Optimal model reference control scheme design for nonlinear strict-feedback systems

Abstract EN

n this paper, a new design of the model reference control scheme is proposed ina class of nonlinear strict-feedback system.

First, the system is analyzed using Lyapunovstability analysis.

Next, a model reference is used to improve system performance.

Then, the Integral Square Error (ISE) is considered as a cost function to drive the error between the reference model and the system to zero.

After that, a powerful metaheuristic optimization method is used to optimize the parameters of the proposed controller.

Finally, the results show that the proposed controller can effectively compensate for the strictly-feedback nonlinear system with more desirable is considered as a cost function to drive the error between the reference model and the system to zero.

After that, a powerful metaheuristic optimization method is used to optimize the parameters of the proposed controller.

Finally, the results show that the proposed controller can effectively compensate for the strictly-feedback nonlinear system with more desirable performance.