In this research paper, an intelligent fuzzy PID controller is developed to control the outlet temperature of a shell and tube heat exchanger. The aim of the proposed controller is to regulate the temperature of the outgoing fluid to a desired level in the shortest possible time irrespective of load and process disturbances, equipment saturation and nonlinearity. The fuzzy PID controller provides a satisfactory performance in both steady state and transient state and overcomes the drawbacks of conventional PID controller and feed-forward controller. The developed fuzzy PID controller has demonstrated 84% improvement in the overshoot and 74% improvement in settling time from the classical controller. Also control accuracy is 100% as steady state error becomes zero. decision. Human expert knowledge is based upon heuristic information gained in relation to the operation of the plant or process, and its inherent vagueness ("fuzziness") offers a powerful tool for the modeling of complex systems. The fuzzy logic controller provides an algorithm, which converts the expert knowledge into an automatic control strategy. Fuzzy logic is capable of handling approximate information in a systematic way and therefore it is suited for controlling non linear systems and is used for modeling complex systems where an inexact model exists or systems where ambiguity or vagueness is common. The fuzzy control systems are rule-based systems in which a set of fuzzy rules represent a control decision mechanism to adjust the effects of certain system stimuli. With an effective rule base, the fuzzy control systems can replace a skilled human operator. The rule base reflects the human expert knowledge, expressed as linguistic variables, while the membership functions represent expert
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