Stochastic optimal control and estimation methods adapted to the noise characteristics of the sensorimotor system. (English) Zbl 1108.93082

In the paper some standard results of linear quadratic Gaussian optimal control and estimation theory are applied to sensorimotor systems. The author presents an extended noise model which incorporates control dependent, state dependent and internal estimation noise. The feedback control laws are restricted to the linear functions of state estimates obtained via unbiased nonadaptive linear filters. It leads to the recursive coordinate descent algorithm which ensures convergence of the optimal control-filter structure. The proposed methodology is illustrated by its application to the analysis of reaching movements. The convergence properties of the algorithm are discussed.


93E20 Optimal stochastic control
93E10 Estimation and detection in stochastic control theory
93E35 Stochastic learning and adaptive control
93C95 Application models in control theory
92C10 Biomechanics
93E25 Computational methods in stochastic control (MSC2010)
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