Adaptive Neural Control of Uncertain Nonlinear Systems Using Disturbance Observer

Abstract

This paper studies the problem of prescribed performance adaptive neural control for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems in the presence of external disturbances and input saturation based on a disturbance observer. The system uncertainties are tackled by neural network (NN) approximation. To handle unknown disturbances, a Nussbaum disturbance observer is presented. By incorporating the disturbance observer and NNs, an adaptive prescribed performance neural control scheme is further developed. Then, the expected asymptotically convergent tracking errors between system output signals and desired signals are achieved. Numerical simulation results demonstrate the effectiveness of the proposed control scheme.

Adaptive neural prescribed performance output feedback control of pure feedback nonlinear systems using disturbance observer

“…Over the past few decades, due to its simple structure and easily implementing in engineering, nonlinear disturbance observer (NDO) is regarded as one of the most effective approach to compensate the unknown time-vary disturbances and approximation errors, and various adaptive control schemes have been developed based on NDO for uncertain nonlinear system to improve the robustness of closed-loop system. [22][23][24][25][26] In Reference 27, an NDO-based robust control scheme was presented for a class single input single output (SISO) uncertain nonlinear systems. For a class of multiple input multiple output (MIMO) uncertain nonlinear systems, a robust control method was developed by employing the NDO to estimate the compounded disturbance in Reference 28.…”

“…Assumption (). The unknown external disturbance d i ( t ) is bounded, that is, there exists an unknown positive constant d iM such that .…”

“…Assumption 3. (22)(23)(24)(25). The unknown external disturbance d i (t) is bounded, that is, there exists an unknown positive…”

Event‐triggered observer‐based robust H∞ control for networked control systems with unknown disturbance

“…Yet, along with these advantages, some challenging issues (bandwidth allocation, communication delay, packet dropouts, packet disorders, and channel fading) emerged and gave rise to much attention. Then most recently, the research on the NCSs has become a heated topic and many elegant results have been proposed . For instance, in Reference , an optimal linear filter for the NCSs was designed with involving time‐correlated fading channels.…”

A new unified input‐to‐state stability criterion for impulsive stochastic delay systems with Markovian switching

“…1,2 Over past few decades, SDSs have received considerable attention because they provide a framework for mathematical modeling of real world problems. Some classical methods such as the Lyapunov function, the Lyapunov-Krasovskii functional, the Lyapunov-Razumikhin theorem, the LaSalle-type theorem, the comparison principle and the Halanay inequality, have been proposed to investigate the stability and control problems for SDS, and a large number of results have been reported, see for example, [1][2][3][4][5][6][7][8][9][10][11][12] and the references therein. Recently, SDSs driven by continuous-time Markov chains have also attracted considerable attention, since it can model practical situations when a SDS experiences some abrupt changes in its structure and parameters.…”