Optimal FLC-Sugeno Controller based on PSO for an Active Damping System

Abstract

In this paper, a method for the design of an optimal Sugeno model (FLC-Sugeno) fuzzy logic controller for the active suspension system of quarter-vehicle models is presented. The parameters of the FLC-Sugeno controller are optimally searched, using the Particle Swarm Optimization (PSO) algorithm. The 16 optimized parameters include 3 parameters for adjusting the domain of the input state variables and control variables at the controller’s output, 4 fuzzy set adjustment numbers of the linguistic variables, and 9 parameters as the fuzzy rule weights of the rule system control. To compare and evaluate the effectiveness of the optimal FLC-Sugeno controller, an optimal PID controller using PSO is also implemented. Simulation results of the active damping system with the controllers when affected by the same type and standard road surface excitation show that the FLC-Sugeno controller is optimal for the quick ending of the oscillations of vehicle body displacement. The result shows that the proposed controlling scheme can be extended and applied to more complex active damping system models.

Digital Shadow-based Control of Temperature and Fault Classification in Shell and Tube Heat Exchanger using Fuzzy Logic Technique

“…The MPC fabulously contributed to reducing the settling time of the response. In Figure 8, the response of the cold fluid output temperature is followed in every instance and settles near to it with a small-time difference [16]. Open loop response of the system along with its setpoints.…”