Adaptive fixed-time control for nonlinear systems against time-varying actuator faults

Nonlinear Dynamics - The adaptive fixed-time control problem for nonlinear systems with time-varying actuator faults is investigated in this paper. A novel adaptive fixed-time controller is...     

Simplified global fault accommodation control design of uncertain nonlinear systems with unknown time-varying powers

This paper addresses the problem of global robust fault accommodation tracking for a class of uncertain nonlinear systems with unknown powers and actuator faults. It is assumed that the powers of the concerned system are unknown time-varying functions, all system nonlinearities are unknown, and unknown actuator faults depend on the time-varying power of a control input. A fault accommodation state-feedback controller is explicitly constructed based on the nonlinear error transformation technique using time-varying performance functions. Global tracking with the preselected performance bounds is established in the presence of unknown time-varying powers and unexpected actuator faults. Different from the previous results dealing with the problem of unknown time-varying powers, the proposed tracking strategy does not require the knowledge of the bounds of the time-varying powers and the nonlinear bounding functions of system nonlinearities. An underactuated mechanical system is simulated to validate the effectiveness of the proposed theoretical approach.     

Adaptive tracking control for a class of nonlinear non-strict-feedback systems

This paper focuses on the adaptive tracking control problem for a class of nonlinear non-strict-feedback systems. By introducing a compact set, the restrictive assumption that the lower bounds of the control gain functions must be positive constants is canceled in the proposed method, and the compact set is proved to be invariant set eventually. The functions in non-strict-feedback system are no longer required to be differentiable, and the neural networks are constructively used to deal with the unknown system functions, which contain the whole state variables of the non-strict-feedback system. Furthermore, it is rigorously proved that all the closed-loop signals are bounded and the tracking error converges to a small residual set asymptotically. Finally, simulation examples are provided to demonstrate the effectiveness of the designed method.     

Adaptive finite-time event-triggered command filtered control for nonlinear systems with unknown control directions

Nonlinear Dynamics - In this article, we study an adaptive finite-time event-triggered command filtered control problem based on output feedback for a class of nonstrict-feedback nonlinear systems...     

Adaptive fuzzy finite-time control of stochastic nonlinear systems with actuator faults

Nonlinear Dynamics - This paper considers the finite-time control problem for a class of nonlinear stochastic systems with actuator faults/failure. A fast convergence feedback control algorithm...     

Adaptive finite-time prescribed performance control for stochastic nonlinear systems with unknown virtual control coefficients

Nonlinear Dynamics - This paper is devoted to the adaptive finite-time prescribed performance control (FTPPC) for stochastic nonlinear systems with unknown virtual control coefficients (UVCCs),...     

ADAPTIVE H-INFINITY CONTROL OF A CLASS OF UNCERTAIN NONLINEAR SYSTEMS

It is concerned with the problem of disturbance attenuation with stability for uncertain nonlinear systems by adaptive output feedback. By a partial-state observer and Backstepping technique, an adaptive output feedback controller was constructed, which can solve the standard gain disturbance attenuation problem with internal stability.     

Adaptive fuzzy decentralized control for a class of pure-feedback large-scale nonlinear systems

In this paper, the problem of adaptive fuzzy decentralized control is investigated for a class of pure-feedback nonlinear interconnected large-scale systems. During the controller design, fuzzy logical systems are used to model packaged unknown nonlinearities and backstepping technique is used to construct adaptive fuzzy decentralized controller. It is shown that the proposed control scheme can guarantee that all the signals in the closed-loop system are semiglobally uniformly ultimately bounded. The main advantage of this study lies in that only one adaptive parameter needs to be estimated online for each subsystem. Simulation results further illustrate the effectiveness of the suggested approach.     

Adaptive neural tracking control for a class of perturbed pure-feedback nonlinear systems

This paper focuses on the problem of the adaptive neural control for a class of a perturbed pure-feedback nonlinear system. Based on radial basis function (RBF) neural networks’ universal approximation capability, an adaptive neural controller is developed via the backstepping technique. The proposed controller guarantees that all the signals in the closed-loop system are bounded and the tracking error eventually converges to a small neighborhood around the origin. The main advantage of this note lies in that a control strategy is presented for a class of pure-feedback nonlinear systems with external disturbances being bounded by functions of all state variables. A numerical example is provided to illustrate the effectiveness of the suggested approach.     

Adaptive fuzzy synchronization for a class of chaotic systems with unknown nonlinearities and disturbances

By incorporating a time-varying parameter into T-S fuzzy logic systems with nonlinear consequents (T-S-FLS-NRC), the synchronization of driver-response chaotic systems with unknown nonlinearities and disturbances is synthesized via state feedback controllers and updated adaptive laws. During designing process of synchronization, only three common parameters are needed to be adjusted automatically, and the number of adaptive laws is not related with the number of IF-THEN rules. Meanwhile, T-S-FLS-NRC is employed to approximate the unknown nonlinearities for the master and slave systems. The general form and high approximate capacity of T-S-FLS-NRC is useful to obtain fewer fuzzy rules than other fuzzy logic systems such as Mamdani or T-S fuzzy logic system with linear consequents. The synchronization method in this paper cannot only significantly reduce the on-line computational burden, but also can synthesize the fuzzy rules with high interpretability by means of intuition inferences. Finally, a numerical example is used to show the validity of the proposed synchronization method.