FPID Controller Parameter Optimization using Simulink Design Optimization

In this section, we utilize the Simulink design optimization software, specifically the Nonlinear Control Design Module Set (NCD), implemented in Matlab, to perform the optimization and tuning of the FPID control parameters for our system [27,28]. This software offers the capability to optimize any Simulink model by adjusting the required parameters within the defined boundaries set by the design specifications.

Design optimization in Simulink involves optimizing the response characteristics such as rise time, settling time, overshoot, and saturation limits. We employ the gradient descent optimization method to obtain the optimal FPID parameters [3,26,29]. The gradient descent method is a simple yet effective optimization approach. By utilizing the Simulink design optimization software, we can obtain the optimal gains that satisfy the given constraints and conditions.

Once the appropriate signal constraints and limitations are established, the adjusted gains are set accordingly, and the optimized tuning is achieved, preparing the system for operation. The Simulink design optimization software provides a graphical representation of the response, with the start response depicted in blue within the constraint window. Through the optimization process, the gains are adjusted to achieve the desired response characteristics and meet the specified design requirements.