The PID controller parameter tuning based on a modified differential evolutionary optimization algorithm for the intelligent active vibration control of a combined single link robotics flexible manipulator - Moloody, Abbas; As’arry, Azizan; Hong, Tang Sai; Raja Kamil, .; Zolfagharian, Ali (Semarak Ilmu Publishing, 2025)
This paper introduces some of the various techniques of vibration control and optimization for the purpose of vibration reduction and balancing. Here, in this research by comprising three of the most effective variational techniques now, a Modified Differential Evolutionary Optimization Algorithm (MDEOA) method is suggested to handle the challenge of adjusting the PID controller parameters for the Intelligent Active Vibration Control (IAVC) of a Combined Single Link Robotics Flexible Manipulator (CSLRFM) in order to reduce the undesired effects of vibration. The Crossover Probability Factor (CPF) as the Certain Ratio (CR) and the Mutation Factor (MF) of the algorithm are gradually altered during algorithm iteration to enhance the method's performance during optimization. On this foundation, the PID controller parameter tuning and the issue of CSLRFM mechanical vibrations are addressed using the MDEOA method. This research suggests an evolutionary algorithm that incorporates the variational techniques mentioned above, which will be combined by a certain ratio, and the specific computational procedure. In this strategy, a Strictly Bearish Distributed Exponential Function (SBDEF) has been used as the main target and the criteria and indicators for evaluating and measuring the optimal performance of differential evolution are the Integral Absolute Error (IAE) rate and the PID controller parameter values. According to simulation findings, the technique can be used to optimize the PID controller parameters settings for the IAVC of the CSLRFM and a reduction in the mechanical vibrations. Simulation results illustrate the effectiveness of the proposed MDEOA strategy which is significantly and quite satisfactory about 25 to 30 (%) better than comparing to the other algorithms in improvement stabilization and vibration control of CSLRFM.