摘要：AbstractWe present the application of an eigenvalue decomposition for the solution of the optimal control problem in model predictive control (MPC). This approach can be used as an alternative to the Riccati recursion that occurs within interior-point solvers, which are used to compute the solution of the optimization problem in constrained MPC. We first demonstrate that a known method applied to the finite-horizon linear quadratic regulator (LQR) for free-final state can be extended to the LQ tracking problem. Likewise, the receding-horizon idea is implemented on these two optimal control problems. In addition, the implications for online implementation are discussed.
关键词：KeywordsOptimal ControlHamiltonian MatrixPredictive ControlOptimization AlgorithmsOn-line Control
