Abstract
We propose a finite-horizon robust minimax tracking controller design method for time-varying continuous-time stochastic uncertain systems. The uncertainty in the system is characterized by a set of probability measures under which stochastic noises, driving the system, are defined. A minimax optimal tracking controller is derived from the solution of a risk-sensitive LQG control problem.
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