Hi,
When evaluating the robustness and suitability of different control strategies for a system, such as classical Proportional-Integral (PI) control, Predictive Control, and ANFIS based control, you can consider various but not limited to performance metrics and robustness tests like the following:
- Gain and Phase Margins: Determine the gain and phase margins for each controller by using Bode plots. The higher the margin, the more insensitive a system becomes to parameter variations or external disturbances.
- Step Response: Investigate the step response of your system with respect to each controller. A robust controller will maintain acceptable performance across a range of operating conditions.
- Robustness to Parameter Variations: Evaluate how control performance changes due to variations in system parameters. This is achieved by changing parameters within their anticipated variation ranges and observing if the control system maintains its operation capacity.
- Monte Carlo Simulations: Run simulations with randomly generated sets of system parameters within their uncertainty bounds and evaluate performance.
The best-suited control strategy for your system will depend on a balance of these factors, considering the specific requirements and constraints of your application. By applying these robustness tests and some other custom tests, you can decide on the most appropriate control for your system.
