Advanced Control of Wheeled Inverted Pendulum Systems

Mathematical Preliminaries.- Modeling of the MWIP System.- Path Planning and Motion Generation.- Linear Control Methods.- Nonlinear Control Methods.- Model-reference Adaptive Control.- Model-free Intelligent Control.- Learning Impedance Control.- Conclusions and Perspectives.

Zhijun Li is an Associate Professor with the Department of Automation, Shanghai Jiaotong University. He received the Dr Eng Degree in mechatronics, Shanghai Jiao Tong University, PR China, in 2002. From 2003 to 2005, he was a postdoctoral fellow in the Department of Mechanical Engineering and Intelligent systems of The University of Electro-Communications, Tokyo, Japan. From 2005 to 2006, he was a research fellow in the Department of Electrical and Computer Engineering, National University of Singapore, and Nanyang Technological University, Singapore. Currently, he is an associate professor in the Department of Automation, Shanghai Jiao Tong University, PR China. Dr. Li is a senior member of the IEEE and his current research interests are adaptive/robust control, mobile manipulators, nonholonomic systems, etc.
Chenguang Yang obtained the Bachelor's degree in Measurement and Control Instrument and Technology at the Northwestern Polytechnical University in 2001 and the PhD degree in Control Theory at the National University of Singapore in 2010. From 2005 to 2009, he was working on adaptive/intelligent controllers for highly uncertain systems. In 2008, he worked for the TechX Challenge Urban Mobile Robot Competition organized by DSTA, Singapore, which is equivalent of the DARPA Grand Challenge in US. Together with teammates, he has developed a fully autonomous robot capable of climbing stairs, recognizing and operating an elevator, and navigating and searching for given targets in an unknown environment. From 2009 until 2010 he was with the Human Robotics Group in Imperial College London working on modeling of human neural-muscular control and development of robot control of human motor behavior. In connection with this he has developed a human-mimetic force- and impedance-adaptation algorithm for robots performing both stable and unstable tasks. Dr. Yang's current research interests are in the fields of intelligent robotic control, nonlinearcontrol and human-robot