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陈虹, CHEN Hong, LIU Zhi-yuan, XIE Xiao-hua
控制与决策,2001,16(4):385~391,-0001,():
-1年11月30日
模型预测控制的一个主要优点是能显式并优化处理控制量和状态量的约束。为此,主要围绕非线性预测控制的算法、稳定性和鲁棒性、对偶问题和滚动时域估计的最新研究成果进行综述,并阐述了理论与应用方面有待进一步研究的几个主要问题。
非线性预测控制, 约束, 稳定性, 鲁棒性, 流动时域估计
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陈虹, Chen Hong, Zhao Guijun, Sun Pengyuan & Guo Konghui
汽车工程,2003,25(1):1~6,-0001,():
-1年11月30日
以2自由度1/4车模型为例在鲁棒控制理论的统一框架下讨论H2和H∞主动悬架的设计,并采用结构奇异值法和加权最坏RMS增益法对其鲁棒性能进行分析和比较。
主动悬架,, H2和H∞控制,, 频率加权,, 鲁棒性能
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【期刊论文】Application of Constrained H∞ Control to Active Suspension Systems on Half-Car Models
陈虹, H. Chen, Z.-Y. Liu, P.-Y. Sun
SEPTEMBER 2005, Vol. 127,-0001,():
-1年11月30日
This paper formulates the active suspension control problem as disturbance attenuation problem with output and control constraints. The H∞ performance is used to measure ride comfort such that more general road disturbances can be considered, while timedomain hard constraints are captured using the concept of reachable sets and state-space ellipsoids. Hence, conflicting requirements are specified separately and handled in a nature way. In the framework of Linear Matrix Inequality (LMI) optimization, constrained H∞ active suspensions are designed on half-car models with and without considering actuator dynamics. Analysis and simulation results show a promising improvement on ride comfort, while keeping suspension strokes and control inputs within bounds and ensuring a firm contact of wheels to road.
Active Suspensions,, Time-Domain Constraints,, LMI Optimization,, Actuator Dynamics
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陈虹, H. Chen*, †, and F. Allgower‡§
J. Proc. Cont. Vol. 8, Nos. 5-6, pp. 475-485, 1998,-0001,():
-1年11月30日
We introduce in this paper a nonlinear model predictive control scheme for open-loop stable systems subject to input and state constraints. Closed-loop stability is guaranteed by an appropriate choice of the finite prediction horizon, independent of the specification of the desired control performance. In addition, this control scheme is likely to allow 'real time' implementation, because of its computational attractiveness. The theoretical results are demonstrated and discussed with a CSTR control application.
nonlinear predictive control, constraints, stability, terminal conditions
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