Simulation Performance of Pid and Fuzzy Logic for Higher Order Systems
Fuzzy control is widely used in industrial processes to achieve optimal control performances for higher order systems
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Proportional Integral Derivative (PID) controllers are widely used in industrial processes for their simplicity and robustness. The main application problems are the tuning of PID parameters to obtain a good settling time, rise time, and overshoot. The challenge is to improve the timing parameters to achieve optimal control performances for the higher-order system. Higher-order system is a critical need in many industrial plants. Fuzzy control is based on a logical system that is much closer in spirit to human thinking and natural language than traditional logical systems. During the past seve...
Proportional Integral Derivative (PID) controllers are widely used in industrial processes for their simplicity and robustness. The main application problems are the tuning of PID parameters to obtain a good settling time, rise time, and overshoot. The challenge is to improve the timing parameters to achieve optimal control performances for the higher-order system. Higher-order system is a critical need in many industrial plants. Fuzzy control is based on a logical system that is much closer in spirit to human thinking and natural language than traditional logical systems. During the past several years, fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of fuzzy set theory, especially in the realm of industrial processes, which do not lend themselves to control by conventional methods because of a lack of quantitative data regarding the input-output relations. The fuzzy logic controller (FLC) based on fuzzy logic provides a means of converting a linguistic control strategy based on expert knowledge into an automatic control strategy.
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