This paper presents an iterative Linear-Quadratic-Gaussian method for locally-optimal control and estimation of non-linear stochastic systems. The new method constructs an affine feedback control law, obtained by minimizing a novel quadratic approximation to the optimal cost-to-go function, and a non-adaptive estimator optimized with respect to the current control law. The control law and filter are iteratively improved until convergence. The performance of the algorithm is illustrated on a complex biomechanical control problem involving a stochastic model of the human arm.
CITATION STYLE
Li, W., & Todorov, E. (2007). Iterative linearization methods for approximately optimal control and estimation of non-linear stochastic system. International Journal of Control, 80(9), 1439–1453. https://doi.org/10.1080/00207170701364913
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