Non Linear and Multi Fractional Tuning Method for Autonomous Vehicles

Abstract

The mathematical model of mover is determined using a Newton-Euler formulation. This paper deals with the simulation depend on proposed controller of an industrial mover that can overcome this trouble. It is important to notice that these control loop parameters error cannot be eliminated from the interaction system completely. Within these possibilities, the control system's performance and the robustness must be considered as important. The aim is to provide industrial oriented solutions and improve the behavior of a differential control system, with an Auto tuning Proportional-Integral-Derivative (ATPID) controller structure. Fractional Order Proportional Integral Derivative controller tuned by genetic algorithm, it is investigated to control and stabilize the position and attitude of control system using feedback linearization. This controller is used as a reference to compare its results with Proportional Integral Derivative (PID) controller tuned by gain margin. The control structure performance is evaluated through the response and minimizing the error of the position and attitude. Simulation results, demonstrates that position and attitude control using auto PID has fast response, better steady state error and measurement error than PID. By simulation the two controllers are tested under the same conditions using Simulink under Matlab programming.