Adaptive neural control of nonlinear fractional order multi- agent systems in the presence of error constraintion

In this paper, the problem of fractional order multi-agent tracking control problem is considered. External disturbances, uncertainties, error constraints, transient response suitability and desirable response tracking problems are the challenges in this study. Because of these problems and challenges, an adaptive control and neural estimator approaches are used in this study. In the first part of this article, the fractional order multi-agent systems are investigated with unknown parameters in the presence of error constraints. Then, a controller is designed on the basis of adaptive control and dynamic surface control so that the control objective of pursuing the desired output is achieved in the presence of the required constraints. The effective performance of the proposed controller is demonstrated by simulation by MATLAB software.