
Linear Quadratic Gaussian (LQG) systems are well-understood and methods to minimize the expected cost are readily available. Less is known about the statistical properties of the resulting cost function. The contribution of this paper is a set of analytic expressions for the mean and variance of the LQG cost function. These expressions are derived using two different methods, one using solutions to Lyapunov equations and the other using only matrix exponentials. Both the discounted and the non-discounted cost function are considered, as well as the finite-time and the infinite-time cost function. The derived expressions are successfully applied to an example system to reduce the probability of the cost exceeding a given threshold.
linear systems, Lyapunov equation, matrix algebra, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control, Stochastic ordinary differential equations (aspects of stochastic analysis), Linear systems in control theory, linear quadratic regulators, Linear-quadratic optimal control problems, probability density function, FOS: Electrical engineering, electronic engineering, information engineering, Optimal stochastic control, LQG control
linear systems, Lyapunov equation, matrix algebra, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control, Stochastic ordinary differential equations (aspects of stochastic analysis), Linear systems in control theory, linear quadratic regulators, Linear-quadratic optimal control problems, probability density function, FOS: Electrical engineering, electronic engineering, information engineering, Optimal stochastic control, LQG control
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