Performance and robustness analysis of V-Tiger PID controller for automatic voltage regulator

Abstract

This paper presents a comprehensive study on the implementation and analysis of PID controllers in an automated voltage regulator (AVR) system. A novel tuning technique, Virtual Time response-based iterative gain evaluation and re-design (V-Tiger), is introduced to iteratively adjust PID gains for optimal control performance. The study begins with the development of a mathematical model for the AVR system and initialization of PID gains using the Pessen Integral Rule. Virtual time-response analysis is then conducted to evaluate system performance, followed by iterative gain adjustments using Particle Swarm Optimization (PSO) within the V-Tiger framework. MATLAB simulations are employed to implement various controllers, including the V-Tiger PID controller, and their performance is compared in terms of transient response, stability, and control signal generation. Robustness analysis is conducted to assess the system's stability under uncertainties, and worst-case gain analysis is performed to quantify robustness. The transient response of the AVR with the proposed PID controller is compared with other heuristic controllers such as the Flower Pollination Algorithm, Teaching–Learning-based Optimization, Pessen Integral Rule, and Zeigler-Nichols methods. By measuring the peak closed-loop gain of the AVR with the controller and adding uncertainty to the AVR's field exciter and amplifier, the robustness of proposed controller is determined. Plotting the performance degradation curves yields robust stability margins and the accompanying maximum uncertainty that the AVR can withstand without compromising its stability or performance. Based on the degradation curves, robust stability margin of the V-Tiger PID controller is estimated at 3.5. The worst-case peak gains are also estimated using the performance degradation curves. Future research directions include exploring novel optimization techniques for further enhancing control performance in various industrial applications.

An Optimized PID Controller Using Enhanced Bat Algorithm in Drilling Processes

“…The overall action of the controller is the sum of the contributions from these three terms. The final control signal 𝑢(𝑡) of the PID controller is the sum of the three terms as given [26,27]:…”

Improving load frequency controller tuning with rat swarm optimization and porpoising feature detection for enhanced power system stability

“…It offers a simple method for determining the proportional, integral, and derivative gains and is based on the system's response to step changes 33 . The following steps are used to optimize the PID coefficients 13 .…”

“…The writers of the aforementioned studies examined the techniques for fine-tuning a PID controller and assessing its robustness via variations in load patterns and parameter uncertainty. The study 13 introduces a new tuning approach called Virtual Time response-based iterative gain evaluation and re-design (V-Tiger) to iteratively tune PID gains for optimum control performance. The research 14 examined the effectiveness of the quasi-oppositional harmony search algorithm based on predictive control in reducing frequency deviation.…”