Decentralized Single-Neuron-Based Distributed Controller for Vibration Equalization in an Elastic Coupled Multi-motor System

Abstract

Multi-motor system (MMS) is a one of the highly nonlinear complicated MIMO systems used in industry. The elastic coupled MMS forms a mechanical resonator as a result of the stiffness of elastic shafts, which are mechanically coupled to each other. The resulted mechanical resonance frequencies have back effects on the MMS. Some of such effects are: short-term wearing of the system motors, faulty operation of the entire system, and partially or entirely defective product out of the system. The work presented in this paper manipulates the problem resulted in MMS. The main contribution of this paper is to propose a stable control algorithm of single-layer, simple structure neuro-controller. The proposed algorithm is based on Lyapunov theory in applying adaptive learning factor to guarantee bounded control of MMS. The main target of the proposed algorithm is to attenuate the effect of mechanical oscillations resulted in the MMS effectively. An experimental setup of MMS is used to assess the performance of the proposed control technique in the real time and provide the experimental data. Moreover, stability analysis of the employed technique based on Lyapunov stability theory is presented in the paper.