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丁宝苍, BaoCang Ding?, , HeXu Sun, PengYang
Automatica 42(2006)503-508,-0001,():
-1年11月30日
This paper further studies stabilization of nonlinear systems represented by a Takagi–Sugeno (T-S) discrete fuzzy model. By extending a nonquadratic Lyapunov function and applying a nonparallel distributed compensation (non-PDC) law, a new stabilization conclusion is presented that is a generalization of some previous results in the literature. The new conclusion under a special situation is also suitable for a PDC law, which presents to be more relaxed than some existing results. An example is provided to demonstrate the effectiveness of the new conclusions.
T-S fuzzy systems, Parameter-dependent Lyapunov function, Parallel distributed compensation, Nonquadratic Lyapunov function
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丁宝苍, Baocang Dinga, ?, Yugeng Xib, Marcin T. Cychowskic, Thomas O’Mahonyc
Automatica 44(2008)258– 264,-0001,():
-1年11月30日
This paper addresses the synthesis approach for output feedback robust model predictive control for systems with polytopic description, bounded state disturbance and measurement noise. Off-line, it calculates a sequence of output feedback laws based on the state estimators, by solving linear matrix inequality (LMI) optimization problems. On-line, at each sampling time, it chooses an appropriate output feedback law from this sequence.The primary contribution is to present a rigorous method to guarantee satisfaction of input/state constraints. A numerical example is given to illustrate the effectiveness of the controller.
Robust model predictive control, Output feedback, State estimator, Constraint
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丁宝苍, Baocang Ding*
,-0001,():
-1年11月30日
This article addresses the robust model predictive control (MPC) for systems with polytopic uncertaintydescription. In the case of multiple state delays, some results are given in the previous works. However, previousworks are not well established for input-delay systems. This article proposes new approaches that can effectivelyhandle not only the input-delay, but also the multiple delayed input. For the time-delay system, a general MPCsolution is based on the use of augmented delay-free state-space description, which can be computationallyexpensive. Hence, in general there are simplified formulations based on the time-delay description, which can beapplied in different situations. This article proposes three simplified formulations, with the first incorporating aprevious result as a special case, the second being a solution for a unique class of systems and the third being amore general solution without special assumptions on the plant. Numerical examples illustrate the effectivenessof the proposed approaches.
model predictive control, uncertain systems, time-delay systems, state feedback, Lyapunov method
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【期刊论文】Improving off-line approach to robustMPCbased-on nominalperformance cost
丁宝苍, BaoCang Dinga, ?, YuGeng Xib, Marcin T. Cychowskic, Thomas O’Mahonyc
Automatica 43(2007)158-163,-0001,():
-1年11月30日
This paper gives two alternative off-line synthesis approaches to robust model predictive control (RMPC) for systems with polytopic description. In each approach, a sequence of explicit control laws that correspond to a sequence of nested asymptotically invariant ellipsoids are constructed off-line. In order to accommodate a wider class of systems, nominal performance cost is chosen to substitute the "worst-case" one in an existing technique. In the design of control law for a larger ellipsoid, the second approach further incorporates the knowledge of control laws associated with all smaller ellipsoids, so as to further improve feasibility and optimality. The effectiveness of the alternative approaches is illustrated by a simulation example.
Robust model predictive control, Off-line method, Nominal performance cost, Asymptotically invariant ellipsoid, Linear matrix inequality
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【期刊论文】New formulation of robust MPC by incorporating off-lineapproach with on-line optimization
丁宝苍, BAOCANG DINGy and BIAO HUANG*z
,-0001,():
-1年11月30日
This article addresses robust model predictive control (MPC) for systems with polytopicdescription. An existing off-line robust MPC enables the on-line computation as simple assearching a state feedback gain among the look-up table. We consider enlarging the region ofattraction of the off-line MPC by incorporating free perturbation items. First, a largerellipsoidal region of attraction is off-line constructed, in which a simple optimization problemis solved on-line. Then, outside of this larger ellipsoid, a standard robust MPC is solved onlinesuch that the overall region of attraction can be rendered as a much larger nonellipsoidalone. The proposed approach possesses all the merits of the off-line MPC and greatly enlargesthe region of attraction. A simulation example is given to demonstrate the effectiveness.
Robust model predictive control, Off-line model predictive control, Region of attraction, Free perturbation item, Vertex perturbation item
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