首页> 外文期刊>IEE Proceedings. Part D >Numerical robustness and efficiency of generalised predictive control algorithms with guaranteed stability
【24h】

Numerical robustness and efficiency of generalised predictive control algorithms with guaranteed stability

机译:保证稳定性的广义预测控制算法的数值鲁棒性和效率

获取原文
获取原文并翻译 | 示例
           

摘要

Three recent publications proposed modifications to the generalised predictive control algorithm which guarantee closed-loop stability. Of these the first two adopt the same philosophy, namely that of constrained receding horizon predictive control (CRHPC), whereas the third adopts a stable generalised predictive control (SGPC) strategy by first stabilising then controlling the plant. The purpose of the paper is to examine the relationship between CRHPC and SGPC. It is shown that, theoretically, the two approaches are equivalent, but is is also shown that CRHPC could be subject to significant numerical instability problems. Two alternative improved implementations of CRHPC are proposed, but SGPC is shown to have the advantage in terms of numerical stability and computational efficiency.
机译:最近的三篇出版物提出了对广义预测控制算法的修改,以保证闭环稳定性。在这两个中,前两个采用相同的原理,即受约束的后备水平预测控制(CRHPC),而第三个则采用稳定的广义预测控制(SGPC)策略,即先稳定然后控制植物。本文的目的是研究CRHPC和SGPC之间的关系。结果表明,理论上,这两种方法是等效的,但也表明,CRHPC可能会遇到严重的数值不稳定问题。提出了CRHPC的两个替代的改进实现,但是SGPC在数值稳定性和计算效率方面具有优势。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号