The project will develop an understanding of the mechanism of animal locomotion from biological observations at the neuronal level, hypothesize the knowledge as engineering principles for feedback control design, and establish a systematic procedure for designing neurodynamic controllers to achieve optimally efficient autonomous locomotion. A simple yet accuratemathematical model for neuronal dynamics is developed first from a control perspective. Lyapunov-based methods will then be employed to analyse the oscillation properties of neuronal circuits to drive mechanical systems for locomotion. A prototype mechanical rectifier is used to experimentally validate the design principles to be developed for locomotion control.
The next technological revolution seems to rely on our understanding of complex biological systems. Such understanding would enable us to develop a completely new kind of robust, adaptive, and autonomous machines. The intellectual merit of this project is the basic understanding of the mechanism underlying such sophistication, through formalization of biological knowledge on animal locomotion in terms of engineering language of feedback control. The impacts of this research include innovations in a variety of fields. Realizations of new type of robotic locomotion systems for space explorations would be a direct application. Physiological control of the heart beat profile for stabilization of defective heart may be another application.
