Abstract
We have designed and implemented an optimized PID controller for an adaptive cruise control system in this paper. The mathematical model for a cruise control system has been developed, and it is observed that it is a nonlinear first-order model with dead time. The objective functions chosen for optimizing the PID controller are ITE, ITAE and ITSE. The design of the optimized PID controller is based on the particle swarm optimization technique and teacher learning-based optimization technique. The results are scientifically compared with the conventionally tuned PID and fuzzy-based controllers. The optimized Proportional Integral Derivative controller shows better performance than a conventional PID and fuzzy-based controller. The overshoot of the system has been reduced to 0% from 46%, and the rise time has been reduced to 0.6150 s. This is the new work in the literature that will be quite useful for the performance enhancement of the cruise control system.
Additional information
Notes on contributors
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Snigdha Chaturvedi
Snigdha Chaturvedi has completed her BTech in electrical and electronics engineering from Uttar Pradesh Technical University in 2009. She has completed her MTech in control and instrumentation from Delhi Technical University in 2014. She is currently pursuing her PhD from Delhi Technological University.
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Narendra Kumar
Narendra Kumar has received his BE degree in electrical engineering from IIT Roorkee and ME degree in power system from PEC Chandigarh. He has received his PhD in instrumentation and control from DCE, Delhi. He is currently working as a professor in Delhi Technological University, in the Department of Electrical engineering. Email: [email protected]