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Variational Equations for a Generalized Spacecraft Trajectory Model

JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2010年第5期33卷 1615-1622页

作者： Ocampo, Cesar Munoz, Jean-Philippe Univ Texas Austin Dept Aerosp Engn & Engn Mech Austin TX 78712 USA

Linear perturbation theory is used to develop the variational equations needed to determine the sensitivities of the state at some final time with respect to all of the independent variables associated with a spacecraft trajectory model that is general enough for most applications of interest. The state vector is an augmented vector that includes the position, velocity, mass, and all other control-related variables, such as thrust magnitude and direction. The force model is general and the trajectory can have any number of impulsive and/or finite burn maneuvers. The gradient expressions depend, in part, on the system state transition matrix associated with the given state and its corresponding equations of motion. As an example, the procedure developed is applied to the numerical optimization of a multi-impulse escape trajectory from the moon.

关键词： Interplanetary Trajectories sequential quadratic programming Periapsis Numerical Optimization Parking Orbit Earth Finite Difference Approximation Perturbation Theory Exhaust Velocity Optimal Control

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Hybrid of comprehensive learning particle swarm optimization and SQP algorithm for large scale economic load dispatch optimization of power system

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Science China(Information Sciences) 2010年第8期53卷 1566-1573页

作者： WANG Yu , LI Bin & YUAN Bo Department of Electronic Science and Technology, School of Information Science and Technology, University of Science and Technology of China, Hefei 230027, China 1. Department of Electronic Science and Technology School of Information Science and Technology University of Science and Technology of China Hefei 230027 China

Economic load dispatch (ELD) is an important optimization task in power systems. In the previous works, various researchers attempted to address this problem by both mathmatical and heuristic optimization algorithms. However, there are still two practically important issues that have not attracted sufficient attention: 1) the stability of these algorithms cannot be effectively ensured; 2) the performance of these algorithms on large scale ELD optimization tasks remains to be unsatisfactory. CLPSO is an effective global optimization algorithm. To strengthen the convergence ability of CLPSO, the sequential quadratic programming (SQP) is introduced into it. This results in a new algorithm hybrid of comprehensive learning particle swarm optimization and sequential quadratic programming (SQP-CLPSO). To assess the performance of SQP-CLPSO, it is compared with several state-of-the-art evolutionary algorithms (EAs) on the classical ELD optimization problems. Experimental results show that SQP-CLPSO has very good abilities of convergence, diversity maintainence and scalability, which make it suitable for complex ELD problems.

关键词： particle swarm optimization comprehensive learning particle swarm optimization sequential quadratic programming local search power systems economic load dispatch

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AN EFFICIENT NUMERICAL METHOD FOR THE SOLUTION OF THE L₂ OPTIMAL MASS TRANSFER PROBLEM

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SIAM JOURNAL ON SCIENTIFIC COMPUTING 2010年第1期32卷 197-211页

作者： Haber, Eldad Rehman, Tauseef Tannenbaum, Allen Emory Univ Dept Math & Comp Sci Atlanta GA 30322 USA Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA Georgia Inst Technol Sch Elect & Comp Atlanta GA 30332 USA Georgia Inst Technol Sch Biomed Engn Atlanta GA 30332 USA

In this paper we present a new computationally efficient numerical scheme for the minimizing flow approach for the computation of the optimal L-2 mass transport mapping. In contrast to the integration of a time dependent partial differential equation proposed in [S. Angenent, S. Haker, and A. Tannenbaum, SIAM J. Math. Anal., 35 (2003), pp. 61-97], we employ in the present work a direct variational method. The efficacy of the approach is demonstrated on both real and synthetic data.

关键词： optimal mass transport sequential quadratic programming variational formulation

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Swarm Intelligence-based Stochastic programming Model for Dynamic Asset Allocation

Swarm Intelligence-based Stochastic Programming Model for Dy...

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2010 IEEE World Congress on Computational Intelligence

作者： Dang, Jing Edelman, David Hochreiter, Ronald Brabazon, Anthony Univ Coll Dublin Nat Comp Res & Applicat Grp Sch Business Dublin Ireland WU Vienna Univ Econom & Business Dept Math & Stat Vienna Austria

ISBN: (纸本)9781424481262

Asset allocation is critical for the portfolio management process. In this paper, we solve a dynamic asset allocation problem through a multiperiod stochastic programming model. The objective is to maximise the expected utility of wealth at the end of the planning period. To improve the optimisation process of the model, we employ swarm intelligent optimisers, the Bacterial Foraging Optimisation (BFO) and the Particle Swarm Optimisation (PSO) algorithm. A hybrid optimiser using the BFO for initialisation and the sequential quadratic programming (SQP) for searching the decision variables is also suggested. The results are compared with the stand-alone SQP and the canonical Genetic Algorithm. We have performed numerical experiments on 2-asset and 4-asset allocation problem respectively. The numerical results suggest that the hybrid method provides a better result especially for the 4-asset case, with improved fitness value and robustness than using BFO, PSO, GA, or SQP alone.

关键词： bacterial foraging optimisation canonical genetic algorithm dynamic asset allocation financial management hybrid optimiser optimisation process particle swarm optimisation particle swarm optimisation planning period portfolio management process quadratic programming robustness sequential quadratic programming stochastic programming stochastic programming model swarm intelligent optimiser

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Optimum Seismic Response Control of Multiple Degree of Freedom Structures using Tuned Viscous Mass Dampers

Optimum Seismic Response Control of Multiple Degree of Freed...

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10th International Conference on Computational Structures Technology

作者： Ikago, K. Sugimura, Y. Saito, K. Inoue, N. Tohoku Univ Grad Sch Engn Sendai Miyagi Japan NTT Facil Inc Res & Dev Tokyo Japan NTT Facil Inc Bldg Engn Tokyo Japan

ISBN: (纸本)9781905088386

The authors have presented a new seismic control device the Tuned Viscous Mass Damper (TVMD). The TVMD consists of a viscous mass damper with an apparent mass amplifier and a soft spring which connects the damper to the primary system. The mass amplifier allowed us to make the additional mass and device itself smaller compared with a conventional TMD. The design method to determine an optimum set of damper parameters has not yet been presented for a vibration control system of a damped MDOF structure, while that of an undamped SDOF structure is obtained by the fixed point theory. In this paper, we present a design method to obtain a set of optimum damper parameters for a seismic control system of a damped MDOF structure using sequential quadratic programming (SQP).

关键词： tuned viscous mass damper dynamic vibration absorber optimum vibration control fixed point theory sequential quadratic programming seismic control

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A ROBUST MINIMUM VOLUME ENCLOSING SIMPLEX ALGORITHM FOR HYPERSPECTRAL UNMIXING

A ROBUST MINIMUM VOLUME ENCLOSING SIMPLEX ALGORITHM FOR HYPE...

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2010 IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Ambikapathi, ArulMurugan Chan, Tsung-Han Ma, Wing-Kin Chi, Chong-Yung Natl Tsing Hua Univ Inst Commun Eng Hsinchu Taiwan

ISBN: (纸本)9781424442966

Hyperspectral unmixing is a process of extracting hidden spectral signatures (or endmembers) and the corresponding proportions (or abundances) of a scene, from its hyperspectral observations. Motivated by Craig's belief, we recently proposed an alternating linear programming based hyperspectral unmixing algorithm called minimum volume enclosing simplex (MVES) algorithm, which can yield good unmixing performance even for instances of highly mixed data. In this paper, we propose a robust MVES algorithm called RMVES algorithm, which involves probabilistic reformulation of the MVES algorithm, so as to account for the presence of noise in the observations. The problem formulation for RMVES algorithm is manifested as a chance constrained program, which can be suitably implemented using sequential quadratic programming (SQP) solvers in an alternating fashion. Monte Carlo simulations are presented to demonstrate the efficacy of the proposed RMVES algorithm over several existing benchmark hyperspectral unmixing methods, including the original MVES algorithm.

关键词： Convex analysis Hyperspectral unmixing Minimum-volume enclosing simplex Chance constrained program sequential quadratic programming

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Hybrid Predictive Control Design with Mixed Inputs based on PSO and its Application for Control of a Batch Reactor

Hybrid Predictive Control Design with Mixed Inputs based on ...

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2010 IEEE World Congress on Computational Intelligence

作者： Munoz-Carpintero, Diego A. Saez, Doris Skrjanc, Igor Univ Chile Dept Elect Engn Av Tupper 2007 Santiago Chile Univ Ljubljana Fac Elect Engn Ljubljana Slovenia

ISBN: (纸本)9781424481262

In this work, we propose a combined approach based on Particle Swarm Optimization (PSO) and sequential quadratic programming (SQP) for solving the real-time optimization problem appearing in the hybrid predictive control of systems with continuous and discrete inputs. The conventional PSO for continuous problems is mixed with binary PSO for handling discrete variables, and after iterations of the algorithm have ended, SQP is applied for refining the continuous variables. This new method (PSO+SQP) is favorably compared with a conventional non-linear optimization techniques (based on Branch and Bound and Explicit Enumeration) and PSO. Also, a multi-objective approach is considered as a tuning method for the population size and number of iterations for PSO. All these algorithms are applied for the temperature control of a Batch Reactor.

关键词： batch reactor binary PSO branch and bound chemical reactors continuous inputs control system synthesis discrete inputs explicit enumeration hybrid predictive control design mixed inputs nonlinear optimization particle swarm optimisation particle swarm optimization predictive control quadratic programming real-time optimization problem sequential quadratic programming temperature control temperature control

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An Interactive Evolutionary Multi-objective Optimization Method Based on Polyhedral Cones

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4th Conference on Learning and Intelligent Optimization

作者： Sinha, Ankur Korhonen, Pekka Wallenius, Jyrki Deb, Kalyanmoy Aalto Univ Sch Econ Dept Business Technol Helsinki 00076 Finland

ISBN: (纸本)9783642137990

This paper suggests a preference based methodology, where the information provided by the decision maker in the intermediate runs of an evolutionary multi-objective optimization algorithm is used to construct a polyhedral cone. This polyhedral cone is used to eliminate a part of the search space and conduct a more focussed search. The domination principle is modified, to look for better solutions lying in the region of interest. The search is terminated by using a local search based termination criterion. Results have been presented on two to five objective problems and the efficacy of the procedure has been tested.

关键词： Evolutionary multi-objective optimization multiple criteria decision-making interactive multi-objective optimization sequential quadratic programming preference based multi-objective optimization

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Structure Characteristic Analysis and Optimization Design for Microsatellite

Structure Characteristic Analysis and Optimization Design fo...

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10th International Conference on Machining and Advanced Manufacturing Technology

作者： Zheng, Kan Liao, Wenhe Zhang, Xiang Nanjing Univ Aeronaut & Astronaut Coll Mech & Elect Engn Nanjing Peoples R China Nanjing Univ Aeronaut & Astronaut Acad Frontier Sci Nanjing Peoples R China

ISBN: (纸本)0878492844

According to the structural layout and mechanics characteristic of microsatellite, the FEM was established reasonably. Base on the FEM analysis and its characteristics, the structure of microsatellite was optimization designed. In the optimization process, the optimization model was established with the design variables of aluminum panel thickness, core plate thickness and skeleton thickness, and subjected to stiffness, strength, displacement and size constraints. Then, used the sequential quadratic programming method for optimization analysis. The results of the optimization demonstrates that the weight of structure loss significantly, and the whole structure weight of the microsatellite loss 11%.Meanwhile, the iterative times of the optimization process is few, so it is very Meaningful and useful for actual project application.

关键词： Microsatellite FEM Optimization design sequential quadratic programming Honeycomb sandwich panel

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AN EFFICIENT NUMERICAL METHOD FOR THE SOLUTION OF THE L₂ OPTIMAL MASS TRANSFER PROBLEM

AN EFFICIENT NUMERICAL METHOD FOR THE SOLUTION OF THE <i>L</...

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10th Copper Mountain Conference on Iterative Methods

关键词： optimal mass transport sequential quadratic programming variational formulation

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