Adaptive prescribed performance asymptotic tracking control for nonlinear systems with time‐varying parameters

Abstract

This study considers the problem of prescribed performance adaptive asymptotic tracking control for a class of nonlinear systems with time-varying parameters. A novel adaptive tracking control scheme is constructed by using the congelation of variables method and the backstepping method, in which the adaptive laws are designed to approximate the averages of the time-varying parameters. The normalized function transformation is introduced to achieve the prescribed performance control; meanwhile, the issue of the explosion of complexity is avoided by using the command filtered technique. In addition, the proposed approach guarantees that all signals of the closed-loop system are bounded and the tracking error can asymptotically converge to zero, while staying within prescribed boundaries. Finally, the effectiveness of the control strategy is shown by two simulation examples.

Command filtered adaptive tracking control of nonlinear systems with prescribed performance under time‐variant parameters and input delay

“…Remark 1. Given that time-variant parameters, disturbances, and input delay are considered simultaneously, the system (1) is more general than that in [21][22][23]36,37. This emphasizes the fundamental discrepancy between this article and the existing command filtering control methods. [13][14][15][16][17][18][21][22][23]36,37 Besides, most of these results can ensure ultimately uniformly bounded-error tracking performance for closed-loop systems only while the zero-error asymptotic convergence performance is a more important index in practical systems.…”

A neural network sliding mode method for nonlinear motors

“…The random noise b at this stage is 0.3rands (1). When the external disturbance d(t) is 30sin(t), the simulation is shown in Figures 7-9.…”

“…At this stage, the external disturbance d(t) is 20sin(t), and the random noise b is 3rands (1) and 5rands (1). When the random noise b is 3rands (1), the simulation is shown in Figures 19-21.…”

“…However, restricted by the environment and internal characteristics, the motor cannot perform normally. Meanwhile, there are a lot of nonlinear and complex behaviors in daily work 1–3 . PID theory and fuzzy theory have limited ability to maintain the stability of nonlinear systems.…”

“…Meanwhile, there are a lot of nonlinear and complex behaviors in daily work. [1][2][3] PID theory and fuzzy theory have limited ability to maintain the stability of nonlinear systems. They cannot respond to state changes in time, and are easily influenced by the external environment.…”