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PREDICTIVE CONTROL DESIGN FOR LARGE SCALE SYSTEMS

机译:大型系统预测控制设计

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The design of model-based Generalised Predictive Controller (GPC) for large scale systems is reported. A two-level decentralised Kalman filter is devised using the MAP approach. An optimal co-ordination strategy is developed for this filtering solution. This filter provides an output predictor for the GPC control design formulation. A two-level optimisation strategy is then employed to decompose the global GPC problem with the input/output constraints. The GPC solution for each subprocess is independently found at the lower level. This solution is sent to a higher level to update the values of an optimal coordinator. This procedure is repeated until an optimal solution is found. Simulation results demonstrate the improvements achieved by using the technique.
机译:报道了大规模系统模型的广义预测控制器(GPC)的设计。使用地图方法设计了一个双层分散的卡尔曼滤波器。为该过滤解决方案开发了最佳协调策略。该滤波器为GPC控制设计配方提供了输出预测器。然后,使用两级优化策略来分解输入/输出约束的全局GPC问题。每个子过程的GPC解决方案独立地发现在较低级别。此解决方案被发送到更高级别以更新最佳协调器的值。重复此过程,直到找到最佳解决方案。仿真结果证明了通过使用该技术实现的改进。

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