Abstract-Several recent techniques from hybrid and optimal control are evaluated on a power electronics benchmark problem. The benchmark involves a number of practically interesting operating scenarios for a fixed-frequency step-up dc-dc converter. The specifications are defined such that good performance can only be obtained if the switched and nonlinear nature of the problem is respected during the design phase.
Abstract-We propose a new algorithm for feedback nonlinear synthesis. The algorithm computes suboptimal solutions, with bounds on suboptimality, to the Hamilton-Jacobi-Bellman equation. For systems that are modeled with polynomials the computations can be done efficiently via semidefinite programming. To illustrate the strength of the proposed method, we compute smooth stabilizing feedback controllers for several problems.
In this paper an alternative approach to model predictive control is presented. In traditional MPC a finite horizon open loop optimal control problem is solved in each sampling instance. When uncertainties such as computational delays are present, one can encounter problems. We propose to parametrize the control sequence in each sampling instant in terms of a linear feedback controller, i.e. in each sample a dynamic feedback compensator is computed. Thus, if computational delays are present the control system runs in closed loop, decreasing the need for ad hoc solutions used in traditional MPC.
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