Disturbance Observer-Based Adaptive Neural Network Output Feedback Control for Uncertain Nonlinear Systems

Abstract

This article is devoted to the output feedback control of nonlinear system subject to unknown control directions, unknown Bouc-Wen hysteresis and unknown disturbances. During the control design process, the design obstacles caused by unknown control directions and Bouc-Wen hysteresis are eliminated by introducing linear state transformation and a new coordinate transformation, which avoids using the Nussbaum function with high-frequency oscillation to deal with the issue. Besides, to settle the issue caused by the unknown disturbances, a novel nonlinear disturbance observer is designed, which has the characteristics of simple structure, low coupling, and easy implementation. Especially, a compensation item is constructed to offset the redundant items generated in the backstepping design process. Simultaneously, using the neural network and backstepping technology, an output feedback controller is devised. The controller ensures that all closed-loop signals are bounded, and the system output, state observation error, and disturbance observation error converge to a small neighborhood of the origin. Finally, to illustrate the effectiveness of the proposed scheme, simulation verification is carried out based on a numerical example and a Nomoto ship model.

Adaptive finite‐time stabilizing control of fractional‐order nonlinear systems with unmodeled dynamics via sampled‐data output‐feedback

“…Remark By using the dynamic signal $$$ v $$$ designed in Lemma 6, the influence cased by external disturbance $$$ {\Delta}_i\left(y,z\right) $$$ $$$ \left(i=1,\dots, n\right) $$$ can be restrained. In addition, we can learn from (1) that external disturbances are composite functions on $$$ t $$$, and these disturbances are not functions directly on $$$ t $$$ (such as disturbances $$$ d(t) $$$ in existing literature in References 46 and 47. For external disturbances in (1), we cannot construct a disturbance observer, which is similar to disturbance observers constructed in References 46 and 47, to compensate the adverse effects caused by external disturbances.…”

“…In addition, we can learn from (1) that external disturbances are composite functions on $$$ t $$$, and these disturbances are not functions directly on $$$ t $$$ (such as disturbances $$$ d(t) $$$ in existing literature in References 46 and 47. For external disturbances in (1), we cannot construct a disturbance observer, which is similar to disturbance observers constructed in References 46 and 47, to compensate the adverse effects caused by external disturbances.…”

Observer-Based Adaptive Finite-Time Neural Control for Constrained Nonlinear Systems With Actuator Saturation Compensation

“…However, the above approaches are not adequate for nonlinear systems with unknown functions. By means of high reliability and strong approximation, a composite neural control was proposed to reduce the system errors and avoid high-frequency oscillations [10]. By applying the nonlinear transformed function, a command-filtered neural controller was presented in [11].…”

“…By synthesizing the above observations, we will design an observer-based adaptive finite-time neural controller for constrained nonlinear systems subject to unmeasurable states, external disturbances, and actuator saturation. The primary innovations of this study are highlighted, as (1) Unlike the multi-objective adaptive CFB [8], the neural CFB [10], and the event-triggered DSC [3], the proposed controller, which integrates the CFB technology and the filtering-error compensation system, not only solves the problems of "explosion of complexity" and the filtering error but also realizes the fast finite time convergence. Compared to previous studies in [1]- [3], [20], [36], this study does not require the availability of system states, which means that the state observation and the controller can be designed independently.…”

Observer‐based neural adaptive fixed‐time tracking control for multi‐input multi‐output nonlinear systems with actuator faults

“…Rejecting mismatching external disturbances is an active research field. Until now, disturbance‐observer‐based adaptive neural control 22 has been investigated for uncertain nonlinear plants subjected to unknown disturbances. In Reference 3, a robust adaptive event‐triggered control scheme was developed for nonlinear systems, and in Reference 23 and 24, on the basis of commonly observed unmeasurable states in real applications, adaptive output feedback control methods were investigated for constrained nonlinear systems with unmeasurable states and mismatching external disturbances.…”