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Broadcast Feedback of Stochastic Cellular Actuators Inspired by Biological Muscle Control

Graduate School of Information Science, Nara Institute of Science and Technology, Nara, 630-0192 uedajun{at}mit.edu, d'Arbeloff Laboratory for Information Systems and Technology, Department of Mechanical Engineering Massachusetts Institute of Technology, Cambridge MA 02139

Lael Odhner

d'Arbeloff Laboratory for Information Systems and Technology, Department of Mechanical Engineering Massachusetts Institute of Technology, Cambridge MA 02139 {lael, asada}@mit.edu

H. Harry Asada

d'Arbeloff Laboratory for Information Systems and Technology, Department of Mechanical Engineering Massachusetts Institute of Technology, Cambridge MA 02139 {lael, asada}@mit.edu

This paper presents a broadcast feedback approach to the distributed stochastic control of an actuator system consisting of many cellular units. This control architecture was inspired by skeletal muscles comprising a vast number of tiny functional units, called sarcomeres. The output of the actuator system is an aggregate e fect of numerous cellular units, each taking a bistable ON—OFF state. A central controller "broadcasts" the error between the aggregate output and a reference input. Rather than ordering the individual units to take specific states, the central controller merely broadcasts the overall error signal to all the cellular units uniformly. In turn each cellular unit makes a stochastic decision with a state transition probability, which is modulated in relation to the broadcasted error. Stochastic properties of both open-loop and closed-loop control systems are analyzed. Stability conditions of the broadcast feedback system are obtained by using a stochastic Lyapunov function. The proposed method is simulated for an artificial cellular actuator, consisting of many segments of smart actuator material. Theoretical results are verified through simulation. It is demonstrated that, even in the absence of deterministic coordination, the ensemble of the cellular units can track a given trajectory stably and robustly.

Key Words: smart actuators • broadcast • stochastic stability • Markov chain • cellular control system • distributed robot systems • muscle

The International Journal of Robotics Research, Vol. 26, No. 11-12, 1251-1265 (2007)
DOI: 10.1177/0278364907082443


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