Stable and robust LQR design via scenario approach

Linear Quadratic Regulator (LQR) design is one of the most classical optimal control problems, whose well-known solution an input sequence expressed as a state-feedback. In this work, finite-horizon and discrete-time LQR solved under stability constraints uncertain system dynamics. The resulting feedback controller balances cost value closed-loop stability. Robustness modeled using scenario approach, without requiring any probabilistic description uncertainty in matrices. new methods are tested compared on Leslie growth model, where we population size while minimizing suitable function.