Adaptive Cruise Control of a Passenger Car Using Hybrid of Sliding Mode Control and Fuzzy Logic Control

This paper focuses on the design of adaptive cruise control (ACC) which was implemented on a passenger car based on sliding mode control (SMC) of throttle valve combining with fuzzy logic control of brake pedal. An important feature of the new adaptive cruise control system is the ability to maintain a proper inter-vehicle gap based on the speed of host vehicle and headway way. There are three important inputs of the ACC system, speed of host vehicle read from electronic control unit (ECU), headway time set by driver, and actual gap measured from a laser scanner. The ACC processes these three inputs in order to calculate distance error and relative velocity which are used as the two inputs for both SMC and fuzzy controller. The SMC determines throttle valve angle while fuzzy controller determines the brake command to maintain a proper gap based on current speed of the leading vehicle and the desired time headway. The experimental results show that the proposed controller can perform efficiently in ACC of a passenger car. INTRODUCTION Many researchers have tried to develop adaptive cruise control (ACC) using fuzzy logic controller [1], [2], [3]. These methods enable the host vehicles to follow autonomously preceding vehicles while keeping safety distance. However since fuzzy logic controller is a non-model based controller, it is designed based on experience of designer, the performance of fuzzy logic controller based ACC can be improved further if dynamics model of the vehicle is taken into consideration. Vehicle dynamics is very important in designing high performance controller, however it is quite difficult to obtain accurate vehicle parameters. System identification of the vehicle parameters requires extensive experiment tests on the real vehicle. Nonlinearity in the vehicle model causes change in the model parameters. Sliding mode control (SMC) is a technique derived from variable structure control. It has gradually been one of the most popular nonlinear control methods since 1977. It is widely used in many applications due to its effectiveness in nonlinear systems and robustness on model uncertainties and disturbances. Motor Driver Motor Mounting Frame FiO-Std RS-232 Vehicle Speed Pulse Motor Driver