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题名: Nonlinear model predictive control with regulable computational cost
作者: He YQ(何玉庆) ; Han JD(韩建达)
作者部门: 机器人学研究室
关键词: Control Lyapunov functions ; nonlinear model predictive control ; input constraints
刊名: ASIAN JOURNAL OF CONTROL
ISSN号: 1561-8625
出版日期: 2012
卷号: 14, 期号:1, 页码:300-307
收录类别: SCI ; EI
产权排序: 1
摘要: Nonlinear model predictive control (NMPC) suffers from problems of closed loop instability and huge computational burden, which greatly limit its applications in real plants. In this paper, a new NMPC algorithm, whose stability is robust with respect to regulable computational cost, is presented. First, a new generalized pointwise min-norm (GPMN) control, as well as its analytic form considering a super-ball type input constraint, is given. Second, the GPMN controller is integrated into a normal NMPC algorithm as a structure of control input profile to be optimized, called GPMN enhanced NMPC (GPMN-ENMPC). Finally, a numerical example is presented and simulation results exhibit the advantage of the GPMN-ENMPC algorithm: computational cost can be regulated according to the computational resources with guaranteed stability.
语种: 英语
WOS记录号: WOS:000299468700028
WOS标题词: Science & Technology ; Technology
类目[WOS]: Automation & Control Systems
关键词[WOS]: STABILIZATION ; OPTIMALITY ; STABILITY
研究领域[WOS]: Automation & Control Systems
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内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/10029
Appears in Collections:机器人学研究室_期刊论文

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何玉庆; 韩建达.Nonlinear model predictive control with regulable computational cost,ASIAN JOURNAL OF CONTROL,2012,14(1):300-307
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