Fuzzy Adaptive Output Feedback Control of MIMO Nonlinear Systems With Partial Tracking Errors Constrained

Adaptive fuzzy fault-tolerant output feedback control of uncertain nonlinear systems with actuator faults based on dynamic surface technique

Robust adaptive fuzzy filters output feedback control of strict-feedback nonlinear systemsIn this paper, an adaptive fuzzy robust output feedback control approach is proposed for a class of single input single output (SISO) strict-feedback nonlinear systems without measurements of states. The nonlinear systems addressed in this paper are assumed to possess unstructured uncertainties, unmodeled dynamics and dynamic disturbances, where the unstructured uncertainties are not linearly parameterized, and no prior knowledge of their bounds is available. In recursive design, fuzzy logic systems are used to approximate unstructured uncertainties, and K-filters are designed to estimate unmeasured states. By combining backstepping design and a small-gain theorem, a stable adaptive fuzzy output feedback control scheme is developed. It is proven that the proposed adaptive fuzzy control approach can guarantee the all the signals in the closed-loop system are uniformly ultimately bounded, and the output of the controlled system converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by a simulation example and some comparisons.

In this paper, a fuzzy adaptive output feedback control approach is developed for a class of SISO strict-feedback nonlinear systems with unmeasured states, unmodeled dynamics, and dynamical disturbances. In the backstepping recursive design, fuzzy logic systems are used to approximate the unknown nonlinear functions, a fuzzy adaptive high-gain observer is designed to estimate the unmeasured states; a dynamic signal is incorporated into the control scheme to dominate the dynamic uncertainties. Using the states estimates and combining the backstepping design technique, a fuzzy adaptive output feedback control is constructed recursively. It is proved that the proposed fuzzy adaptive output feedback control scheme can guarantee the all signals in the closed-loop system are semiglobally uniformly ultimately bounded (SUUB), and the observer and tracking error converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated via an example.

In this paper, we present a new scheme to design adaptive fuzzy output-feedback controller for uncertain nonlinear systems in the presence of input saturation. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, and a state filter is designed to estimate unmeasured states. Combining the backstepping recursive design with modular design techniques, a new adaptive fuzzy output control scheme is synthesized. Unlike some existing control schemes for systems with input saturation, the developed controller dose not require assumptions on the states available and nonlinear systems satisfying the matching condition. It is proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are semi-globally uniformly ultimately bounded, and the tracking error converges to a small neighborhood of the origin. A simulation is included to illustrate the effectiveness of the proposed approach.

In this paper, an adaptive fuzzy output feedback control approach is investigated for a class of stochastic nonlinear strict-feedback systems without the requirement of states measurement. The stochastic nonlinear system addressed in this paper is assumed to possess unstructured uncertainties (unknown nonlinear functions) and, in the presence of unmodeled dynamics, dynamics disturbances. Fuzzy logic systems are used to approximate the unstructured uncertainties, and a fuzzy state observer is designed to estimate the unmeasured states. By combining the backstepping design technique with the stochastic small-gain approach, a new adaptive fuzzy output feedback control approach is developed. It is proved that the proposed control approach can guarantee that the closed-loop system is input-state-practically stability (ISpS) in probability, and the observer errors and the output of the system converge to a small neighborhood of the origin by appropriate choice of the design parameters. Simulation results are included to indicate that the proposed adaptive fuzzy control approach has a satisfactory control performance. In addition, the simulation comparisons with the previous methods show that the proposed adaptive fuzzy control approach has robustness to the dynamical uncertainties.

In this paper, the problem of adaptive fuzzy output-feedback control is investigated for a class of uncertain switched nonlinear systems in strict-feedback form. The considered switched systems contain unknown nonlinearities, dead-zone, and immeasurable states. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, a switched fuzzy state observer is designed and thus the immeasurable states are obtained by it. By applying the adaptive backstepping design principle and the average dwell time method, an adaptive fuzzy output-feedback tracking control approach is developed. It is proved that the proposed control approach can guarantee that all the variables in the closed-loop system are bounded under a class of switching signals with average dwell time, and also that the system output can track a given reference signal as closely as possible. The simulation results are given to check the effectiveness of the proposed approach.

In this paper, a hybrid fuzzy adaptive output feedback control design approach is proposed for a class of multiinput and multioutput strict-feedback nonlinear systems with unknown time-varying delays, unmeasured states, and input saturation. First, fuzzy logic systems are employed to approximate unknown nonlinear functions in the system. Next, a smooth function is used to approximate the input saturation and an adaptive fuzzy state observer is constructed to solve the problem of unmeasured states. Based on the designed adaptive fuzzy state observer, a serial-parallel estimation model is established. By applying adaptive fuzzy dynamic surface control technique and utilizing the prediction error between the system states observer model and the serial-parallel estimation model, a new fuzzy controller with the composite parameters adaptive laws is developed based on Lyapunov-Krasovskii functional. It is proved that all variables of the closed-loop system are bounded and the system outputs can follow the given bounded reference signals as close as possible. A simulation example is provided to further show the effectiveness of this novel control scheme.

In this paper, an adaptive fuzzy output feedback control approach is presented for a class of single-input single-output uncertain nonlinear systems with unknown backlash-like hysteresis and unmeasured states. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, and a state filter observer is designed to estimate unmeasured states. Combining the backstepping recursive design with modular design techniques, a new adaptive fuzzy output control scheme is developed. It is proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are semiglobally uniformly ultimately bounded, and the tracking error converges to a small neighborhood of the origin. A simulation is included to illustrate the effectiveness of the proposed approach. The important feature of the proposed control approach is that it can solve the states immeasurable problem of nonlinear systems with unknown backlash-like hysteresis and the problem of unknown virtual control coefficients.

Output-feedback control of uncertain nonlinear systems using a self-structuring adaptive fuzzy observer

Distributed adaptive fuzzy control for multi-agent systems with full state constraints and unmeasured states

This paper addresses the output feedback trajectory tracking problem for a nonholonomic wheeled mobile robot in the presence of parameter uncertainties, external disturbances, and a lack of velocity measurements. An unknown function is approximated by the fuzzy logic system, and an adaptive fuzzy observer is introduced. Then, by combining the kinematic model with the dynamic model, a control strategy is proposed that integrates an auxiliary velocity controller with an integral terminal sliding mode controller. By applying the proposed control strategy, it is proven that all of the signals in the closed system are bounded and that the auxiliary velocity tracking errors converge to a neighborhood of the origin in finite time. Therefore, the tracking position errors converge asymptotically to a small neighborhood near the origin with a faster response than achieved by other existing controllers. The simulation results demonstrate the effectiveness of the proposed strategy.

Decentralized adaptive approximation-based fuzzy output-feedback control of uncertain switched stochastic interconnected nonlinear systems

In this paper, the command filter-based adaptive fuzzy finite-time output feedback control (FOFC) is investigated for the Electro-hydraulic servo system. For the uncertainties in the system, we utilize the fuzzy logic systems (FLSs) to estimate these uncertain nonlinearities and fuzzy state observer is established to approximate the unmeasurable hydraulic cylinder stem speed and the internal cylinder force. Then, a command filter-based finite time output feedback control is proposed to achieve high tracking precision, where the tracking errors can be regulated into a small neighborhood around the equilibrium proved by the Lyapunov finite-time stability theory. Moreover, a command filter is introduced to avoid the explosion of complexity in the backstepping procedure, where a compensation mechanism is developed to compensate for filter errors. Finally, simulation results are provided to demonstrate the effectiveness of the proposed control.

In this paper, a new fuzzy adaptive control approach is developed for a class of strict-feedback nonlinear systems with unknown time-delay. Using fuzzy logic systems to approximate the unknown nonlinear functions, a fuzzy adaptive observer is introduced for state estimation. Under the backstepping design, fuzzy adaptive output feedback control is constructed recursively. In addition, the number of on-line adaptive parameters is not more than the order of the considered systems. It is proved that the proposed backstepping design approach guarantees the semi-global boundedness property for all the signals. Finally, Simulation results are provided to show the effectiveness of the proposed approach.

The paper presents a new output feedback adaptive control scheme for multi-input and multi-output (MIMO) non-linear systems whose non-linear terms depend only on the output variable based on the backstepping approach with vector form. The assumption on the prior knowledge of the high frequency gain matrix in existing results is reduced and the new required condition for the high frequency gain matrix can be easily checked for certain plants so that the proposed method is widely applicable. This control scheme guarantees the global stability of the closed-loop systems and makes the tracking error be arbitrary small. A simulation example is included to demonstrate the proposed algorithm.