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

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.

Automated summary

This paper presents a study on the tracking control problem of fractional order multi-agent systems in the presence of uncertainties. The study considers the issues of error constraints, saturated inputs, and transient response suitability. A neural adaptive control approach is used to address these challenges, and the effectiveness of the proposed controller is demonstrated through simulation using MATLAB software.