Performance Comparison Of AFC-CA, AFC-GA, AFC-PSO And AFC-NN In Reducing The Vibration Of Suspended Handle Model - Chin, Jiun How (Universiti Sains Malaysia, 2022)
Vibration can be generated in any mechanical systems. Some of the vibration produced is beneficial in some processes such as drilling, cutting, and grinding but it will detrimental to the operator who operate the mechanical power tools. Hand-arm vibration syndrome (HAVs) is one of the consequences due to prolonged exposure of high level vibration. The anti-vibration glove is proposed and used in many industries, but it has limited effective frequency bandwidth and ineffective in handling the dynamics system. Therefore, Active Vibration Control (AVC) is suggested in vibration attenuation when operator is handling the power tool. From previous research, AVC with proportional-integral-derivative (PID) controller without Active Force Control (AFC) scheme is not perform very well in vibration attenuation compared to AVC-PID with AFC scheme. In this study, various intelligent tuning methods are applied such as Crude Approximation (CA), Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Neural Network (NN) together with AVC-PID system. The performance of AFC schemes in vibration attenuation is analyzed and compared under different combination of disturbances. From the results, AVC-PID with AFC schemes have performed better in reducing the vibration compared to passive system and AVC with PID controller. Among all the AFC schemes, AFCNN tuning methods has produced the best performance in reducing vibration even though under uncertainty disturbances. As a conclusion, AFC with intelligent tuning methods is an advantageous way for vibration attenuation of suspended handle.