Finite horizon guaranteed cost for nonlinear quadratic systems

In this paper we consider the optimal control problem for the class of discrete-time nonlinear quadratic systems. More specifically, we focus on the design problem of a state feedback controller that guarantees a certain bound to a finite horizon quadratic cost function, whenever the state trajectories start from a prescribed set of initial conditions. The controller design requires the solution of a convex optimization problem involving Linear Matrix Inequalities (LMIs), which can be efficiently solved via available optimization algorithms. Finally, the proposed design methodology is illustrated via an example concerning the Integrated Pest Management (IPM).