Optimization of dynamic parameter design of Stewart platform with Particle Swarm Optimization (PSO) algorithm

Abstract

Today motion simulators are being produced rely on electric actuators. The conventional way of dealing with high velocity, accelerations, and bulky payload is using a bigger actuator, but this leads to increased power usage and costs. To overcome these limitations, an optimized design of the Stewart platform design parameter improves simulators’ ability to support the weight of the equipment and satisfy the desired velocity and acceleration. However, it is challenging to set platform design parameters to maintain efficiency across the entire workspace. In this article, the kinematics and dynamics of the six-axis general Stewart robot are explored. A high-rated desired velocity and acceleration for the Stewart platform are defined and simulated. Then, the electric actuator force during some motion trajectory based on the defined workspace, velocity, and acceleration are calculated. Particle Swarm Optimization (PSO) is employed to optimize platform design parameters. The algorithm defines a cost function to minimize the maximum speed and maximum Force of the actuator by examining the structural kinematics arrangement of design parameters. Findings demonstrate that optimized design parameters have been successful in reducing the maximum actuator power 88.3%. Additionally, improves Stewart platform mechanical components’ life. These procedures can be employed for any Stewart platform.