Determining the optimal manipulated action for large scale model predictive control formulations requires significant computational overhead. It has been demonstrated that the offline, explicit solution provided by multiparametric programming has the capacity to greatly improve the online computational performance of MPC strategies. For large scale problems, developing and deploying the full multiparametric solution remains an open challenge. In this work, a partial multiparametric solution is utilized to improve the initialization procedure for a hot start strategy. The hot start strategy provides an improved technique for determining the optimal solution of large scale MPC formulations, and the partial multiparametric solution ensures the initialization is suitable under varying conditions. The efficacy of the proposed strategy is verified on randomly generated large scale MPC problems.

为大型模型预测控制公式确定最佳操作需要大量的计算开销。已经证明，多参数编程提供的离线显式解决方案具有极大地提高MPC策略的在线计算性能的能力。对于大规模问题，开发和部署完整的多参数解决方案仍然是一个挑战。在这项工作中，使用了部分多参数解决方案来改善热启动策略的初始化过程。热启动策略为确定大规模MPC配方的最佳解决方案提供了一种改进的技术，部分多参数解决方案可确保在各种条件下进行初始化都是合适的。