Development of intelligent active steering with fuzzy, PID controller and uncontrolled

Abstract

The design of a fuzzy controller entails the concept of input-output fuzzy variables, decision-making procedures for the fuzzy control laws, fuzzy inference logic, and defuzzification. Two input parameters and one output variable comprise a fuzzy controller. The yaw rate error and its derivative are used as inputs. Through the use of appropriate differential equations, fuzzification created the evaluated controller inputs structurally consistent with the circumstance of the information rules. The fuzzy control technique can be used to compensate for the program's various coefficients of road friction and fluctuations. To accommodate for disruptions, the vehicle's side slip angles and yaw rate should be monitored. The proposed framework here considers the system's various coefficient of friction of the road. The mathematical derivation demonstrates that the system meets a contrasting situation. Comprehensive computer tests are performed for a variety of abnormalities, including crosswind and braking torque. The results of the simulation will reveal the effect of disturbance absorption. The implemented controller's efficiency will be evaluated to that of uncontrolled and PID controller techniques. The findings indicate that when opposed to ordinary and PID control schemes, the Fuzzy proposed controller is more effective at attenuating various disturbances for different road correlations. Additionally, the simulation results indicate that the system is unresponsive to external disturbances and competent of compensating for the driver's 'delayed acts' in response to a sudden disturbance on any driving conditions.