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Controllers and compensators are widely used in the design and development of mobile robotic devices for various applications such as exploration, search and rescue, surveillance, or object manipulation and transport. In this project, an intelligent controller has been designed and implemented for a vehicle following system. The system provides longitudinal action of a vehicle driver when it follows another vehicle and maintains a safe following distance to a leading vehicle. The intelligent control is implemented using fuzzy logic on a pair of Lego robotic vehicles. A model of the vehicle following system is created using Simulink and Matlab’s Fuzzy Logic Toolbox is used to develop a fuzzy inference system for intelligent control. A Sugeno type fuzzy system is selected for efficient computation on Lego NXT controllers. A two input single output fuzzy system is proposed. The inputs are the error from a target following distance and the rate at which the error is changing. A motor speed PWM change is the output. After empirical tuning of the intelligent controller in Simulink, it is implemented in hardware on a Lego NXT controller using Robot C. Simulation and hardware results verify that the intelligent controller is able to perform closely to the specified requirements. Fig. 1 illustrates the overall Simulink block diagram . Fig. 2 shows the dynamic model of the leading vehicle. The dynamic model of the following vehicle is similar to the leading vehicle.
Fig. 1: Overall Simulink block diagram of vehicle following system
Fig. 2: Simulink model of the leading vehicle
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For more details on this project refer to the following
Book Chapter Paper:
Chand, P., Kumar, K., Kumar. Development of an Intelligent Control Based Vehicle Following System. In Mobile Robotics: Principles, Techniques and Applications, 2015, Nova Science Publishers, USA. Available here
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