Evaluation of Cruise Control Systems: A Comparative Study of Fuzzy Logic, Linear, and Nonlinear Controllers
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Abstract
Cruise control systems are an essential component in the field of mechatronics, designed to maintain a vehicle's speed at a predetermined rate. This capability is widely hired inside the automobile industry to decorate riding comfort and fuel performance. A Cruise Control System (CCS) generally aims to adjust and sustain a predetermined speed, adapting to various road situations. The key components of this system consist of a velocity sensor, measurement system, controller, and actuator. This takes a look at evaluates the performance of three distinct sorts of controllers implemented in CCS: Intelligent Fuzzy Logic Controller (FLC), classical linear controller, and nonlinear controller. The FLC, in particular, processes information regarding vehicle speed and adjusts the throttle position to maintain the desired speed. Through simulation results, the overall performance of those three controllers is in comparison. The findings indicate that the FLC demonstrates a fast reaction and quick attainment of the favored pace in comparison to the classical linear and nonlinear controllers. Nonetheless, the classical linear and nonlinear controllers additionally showcase balance and fine response, making them possible options for cruise manipulate programs.
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