Plenary Lecture
Desing of Neural Network Based Fuzzy Inference System for Speed Control of Heavy Duty Vehicles with Electronic Throttle Control System
Professor Şahin Yıldırım
Co-author İkbal Eski
Erciyes University
Faculty of Engineering
Mechatronics Engineering Department
Turkey
E-mail: sahiny@erciyes.edu.tr
Abstract: The objective of this study is to apply various control approaches to control the speed of a heavy duty vehicle using an electronic throttle control system. However, the dc servo motor is used for controlling the angular position of electronic throotle valve. Moreover, four control techniquies are used to control prescribed two different random inputs of the heavy duty vehicle speed. These control structures are as standard PID controller, Model based neural network controller, Adaptive neural network based fuzzy inference controller and proposed robust adaptive neural based fuzzy inference control systems. On the other hand, the time performance specifications such as rise time, settling time, peak time, peak value, steady state error and etc are also examined for these control approaches. The results of the simulation for four approaches showed that the proposed robust adaptive neural network based fuzzy inference control system has better performance rather than other standard control systems under varying speed conditions. Finally, the proposed control system structure will be implented for speed control of dc servo motor.
Brief Biography of the Speaker: Brief Biography of the Speaker: Dr YILDIRIM has received the MSc degree in Mechanical Engineering in 1990 from Erciyes University, Turkey. He has received hise PhD degree in 1998 from Cardiff University. He was established Mechatronic Engineering Department in 2005, Kayseri, Turkey. He is head of the Mechatronic Engineering Department. He is lecturing the control theory, robotics, neural network applications in engineering at Erciyes University, Turkey. He has been supervised some national and international projects such as nurse robot design and control, active vehicle system design and control, 2 legged walking robot control. He has been reviewed more than 100 papers. He is also author of more than 140 journal and conference papers. He is currently supervisin more than 30 PhD and Msc students. His research area is consisted of neural network, control theory and applications, mobile and industrial robots, vehicle Dynamics and control.