Neural Adaptive Robust Finite-Time Control of Tractor-Trailer Wheeled Mobile Robot via Input-Output Feedback Linearization Technique
Subject Areas : Renewable energyMaliheh Kazemipour 1 , Khoshnam Shojaei 2
1 - Department of Electrical Engineering- Najafabad Branch, Islamic Azad University, Najafabad, Iran
2 - Digital Processing and Machine Vision Research Center- Najafabad Branch, Islamic Azad University, Najafabad, Iran
Keywords: Feedback linearization, neural network robust adaptive control, tractor-trailer mobile robot, Finite-time control, Nonholonomic constraints,
Abstract :
The reference trajectory tracking is one of the most important issues in the field of tractor-trailer wheeled mobile robots control. In this paper, thetrajectory tracking control issues of a tractor-trailer wheeled mobile robot has been significantly solved in the presence of structural uncertainties,non-holonomic constraints and external disturbance. The proposed scheme is based on a design that the tractor-trailer’s state space representation is extracted from its dynamic and kinematic models and presented ina companion format first. In the following,by considering the state space representation of system, the control algorithm is presented includingtwo external and internal control loops. Toward this end, the control law has been developed in the inner loop via input-output feedback linearization in a nonlinear feedback formwhich is continuously eliminating the nonlinear dynamics of the system. Then,by using a combination of the output that is produced in linearization steps with a terminal sliding mode control algorithm and sketching a neural robust adaptive finite time controller in the outer loop, the accurate and fast performance of the closed loop system has been guaranteed in the presence of uncertainties. The proposed control algorithmfinally guarantees the boundedness of closed-loop signals and accurate finite time convergence of tracking errors. At the end, the effectiveness of the proposed scheme has been demonstrated and shown through the extended Lyapunov theorem and simulated by MATLAB application.
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