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For discrete-time linear time-invariant systems with input disturbances and constraints on inputs and states, we develop an algorithm to determine explicitly, as a function of the initial state, the solution to robust optimal control problems based on min-max optimization. We show that the optimal control sequence is a piecewise linear function of the initial state. Thus, when the optimal control...
This paper proposes a new approach to design a robust model predictive control (MPC) algorithm for LTI discrete time systems. By using a randomization technique, the optimal control problem embedded in the MPC scheme is solved for a finite number of realizations of model uncertainty and additive disturbances. Theoretical results in random convex programming (RCP) are used to show that the designed...
An approximation controller is developed to obtain an optimal control for nonlinear networked control systems (NCS) with time delay. In the approach only the non-linear compensating term, solution of a sequence of adjoint vector differential equations, is required iteration. By taking the finite iteration of non-linear compensating term of optimal solution sequence, a suboptimal control law for NCS...
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