Assessment of Alternative Controller Tuning Techniques for Systems without Ultimate Parameters
DOI:
https://doi.org/10.13052/jgeu0975-1416.1316Keywords:
PID controller, tuning techniques, particle swarm optimization, ultimate parameters, robustnessAbstract
This work presented in this article aims at designing and analysingalternate methods for tuning of the Proportional – Integral – Derivative (PID) controller for the plants that do not possess the ultimate parameters (ultimate gain and ultimate period). The motivation lies in the fact that the conventional methods such as the Ziegler-Nichols (Z-N) approach require the ultimate parameters for designing the PID controllers. However, because there exist some plants which do not have these parameters, and hence it is difficult to design controllers for such plants using conventional approaches directly. So, there is a need of using some alternative ways to design controllers for such plants. So, in the presented work, Particle Swarm Optimization (PSO), Extended Forced Oscillations (EFO), and Internal Model Control (IMC) methods have been applied for designing PID controllers suitable for such a plant. All the techniques were tested for their capability in optimizing control performance on rise time, settling time, overshoot, and error indices like Integral of Absolute Error (IAE), Integral of Squared Error (ISE), Integral of Time-Weighted Absolute Error (ITAE), and Integral of Time Squared Error (ITSE). Special attention was given to the objective function of ITAE minimization for the PSO-based PID controller. The results show that out of various approaches, the PSO-based PID controller provides the fastest response with minimum overshoot and low values of errors compared to EFO-based and IMC-based PID controllers. The EFO-based PID controller gave a mediocre performance while the IMC-based PID turned out to be the worst, giving a response that was the slowest with maximum errors. This work is carried out for a comprehensive comparison of various alternative tuning approaches, and it presents PSO-based PID as the most robust and reliable solution for plants with no ultimate parameters hence proposes it as an efficient alternative to conventional PID tuning strategies.
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