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OPTIMIZATION WITH QUADRATIC CONSTRAINT IN APPLICATION OF STRUCTURE DYNAMIC MODEL UPDATING 被引量:1
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作者 桂冰 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2005年第3期212-215,共4页
A model updating optimization algorithm under quadratic constraints is applied to structure dynamic model updating. The updating problems of structure models are turned into the optimization with a quadratic constrain... A model updating optimization algorithm under quadratic constraints is applied to structure dynamic model updating. The updating problems of structure models are turned into the optimization with a quadratic constraint. Numerical method is presented by using singular value decomposition and an example is given. Compared with the other method, the method is efficient and feasible. 展开更多
关键词 updating model quadratic constraint singular value decomposition
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Robust Fuzzy Tracking Control for Nonlinear Networked Control Systems with Integral Quadratic Constraints 被引量:5
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作者 Zhi-Sheng Chen Yong He Min Wu 《International Journal of Automation and computing》 EI 2010年第4期492-499,共8页
This paper investigates the robust tracking control problcm for a class of nonlinear networked control systems (NCSs) using the Takagi-Sugeno (T-S) fuzzy model approach. Based on a time-varying delay system transf... This paper investigates the robust tracking control problcm for a class of nonlinear networked control systems (NCSs) using the Takagi-Sugeno (T-S) fuzzy model approach. Based on a time-varying delay system transformed from the NCSs, an augmented Lyapunov function containing more useful information is constructed. A less conservative sufficient condition is established such that the closed-loop systems stability and time-domain integral quadratic constraints (IQCs) are satisfied while both time-varying network- induced delays and packet losses are taken into account. The fuzzy tracking controllers design scheme is derived in terms of linear matrix inequalities (LMIs) and parallel distributed compensation (PDC). Furthermore, robust stabilization criterion for nonlinear NCSs is given as an extension of the tracking control result. Finally, numerical simulations are provided to illustrate the effectiveness and merits of the proposed method. 展开更多
关键词 Nonlinear networked control system fuzzy model robust tracking integral quadratic constraint linear matrix inequality.
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ARBITRARILY HIGH-ORDER ENERGY-CONSERVING METHODS FOR HAMILTONIAN PROBLEMS WITH QUADRATIC HOLONOMIC CONSTRAINTS
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作者 Pierluigi Amodio Luigi Brugnano +1 位作者 Gianluca Frasca-Caccia Felice Iavernaro 《Journal of Computational Mathematics》 SCIE CSCD 2024年第4期1145-1171,共27页
In this paper,we define arbitrarily high-order energy-conserving methods for Hamilto-nian systems with quadratic holonomic constraints.The derivation of the methods is made within the so-called line integral framework... In this paper,we define arbitrarily high-order energy-conserving methods for Hamilto-nian systems with quadratic holonomic constraints.The derivation of the methods is made within the so-called line integral framework.Numerical tests to illustrate the theoretical findings are presented. 展开更多
关键词 Constrained Hamiltonian systems quadratic holonomic constraints Energy-conserving methods Line integral methods Hamiltonian Boundary Value Methods HB-VMs
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Modified Exact Jacobian Semidefinite Programming Relaxation for Celis-Dennis-Tapia Problem
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作者 赵馨 孔汕汕 《Journal of Donghua University(English Edition)》 CAS 2023年第1期96-104,共9页
A modified exact Jacobian semidefinite programming(SDP)relaxation method is proposed in this paper to solve the Celis-Dennis-Tapia(CDT)problem using the Jacobian matrix of objective and constraining polynomials.In the... A modified exact Jacobian semidefinite programming(SDP)relaxation method is proposed in this paper to solve the Celis-Dennis-Tapia(CDT)problem using the Jacobian matrix of objective and constraining polynomials.In the modified relaxation problem,the number of introduced constraints and the lowest relaxation order decreases significantly.At the same time,the finite convergence property is guaranteed.In addition,the proposed method can be applied to the quadratically constrained problem with two quadratic constraints.Moreover,the efficiency of the proposed method is verified by numerical experiments. 展开更多
关键词 Celis-Dennis-Tapia(CDT)problem quadratically constrained problem with two quadratic constraints semidefinite programming(SDP)relaxation method
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STABILITY MARGIN OF SYSTEMS WITH MIXED UNCERTAINTIES UNDER THE IQC DESCRIPTIONS
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作者 董海荣 耿志勇 +1 位作者 王金枝 黄琳 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2002年第11期1274-1281,共8页
Stability perturbation bounds problem for systems with mixed uncertainties is discussed. It is supposed that the linear part in the forward loop is of parametric uncertainties described by interval perturbation mode, ... Stability perturbation bounds problem for systems with mixed uncertainties is discussed. It is supposed that the linear part in the forward loop is of parametric uncertainties described by interval perturbation mode, and that the nonlinear part in the feedback loop is characterized by an integral quadratic constraint (IQC). The definition of stability margin under the interval perturbation mode is given by using the Minkowski functional. The infinite stability checking problem of the mixed uncertain system can be converted to finite or one dimensional stability checking for different structures of the IQC multipliers based on the concepts of biconvex and convex-concave junctions and their properties. The result is illustrated to be efficient through an example. 展开更多
关键词 system with mixed uncertainty perturbation margin integral quadratic constraint parametric uncertainty stability checking
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Missile autopilot design based on robust LPV control
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作者 Yuanchuan Shen Jianqiao Yu +1 位作者 Guanchen Luo Yuesong Mei 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2017年第3期536-545,共10页
This paper proposes an effective algorithm to work out the linear parameter-varying (LPV) framework autopilot for the air defense missile so as to simultaneously guarantee the closed-loop system properties globally an... This paper proposes an effective algorithm to work out the linear parameter-varying (LPV) framework autopilot for the air defense missile so as to simultaneously guarantee the closed-loop system properties globally and locally, which evidently reduces the number of unknown variables and hence increases the computational efficiency. The notion of 'robust quadratic stability' is inducted to meet the global properties, including the robust stability and robust performance, while the regional pole placement scheme together with the adoption of a model matching structure is involved to satisfy the dynamic performance, including limiting the 'fast poles'. In order to reduce the conservatism, the full block multiplier is employed to depict the properties, with all specifications generalized in integral quadratic constraint frame and finally transformed into linear matrix inequalities for tractable solutions through convex optimization. Simulation results validate the performance of the designed robust LPV autopilot and the proposed framework control method integrating with the full block multiplier approach and the regional pole placement scheme, and demonstrate the efficiency of the algorithm. An efficient algorithm for the air defense missile is proposed to satisfy the required global stability and local dynamical properties by a varying controller according to the flight conditions, and shows sufficient promise in the computational efficiency and the real-time performance of the missile-borne computer system. 展开更多
关键词 linear parameter-varying (LPV) full-block multiplier integral quadratic constraint regional pole placement linear matrix inequality
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Krein space approach to robust H_∞ filtering for linear uncertain systems
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作者 Jin Feng Fei Yu +2 位作者 Na Yang Pengyu Zhang Wei Gao 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2012年第4期596-602,共7页
A novel Krein space approach to robust H∞ filtering for linear uncertain systems is developed. The parameter uncertainty, entering into both states and measurement equations, satisfies an energy-type constraint. Then... A novel Krein space approach to robust H∞ filtering for linear uncertain systems is developed. The parameter uncertainty, entering into both states and measurement equations, satisfies an energy-type constraint. Then a Krein space approach is used to tackle the robust H∞ filtering problem. To this end, a new Krein space formal system is designed according to the original sum quadratic constraint (SQC) without introducing any nonzero factors into it and, consequently, the estimate recursion is obtained through the filter gain in Krein space. Finally, a numerical example is given to demonstrate the effectiveness of the proposed approach. 展开更多
关键词 linear uncertain system sum quadratic constraint(SQC) robust H∞ filtering Krein space linear estimation.
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A Quadratically Approximate Framework for Constrained Optimization,Global and Local Convergence 被引量:1
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作者 Jin Bao JIAN 《Acta Mathematica Sinica,English Series》 SCIE CSCD 2008年第5期771-788,共18页
This paper presents a quadratically approximate algorithm framework (QAAF) for solving general constrained optimization problems, which solves, at each iteration, a subproblem with quadratic objective function and q... This paper presents a quadratically approximate algorithm framework (QAAF) for solving general constrained optimization problems, which solves, at each iteration, a subproblem with quadratic objective function and quadratic equality together with inequality constraints. The global convergence of the algorithm framework is presented under the Mangasarian-Fromovitz constraint qualification (MFCQ), and the conditions for superlinear and quadratic convergence of the algorithm framework are given under the MFCQ, the constant rank constraint qualification (CRCQ) as well as the strong second-order sufficiency conditions (SSOSC). As an incidental result, the definition of an approximate KKT point is brought forward, and the global convergence of a sequence of approximate KKT points is analysed. 展开更多
关键词 constrained optimization quadratic approximation algorithm framework quadratic constraints global and local convergence
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Robustness analysis and distributed control of a networked system with time-varying delays
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作者 Zhike WANG Tong ZHOU 《Control Theory and Technology》 EI CSCD 2020年第3期293-306,共14页
This paper is concerned with the robustness analysis and distributed output feedback control of a networked system with uncertain time-varying communication delays.This system consists of a collection of linear time-i... This paper is concerned with the robustness analysis and distributed output feedback control of a networked system with uncertain time-varying communication delays.This system consists of a collection of linear time-invariant subsystems that are spatially interconnected via an arbitrary directed network.Using a dissipation inequality that incorporates dynamic hard lQCs(integral quadratic constraints)for the delay uncertainties,we derive some sufficient robustness conditions in the form of coupled linear matrix inequalities,in which the couplld parts reflect the interconnection structure of the system.We then provide a procedure to construct a distributed controller to ensure the robust stability of the closed-loop system and to achieve a prescribed lzgain performance.The effectiveness of the proposed approach is demonstrated by some numerical examples. 展开更多
关键词 Networked system time delay integral quadratic constraints(IQCs) robust stability distributed control
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Stable reinforcement learning with recurrent neural networks
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作者 James Nate KNIGHT Charles ANDERSON 《控制理论与应用(英文版)》 EI 2011年第3期410-420,共11页
In this paper,we present a technique for ensuring the stability of a large class of adaptively controlled systems.We combine IQC models of both the controlled system and the controller with a method of filtering contr... In this paper,we present a technique for ensuring the stability of a large class of adaptively controlled systems.We combine IQC models of both the controlled system and the controller with a method of filtering control parameter updates to ensure stable behavior of the controlled system under adaptation of the controller.We present a specific application to a system that uses recurrent neural networks adapted via reinforcement learning techniques.The work presented extends earlier works on stable reinforcement learning with neural networks.Specifically,we apply an improved IQC analysis for RNNs with time-varying weights and evaluate the approach on more complex control system. 展开更多
关键词 Stability analysis Integral quadratic constraint Recurrent neural network Reinforcement learning Linear matrix inequality
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