Multi Objective Optimization of Control Parameters for Auto-Steering of Off-Road Vehicles

ABSTRACT: In this thesis, the lateral controller parameters of an agricultural tractor vehicle were optimized to reduce both the root mean square error (ERMS), and the peak error (Epeak), by using two evolutionary multi-objective optimization algorithms. The lateral controller of a tractor provides tracking of a desired path with minimum lateral error, which enhances the efficiency of agricultural plantation since many processes in agriculture require tracking a desired path. The evolutionary multi-objective optimization algorithms: NSGA-II and MODE are commonly used search algorithms to find the Pareto-front of the optimal solutions for multiple fitness functions. In parameter optimization of the lateral controller, two fitness functions, ERMS and Epeak, were evaluated along a predefined reference path of tracking through the simulation of the tractor motion in an agricultural field. Results of the optimization by both methods supported each other closely, and the optimization reduced the error figures down to 0.0016 m Epeak, and 0.0004 m ERMS. The obtained Pareto-front can be used to compromise between the Epeak and ERMS in setting the controller parameters best way for the conditions of the application. Keywords: NSGA-II - MODE - Lateral Error – Auto-Steering Control. …………………………………………………………………………………………………………………………