Optimizing Active Proof-Mass Damper in Cantilever Beam Structures: An Indirect Randomized PSO Approach for Enhanced Control and Stability

This paper studies the iterative application of Particle Swarm Optimization (PSO) algorithms to determine optimal control parameters for an Active Proof-Mass Damper (APMD). The focus is on damping resonance frequencies in a cantilever beam's first and second modes. Simulation results highlight the effectiveness of the proposed Randomized Inertia PSO (RPSO) algorithm, employing an indirect approach based on input and output data in the frequency domain. The RPSO algorithm exhibits accelerated convergence and reduced anomalies compared to its non-randomized counterpart, NRPSO. The transient response of the controlled system to impulse excitation demonstrates successful attenuation of both modes simultaneously. Comparative analyses of frequency responses and pole-zero plots, considering various optimization criteria, illuminate the behavior of the RPSO algorithm, displaying characteristics similar to H₂, H_∞, and Stability Max optimization. These findings emphasize the potential of RPSO in achieving desired control outcomes in dynamic systems, underscoring its significance in engineering applications.