This paper proposes a novel method to tune the I-PD controller structure for the time-delayed unstable process (TDUP) using Bacterial Foraging Optimization (BFO) algorithm. The tuning process is focussed to search the optimal controller parameters ( , , ) by minimising the multiple objective performance criterion. A comparative study on various cost functions like Integral of Squared Error (ISE), Integral of Absolute Error (IAE), Integral of Time-weighted Squared Error (ITSE), and Integral of Time weighted Absolute Error (ITAE) have been attempted for a class of TDUP. A simulation study for BFO-based I-PD tuning has been done to validate the performance of the proposed method. The results show that the tuning approach is a model independent approach and provides enhanced performance for the setpoint tracking with improved time domain specifications. 1. Introduction Proportional + Integral + Derivative (PID) controllers are widely used in various industrial applications in which setpoint tracking and disturbance rejection are necessary. This controller provides an optimal and robust performance for a wide range of operating conditions for stable, unstable and nonlinear processes. Based on the controller configuration (position of P, I, and D), the PID is classified as ideal PID, series PID, and parallel PID. Since an ideal PID controller has practical difficulties due to its unrealizable nature, it is largely considered in academic studies. Parallel PID controllers are widely used in industries due to its easy accomplishment in analog or digital form. The major drawbacks of the basic parallel PID controllers are the effects of proportional and derivative kick. In order to minimize these effects, modified forms of parallel controller structures such as ID-P and I-PD are widely considered [1]. Time Delayed Unstable Processes (TDUP) considered in this work are widely observed in chemical process industries (exothermic stirred reactors with back mixing, pump with liquid storage tank, combined feed/effluent heat exchanger with adiabatic exothermic reaction, bioreactor, polymerization reactor, jacketed CSTR) [2]. Fine tuning of controller parameters for these systems is highly difficult than in open loop stable systems since (i) unstable processes are hard to stabilize due to unstable poles, (ii) the controller gains are limited by a minimum and maximum value based on the process time delay (ratio of process time delay to process time constant, that is, ratio). The increase in time delay “ ” in the process narrows down the limiting value and it restricts the
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