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ABSTRACT
Control system is the vital integrant in proportional–integral–derivative (PID) controller. The controllers are also planted in many special-purpose control systems. PID controller is often combined with logic, sequential functions, selectors, and simple function blocks to build the complicated automation systems used for energy production, transportation, and manufacturing. In the existing process, PID controller controls water level, speed, temperature, etc. Some of the issues arise while using PID controller can be easily solved by integrating fuzzy or with some other soft computing techniques. The major difficulty in PID controller is feedback system, with constant parameters and no direct knowledge of the process. Our proposed methodology has been introduced to control the speed of highly nonlinear hybrid electric vehicles (HEVs) having an electronic throttle control system in the cascade control loop. In recent PID controllers, no such specific tuning methods are applicable. The proposed method uses fractional order fuzzy PID nonlinear controller that is used in the cascade control loop. Aging leader and challenger-aided multi-objective dragonfly algorithm is considered for controller optimization in closed loop. It is employed to enhance the gain of the controller for the reduction of integral absolute error, maximum overshoot, settling time elimination of disturbance, uncertainty model, and control HEVs.