(untitled) (Jurnal Mekanikal, 2018)
This paper presents a new intelligent controller algorithm comprising an on-line multi-layer artificial neural network (ANN) training scheme to estimate the inertia matrix ofthe robot arm to enhance the performance of the active force control (AFC) scheme. The robot under study is a planar two-link rigid robot which is subjected to a non-linear disturbance torques acting at the robot joints. The algorithm has two stages, namely the ANN training stage and -the implementation stage. During the training stage, the proposed ANN scheme trains the ANNparameters (weights and biases) for a period oftime by utilising the back-propagation (BP) learning method. After a sufficient training period, the training session is switched off, and the ANN is ready to be used in the implementation stage of the intelligent AFC-ANN controller scheme. The results of the training and implementation stages are shown and discussed. It is shown that the proposed controller scheme is very effective and robust. The simulation is accomplished using MATLAB@ software.