic tracking performance is assured with the proposed controller. In the end, some simulation cases demonstrate the validity of the proposed controller.  相似文献   

3.
For a class of switched nonlinear systems with unmatched external disturbances and unknown backlash-like hysteresis, an adaptive fuzzy-based control strategy is proposed to handle the anti-disturbance issue. The unmatched external disturbances come from a switched exosystem. Our aim is to achieve the output tracking performance and the disturbance attenuation by using the adaptive fuzzy-based composite anti-disturbance control technique. First, based on the fuzzy logics, we design a switching adaptive fuzzy disturbance observer to estimate unmatched external disturbances. Second, a composite switching adaptive anti-disturbance controller is constructed. By means of the backstepping technique, disturbance estimations are added in each virtual control to offset the unmatched disturbances, which results in the different coordinate transformations. At last, the availability of the proposed approach is illustrated by a mass-spring-damper system.  相似文献   

4.
This paper is concerned with the problem of adaptive disturbance attenuation for a class of nonlinear systems. The traditional adaptive methods are almost impossible to compensate the time-varying unknown disturbance by designing parameter adaptive laws without a priori knowledge about the bounds of external disturbances. To solve the problem, a new strategy is proposed by constructing an augmented system where the external disturbance is considered as another component of the augmented state vector. Based on this, a double-gain nonlinear observer is employed to estimate the state of the augmented nonlinear system. Further, an output feedback control strategy is designed, and it is proved that the proposed strategy ensures that all the signals are bounded and the tracking error exponentially converges to an adjustable compact set. Finally, an example is performed to demonstrate the validity of the proposed scheme.  相似文献   

5.
This paper studies the fault-tolerant control (FTC) problem of a class of strict-feedback nonlinear systems. First, we put forward a key theorem which shows that type-B Nussbaum functions can be extended to the cases containing multiple Nussbaum functions in the same Lyapunov inequality under certain conditions. Then, by using the techniques of Nussbaum functions and adaptive control, a new fault-tolerant control scheme is proposed. Compared with the previous work, this paper considers unknown time-varying control coefficients and unknown time-varying fault coefficients of actuators. It is proved that all the signals of the closed-loop system are globally bounded and the tracking error converges to zero asymptotically. Finally, simulations are provided to verify the effectiveness of the proposed control scheme.  相似文献   

6.
This paper investigates globally bounded consensus of leader-following multi-agent systems with unknown nonlinear dynamics and external disturbance via adaptive event-triggered fuzzy control. Different from existing works where filtering and backstepping techniques are applied to design controllers and event-triggered conditions, a matrix inequality is established to obtain the feedback gain matrix and event-triggered functions. To save communication resources, a new distributed event-triggered controller with fully discontinuous communication among following agents is designed. Meanwhile, a strictly positive minimum of inter-event time is provided to exclude Zeno behavior. Furthermore, to achieve globally bounded leader-following consensus, an adaptive fuzzy approximator and a parameter estimator are designed to approximate the unknown nonlinear dynamics and parameters, respectively. Finally, the effectiveness of the proposed method is validated via a simulation example.  相似文献   

7.
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   

8.
For a class of large-scale nonlinear time-delay systems with uncertain output equations, the problem of global state asymptotic regulation is addressed by output feedback. The class of systems under consideration are subject to feedforward growth conditions with unknown growth rate and time delays in inputs and outputs. To deal with the system uncertainties and the unknown delays, a novel low-gain observer with adaptive gain is firstly proposed; next, an adaptive output feedback delay-free controller is constructed by combining Lyapunov-Krasovskii functional with backstepping algorithm. Compared with the existing results, the controllers proposed are capable of handling both the uncertain output functions and the unknown time delays in inputs and outputs. With the help of dynamic scaling technique, it is shown that the closed-loop states converge asymptotically to zero, while the adaptive gain is bounded globally. Finally, the effectiveness of our control schemes are illustrated by three examples.  相似文献   

9.
In this paper, an adaptive fuzzy decentralized control method is proposed for accommodating actuator faults for a class of uncertain nonlinear large-scale systems. The considered faults are modeled as both loss of effectiveness and lock-in-place. With the help of fuzzy logic systems to approximate the unknown nonlinear functions, the novel adaptive fuzzy faults-tolerant decentralized controllers are constructed by combining the backstepping technique and the dynamic surface control (DSC) approach. It is proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop systems are bounded and the tracking errors converge to a small neighborhood of zero. Simulation results are provided to show the effectiveness of the control approach.  相似文献   

10.
This paper focuses on an adaptive fuzzy fixed-time control problem for stochastic nonstrict nonlinear systems with unknown dead-zones by using dynamic surface control (DSC) technology. Fuzzy logic systems (FLSs) and DSC technology are used to approximate nonlinear functions and reduce the computational complexity, respectively. At the same time, the influence of the dead-zone disturbance is offset by transforming the dead-zone model into the nonlinear model that can be approximated by the FLSs. Then, based on the fixed-time stability theory, an adaptive fuzzy fixed-time tracking control strategy is proposed, which can ensure semi-global practical fixed-time stability of the system and the tracking error converging to a small neighborhood near the origin. Finally, two simulation examples are given to prove the effectiveness of the proposed control strategy.  相似文献   

11.
This paper studies the adaptive fuzzy fault-tolerant control design problem for a class of stochastic multi-input and multi-output (MIMO) nonlinear systems in pure-feedback form. The nonlinear systems under study contain unknown functions, unmeasured states and actuator faults, which are described by the loss of effectiveness and lock-in-place modes. With the help of fuzzy logic systems identifying uncertain stochastic nonlinear systems, a fuzzy state observer is established for estimating the unmeasured states. Based on the backstepping design technique with the nonlinear tolerant-fault control theory, an adaptive fuzzy output feedback faults-tolerant control approach is developed. It is proved that the proposed fault-tolerant control approach can guarantee that all the signals of the resulting closed-loop system are bounded in probability. Moreover, the observer errors and tracking errors can be regulated to a small neighborhood of the origin by choosing design parameters appropriately. A simulation example is provided to show the effectiveness of the proposed approach.  相似文献   

12.
In this paper, a robust adaptive control scheme is proposed for the leader following control of a class of fractional-order multi-agent systems (FMAS). The asymptotic stability is shown by a linear matrix inequality (LMI) approach. The nonlinear dynamics of the agents are assumed to be unknown. Moreover, the communication topology among the agents is assumed to be unknown and time-varying. A deep general type-2 fuzzy system (DGT2FS) using restricted Boltzmann machine (RMB) and contrastive divergence (CD) learning algorithm is proposed to estimate uncertainties. The simulation studies presented indicate that the proposed control method results in good performance under time-varying topology, unknown dynamics and external disturbances. The effectiveness of the proposed DGT2FS is verified also on modeling problems with high dimensional real-world data sets.  相似文献   

13.
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   

14.
In this paper, a command filter-based adaptive fuzzy controller is constructed for a class of nonlinear systems with uncertain disturbance. By using the error compensation signals and fuzzy logic system, a command filter-based control strategy is presented to make that the tracking error converge to an any small neighborhood of zero and all closed-loop signals are bounded. In the design procedure, fuzzy logic system is employed to estimate unknown package nonlinear functions, which avoids excessive and burdensome computations. The control scheme not only resolves the explosion of complexity problem but also eliminates the filtering error in finite-time. An example has evaluated the validity of the control method.  相似文献   

15.
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   

16.
This study carries out the problem of adaptive backstepping fuzzy tracking control for a class of full state constrained uncertain nonlinear system with unknown control directions. Based on Nussbaum-type functions and tan-type Barrier Lyapunov functions, a novel adaptive fuzzy tracking controller is proposed to guarantee that the system output tracking error asymptotically converges to zero, while the constraints on the states of system will not be violated during operation. Compared with the existing results, a better convergence effect is obtained for this class of systems. Stability analysis of the proposed closed-loop control system is supported by the Lyapunov stability theory. Finally, a simulation example is presented to illustrate the effectiveness of the proposed control strategy.  相似文献   

17.
非线性不确定系统的模糊自适应 输出反馈跟踪   总被引：2，自引：0，他引：2  
本文研究了非仿射非线性系统的模糊自适应 输出反馈跟踪。在非仿射非线性模型存在不确定的情况下，使用模糊自适应控制器对系统进行控制，并基于Lyapunov稳定性定理得出自适应律。通过解一个代数Riccati方程实现了 跟踪性能。估计状态通过引入高增益观测器得到，实现了系统的输出反馈控制。最后，通过对一个数值例子的仿真验证了算法的有效性。  相似文献   

18.
This article develops an asymptotic tracking control strategy for uncertain nonlinear systems subject to additive disturbances and parametric uncertainties. To fulfill this work, an adaptive-gain disturbance observer (AGDO) is first designed to estimate additive disturbances and compensate them in a feedforward way, which eliminates the impact of additive disturbances on tracking performance. Meanwhile, an updated observer gain law driven by observer estimation errors is adopted in AGDO, which reduces the conservatism of observer gain selection and is beneficial to practical implementation. Also, the parametric uncertainties existing in systems are addressed via an integrated parametric adaptive law, which further decreases the learning burden of AGDO. Based on the parametric adaption technique and the proposed AGDO approach, a composite controller is employed. The stability analysis uncovers the system asymptotic tracking performance can be attained even when facing time-variant additive disturbances and parametric uncertainties. In the end, comparative experimental results of an actual mechatronic system driven by a dc motor uncover the validity of the developed approach.  相似文献   

19.
This paper is concerned with event-triggered adaptive fuzzy tracking control for high-order stochastic nonlinear systems. The approach of fuzzy logic systems (FLSs) approximation is extended to high-order stochastic nonlinear systems to deal with the unknown nonlinear uncertainties. A novel high-order adaptive fuzzy tracking controller is firstly presented via a backstepping approach and event-triggering mechanism which can mitigate the unnecessary waste of computation and communication resources. Based on the above techniques, frequently-used growth assumptions imposed on unknown system nonlinearities are removed and the influence for the high order is handled. The proposed high-order adaptive fuzzy tracking control method not only deals with the influence of high order, but also ensures that the tracking error converges to a small neighborhood of the origin in probability. Finally, the effectiveness of the proposed control method is illustrated by a numerical example.  相似文献   

20.
In this paper, we study the consensus tracking control problem of a class of strict-feedback multi-agent systems (MASs) with uncertain nonlinear dynamics, input saturation, output and partial state constraints (PSCs) which are assumed to be time-varying. An adaptive distributed control scheme is proposed for consensus achievement via output feedback and event-triggered strategy in directed networks containing a spanning tree. To handle saturated control inputs, a linear form of the control input is adopted by transforming the saturation function. The radial basis function neural network (RBFNN) is applied to approximate the uncertain nonlinear dynamics. Since the system outputs are the only available data, a high-gain adaptive observer based on RBFNN is constructed to estimate the unmeasurable states. To ensure that the constraints of system outputs and partial states are never violated, a barrier Lyapunov function (BLF) with time-varying boundary function is constructed. Event-triggered control (ETC) strategy is applied to save communication resources. By using backstepping design method, the proposed distributed controller can guarantee the boundedness of all system signals, consensus tracking with a bounded error and avoidance of Zeno behavior. Finally, the correctness of the theoretical results is verified by computer simulation.  相似文献   

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