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IEEE International Conference on Communications (ICC)

作者： Sun, Cong Jorswieck, Eduard Chinese Acad Sci State Key Lab Sci & Engn Comp ICMSEC Acad Math & Syst Sci Beijing Peoples R China Tech Univ Dresden Commun Lab Commun Theory Dresden Germany

ISBN: (纸本)9781467331227

A multiple-antenna amplify-and-forward (AF) two-hop interference network with multiple links and multiple relays is considered. We optimize transmit precoders, receive decoders and relay AF matrices to maximize the achievable sum rate. Two constraint sets are discussed: first, individual per user and total relay sum power constraints. We propose an algorithm to maximize the total signal to total interference plus noise ratio (TSTINR). Second, this algorithm is extended to individual user and individual relay fixed transmit power constraints. Additionally, we derive algorithms for the total leakage interference plus noise (TLIN) minimization and the weighted minimum mean square error (WMMSE) approach to sum rate maximization. Interestingly, our simulations show that, for both constraint sets, our TSTINR algorithm outperforms the TLIN algorithm generally and outperforms WMMSE in medium to high Signal-to-Noise-Ratio (SNR) scenarios, while TSTINR and TLIN requires less computing time than WMMSE generally.

关键词： MIMO relay networks individual power constraints alternating iteration sequential quadratic programming

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Flight Control System Design for a Flying-Wing Aircraft

Flight Control System Design for a Flying-Wing Aircraft

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IEEE International Conference of Region 10 (TENCON)

作者： Xu Mingxing Zhu Xiaoping Zhou Zhou Zhang Bo Northwestern Polytech Univ Sci & Technol UAV Lab Xian 710072 Peoples R China Northwestern Polytech Univ UAV Res Inst Xian Peoples R China

ISBN: (纸本)9781479928255;9781479928279

In this paper, the flight control system of a flying-wing aircraft is designed. Significant dynamic nonlinearity and control redundancy are main problems for a flying-wing aircraft. As the over-actuated system and dynamic nonlinearity, the flight control system is divided into two parts: control laws and control allocation. Nonlinear dynamic inversion is used to design the control laws to generate control moments as the commands of control allocator. Because the relationship between moment and effector deflection is nonlinear, the nonlinear control allocation based on SQP is designed. The nonlinear control allocation can reduce the errors between commands and responses of control moments.

关键词： nonlinear dynamic inversion nonlinear control allocation sequential quadratic programming flying-wing aircraft

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Fast Intercept Trajectory Optimization for Multi-stage Air Defense Missile Using Hybrid Algorithm

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Procedia Engineering 2013年 67卷 447-456页

作者： F.B. Wang C.H. Dong School of Aeronautics Science and Engineering Beihang University Beijing 100191 China School of Astronautics Beihang University Beijing 100191 China

A hybridalgorithmconsists of particle swarm optimization (PSO) and sequential quadratic programming (SQP) is proposed, and appliesto solve the optimal trajectory with maximizing the terminal velocity at predict impact point (PIP) for multi-stage air defense missile. This hybrid optimization approach combines the advantages of PSO as a global optimizer and complemented with SQP to find the accurate local optima. A simple plane motion equation of multi-stage air defense is establishedwith respect to trajectory referenceframe firstly, and restrictions on path parameters and terminal conditions are *** task with given PIP, intercept trajectory optimization problem is a classical continuous optimal control problem. Then control of angle of attack (AOA) is parameterized according to empirical equations so that converting the continuousoptimal control problem into a parameters optimization ***, the hybrid algorithm is employed to solve this parameters optimization problem effectively with high accuracy. Several simulations and comparative cases are carried out, simulation results illustrate the hybrid method is feasible and it can fast converges to the optimal solution. Comparison results with the conventional optimization algorithm confirm that the proposed algorithm is more accurate and effective and more suited for missile trajectory profile optimization.

关键词： Trajectory optimization Air defense missile Hybrid algorithm Particle Swarm Optimization sequential quadratic programming

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Gradient-Based Artificial Bee Colony for Damping Controllers Design

Gradient-Based Artificial Bee Colony for Damping Controllers...

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IEEE International Power Engineering and Optimization Conference

作者： Mahdiyeh Eslami Hussain Shareef Azah Mohamed Mohammad Khajehzadeh Department of Electrical Electronic and Systems Engineering National University of Malaysia Department of Civil Engineering Anar Branch Islamic Azad University

ISBN: (纸本)9781467350723

A novel optimization algorithm by combining the artificial bee colony (ABC) algorithm and the sequential quadratic programming (SQP), that is the gradient based ABC algorithm, is presented to resolve the problems of global optimization and inter-area oscillations damping in power system. The proposed algorithm merges the global exploration ability of the artificial bee colony to converge quickly to a near optimum resolution, and the correct local exploitation capacity of the sequential quadratic programming to accelerate the search process and discover a correct solution. To show the feasibility and efficiency of the new method, numerical result is investigated on the New England system by tuning a power system stabilizer and a controller for the static VAR compensator. The proposed gradient based ABC algorithm is compared with ABC. The simulations studies demonstrate that the proposed algorithm based designed damping controllers perform better than controller designed by ABC.

关键词： Controllers activity based costing bee colonies Search process sequential quadratic programming Bee absorption of shock Power system stability New England Optimization algorithms Global optimization power systems

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A hybrid CPSO-SQP method for economic dispatch considering the valve-point effects

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ENERGY CONVERSION AND MANAGEMENT 2012年第1期53卷 175-181页

作者： Cai, Jiejin Li, Qiong Li, Lixiang Peng, Haipeng Yang, Yixian Sun Yat Sen Univ Sch Phys & Engn Guangzhou 510275 Guangdong Peoples R China Sun Yat Sen Univ Sino French Inst Nucl Engn & Technol Guangzhou 510275 Guangdong Peoples R China S China Univ Technol State Key Lab Subtrop Bldg Sci Guangzhou 510640 Peoples R China Beijing Univ Posts & Telecommun Informat Secur Ctr Beijing 100876 Peoples R China

This paper developed a new method for solving the economic dispatch (ED) problems considering the valve-point effects in power systems. The method is based on a hybrid algorithm consisting of chaotic particle swarm optimization (CPSO) algorithm and sequential quadratic programming (SQP) techniques. The CPSO is the main optimizer of the algorithm and the SQP is used to fine tune its results to improve the solution. The proposed method was applied to three different cases of power systems. The economic effect, solution quality, convergence property and computation efficiency of the proposed method have been explored through the comparison with the existing techniques for the ED problems considering the valve-point effects. The simulation results demonstrate the applicability and effectiveness of the proposed algorithm to the practical ED problems. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Economic dispatch Chaotic particle swarm optimization sequential quadratic programming Evolutionary algorithm Power system

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A primal-dual augmented Lagrangian

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2012年第1期51卷 1-25页

作者： Gill, Philip E. Robinson, Daniel P. Univ Oxford Math Inst Oxford OX1 3LB England Univ Calif San Diego Dept Math San Diego CA 92093 USA

Nonlinearly constrained optimization problems can be solved by minimizing a sequence of simpler unconstrained or linearly constrained subproblems. In this paper, we consider the formulation of subproblems in which the objective function is a generalization of the Hestenes-Powell augmented Lagrangian function. The main feature of the generalized function is that it is minimized with respect to both the primal and the dual variables simultaneously. The benefits of this approach include: (i) the ability to control the quality of the dual variables during the solution of the subproblem;(ii) the availability of improved dual estimates on early termination of the subproblem;and (iii) the ability to regularize the subproblem by imposing explicit bounds on the dual variables. We propose two primal-dual variants of conventional primal methods: a primal-dual bound constrained Lagrangian (pdBCL) method and a primal-dual a"" (1) linearly constrained Lagrangian (pda"" (1)LCL) method. Finally, a new sequential quadratic programming (pdSQP) method is proposed that uses the primal-dual augmented Lagrangian as a merit function.

关键词： Nonlinear programming Nonlinear constraints Augmented Lagrangian methods Bound constrained Lagrangian methods Linearly constrained Lagrangian methods sequential quadratic programming Primal-dual methods

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Variational Model for Optimization of Finite-Burn Escape Trajectories Using a Direct Method

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2012年第2期35卷 598-608页

作者： Ocampo, Cesar A. Mathur, Ravishankar Univ Texas Austin Dept Aerosp Engn & Engn Mech Austin TX 78712 USA

A variational model is used to obtain the necessary gradient information for a multiple finite-burn trajectory problem. The augmented state vector includes position, velocity, mass, and control variables such as thrust magnitude, and the variables that describe the time evolution of the thrust direction unit vector. The augmented state vector and its associated state equation are used in the variational model to formulate analytical expressions for the gradients of the problem functions with respect to the problem variables. A general finite-burn trajectory problem is formulated for an inertially fixed thrust vector steering model and a fixed-plane linearly varying thrust vector steering model that constrains the thrust vector to be normal to a rotation axis, which itself is part of the control variable set. Both steering models are used in the optimization of a three-finite-burn lunar-escape-trajectory example, using a direct optimization method with explicit numerical integration. The performance of the optimization procedure is compared for both thrust vector steering models, using variational gradients and standard numerical finite difference gradients. The ability to obtain the most accurate gradient information for the direct optimization of simple finite-burn thrust steering models is a motivation of the current study.

关键词： Exhaust Velocity Hohmann Transfer Propellant sequential quadratic programming Finite Difference Method Earth Trajectory Optimization Computing Crew Exploration Vehicle Numerical Integration

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AN SQP TRUST REGION METHOD FOR SOLVING THE DISCRETE-TIME LINEAR quadratic CONTROL PROBLEM

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INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE 2012年第2期22卷 353-363页

作者： Mostafa, El-Sayed M. E. Alexandria Univ Moharam Bey Fac Sci Dept Math Alexandria 21511 Egypt

In this paper, a sequential quadratic programming method combined with a trust region globalization strategy is analyzed and studied for solving a certain nonlinear constrained optimization problem with matrix variables. The optimization problem is derived from the infinite-horizon linear quadratic control problem for discrete-time systems when a complete set of state variables is not available. Moreover, a parametrization approach is introduced that does not require starting a feasible solution to initiate the proposed SQP trust region method. To demonstrate the effectiveness of the method, some numerical results are presented in detail.

关键词： output feedback control design sequential quadratic programming trust region method

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A NEIGHBORING EXTREMAL SOLUTION FOR OPTIMAL SWITCHED IMPULSIVE CONTROL PROBLEMS WITH LARGE PERTURBATIONS

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INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL 2012年第9期8卷 6235-6257页

作者： Jiang, Canghua Teo, Kok Lay Loxton, Ryan Duan, Guang-Ren Harbin Inst Technol Ctr Control Theory & Guidance Technol Harbin 150001 Peoples R China Curtin Univ Technol Dept Math & Stat Perth WA 6845 Australia

This paper presents an approach to compute the neighboring extremal solution for an optimal switched impulsive control problem with a pre-specified sequence of modes and a large perturbation in the initial state. The decision variables - the subsystem switching times and the control parameters - are subject to inequality constraints. Since the active status of these inequality constraints may change under the large perturbation, we add fractions of the initial perturbation separately such that the active status of the inequality constraints is invariant during each step, and compute the neighboring extremal solution iteratively by solving a sequence of quadratic programming problems. First, we compute a correction direction for the control in the perturbed system through an extended backward sweep technique. Then, we compute the maximal step size in this direction and derive the solution iteratively by using a revised active set strategy. An example problem involving a shrimp harvesting operation demonstrates that our solution approach is faster than the sequential quadratic programming approach.

关键词： Optimal control Neighboring extremal Impulsive control Switched system sequential quadratic programming Active set strategy

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Nonlinear Model Predictive Control of a Distillation Column Using Wavenet Based Hammerstein Model

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ENGINEERING LETTERS 2012年第4期20卷 330-335页

作者： Ramesh, K. Hisyam, A. Aziz, N. Shukor, S. R. Abd Univ Malaysia Pahang Fac Chem & Nat Resources Engn Proc Syst Engn Grp Kuantan 26300 Pahang Malaysia Univ Sains Malaysia Seri Ampangan Sch Chem Engn Engn Campus Nibong Tebal 14300 Pulau Pinang Malaysia

Distillation columns are fairly complex multivariable systems and needs to be controlled close to optimum operating conditions because of economic incentives. Nonlinear Model Predictive Control (NMPC) scheme is one of the best options to be explored for proper control of distillation columns. In the present work, a new wavenet based Hammerstein model NMPC has been developed to control distillation column. An experimentally validated equilibrium model was used as plant model in nonlinear system identification and in NMPC. Two multiple-input-single-output (MISO) wavenet based Hammerstein models are developed to model the dynamics of the distillation column. The nonlinear model parameters were estimated using iterative predictionerror minimization method. The Unscented Kalman Filter (UKF) was used to estimate the state variables in NMPC and the NLP problem was solved using sequential quadratic programming (SQP) method. The closed loop control studies have indicated that the performance of developed NMPC scheme was good in controlling the distillation column.

关键词： Distillation column Nonlinear model predictive control sequential quadratic programming Wavenet based Hammerstein model

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