Adaptive neural control of non‐linear fractional order multi‐agent systems in the presence of error constraints and input saturation

Abstract

This paper presents a tracking control problem for fractional order multi-agent systems in the presence of uncertainties. The study takes into account the problems of error constraints, saturated inputs and transient response suitability. Because of the existing challenges, a neural adaptive control approach is used in this study. Fractional order multi-agent systems are investigated with uncertainty in the presence of error constraints. A controller is designed on the basis of adaptive control and dynamic surface control. As a result, the control objective of pursuing the desired output is achieved in the presence of required constraints. The effective performance of the proposed controller is demonstrated by simulation using MATLAB software.