Intelligent active force control of a robotic arm using genetic algorithm

Abstract

The main requirement of an active force control (AFC) applied to a dynamical system is the estimation of the inertia matrix, IN to compensate for the disturbances and uncertainties in the system. In this paper, genetic algorithm (GA) is used to estimate suitable value of IN of a robotic manipulator necessary for the implementation of the AFC strategy through a simulation study. A set of constant torques at the joints is deliberately introduced as the disturbance mechanism to test the effectiveness of the proposed scheme. The results show that the GA used in the study being a stochastic and global optimizer successfully computes appropriate IN value to effect the control action. The proposed scheme exhibits a high degree of robustness and accuracy as the track error is bounded within an acceptable range of value even under the influence of the introduced disturbance.