Stochastic Control of Population Dynamics Using Kalman Filtering with Applications to Artificial Muscle Recruitment

This paper addresses a problem in distributed control: given a large number of identical hybrid-state agents, control the ensemble behavior of the agents assuming that only limited information is available about the agents' states. This process has relevance to a number of biologically-inspired...

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Bibliographic Details
Main Authors: Odhner, Lael U. (Contributor), Asada, Harry (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Mechanical Engineering (Contributor), Asada (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers, 2010-11-23T20:19:58Z.
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Online Access:Get fulltext
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100 1 0 |a Odhner, Lael U.  |e author 
100 1 0 |a Massachusetts Institute of Technology. Department of Mechanical Engineering  |e contributor 
100 1 0 |a Asada, Harry  |e contributor 
100 1 0 |a Odhner, Lael U.  |e contributor 
100 1 0 |a Asada  |e contributor 
700 1 0 |a Asada, Harry  |e author 
245 0 0 |a Stochastic Control of Population Dynamics Using Kalman Filtering with Applications to Artificial Muscle Recruitment 
260 |b Institute of Electrical and Electronics Engineers,   |c 2010-11-23T20:19:58Z. 
856 |z Get fulltext  |u http://hdl.handle.net/1721.1/60038 
520 |a This paper addresses a problem in distributed control: given a large number of identical hybrid-state agents, control the ensemble behavior of the agents assuming that only limited information is available about the agents' states. This process has relevance to a number of biologically-inspired control problems, such as motor recruitment. In this paper, we describe a stochastic control policy capable of achieving convergent control of the distribution of an ensemble of finite state agents in this way. Using techniques developed for the observation of biological population dynamics, we show that it is possible to observe the state distribution of agents under our control policy using a Kalman filter. Look-ahead control laws based on the Kalman filter estimates are used to achieve a high degree of stability and robustness in systems exhibiting large time delays. An example of control over a hybrid-state, recruitment-like controller for an artificial muscle is presented. 
546 |a en_US 
655 7 |a Article 
773 |t Proceedings of the American Control Conference, 2009