从非优到优的属性分析方法

提出了一种与最优化系统相对应的理论——系统非优分析,从而将人类实践的过程和结果按其性质划分为"优"、"介优"和"非优"三大范畴,并建立了从非优系统去寻求优系统的方法.但非优系统并不排斥在实践中追求最优化的目标和结果.而非优系统的形成是最优系统存在的基础,同时从非优系统中还可以度量优系统的不同特征和功能.本文还从实际现象中总结出系统优与非优的关系,然后从以往最优化的实际出发,给出了一种由非优逼近优的方法,最后提出了这一领域的研究方向.

Fuzzy Variable Structure Control of Photovoltaic MPPT System

In order to reduce chattering phenomenon of variable structure control, a fuzzy variable structure control method is adopted and applied in the photovoitaic maximum power point tracking （MPPT） control system. Firstly, the electric features of PV cells and a dynamic model of photovoitaic system with a DGDC buck converter are analysed. Then a hybrid fuzzy variable structure controller is designed. The controller is composed of a fuzzy variable structure control term and a supervisory control term. The former is the main part of the controller and the latter is used to ensure the stability of the system. Finally, the conventional variable structure control method and the fuzzy variable structure control method are applied respectively. The comparing of simulation results shows the superiority of the latter.

Availability-based maintenance optimization under unequal inspection period and imperfect repair

Taking the multi-component system as research object, a maintenance optimization model based on the unequal inspection period and imperfect repair is established by considering the requirement of expected availability for improving the system＇s availability. An age reduction factor is used to describe the effect of imperfect repair, and the modelling approach for the unequal inspection period is proposed. Unavailable situations are classified into three kinds of independent cases, and the availability is calculated accordingly. Based on the analysis of the relationship between the unavailable cases and the unequal inspection period, an optimization model under imperfect repair is established to optimize the system＇s expected availability. A case study of a wind turbine is provided, and three key components, i.e. gearbox, generator and spindle, are considered. The optimization results of the unequal inspection period model and the equal inspection period model are compared. The results show that the unequal inspection period model based on availability can update the maintenance plan so as to optimize maintenance activities and improve the system＇s availability.

A Quadratic precision generalized nonlinear global optimization migration velocity inversion method

An important research topic for prospecting seismology is to provide a fast accurate velocity model from pre-stack depth migration. Aiming at such a problem, we propose a quadratic precision generalized nonlinear global optimization migration velocity inversion. First we discard the assumption that there is a linear relationship between residual depth and residual velocity and propose a velocity model correction equation with quadratic precision which enables the velocity model from each iteration to approach the real model as quickly as possible. Second, we use a generalized nonlinear inversion to get the global optimal velocity perturbation model to all traces. This method can expedite the convergence speed and also can decrease the probability of falling into a local minimum during inversion. The synthetic data and Mamlousi data examples show that our method has a higher precision and needs only a few iterations and consequently enhances the practicability and accuracy of migration velocity analysis （MVA） in complex areas.

A New Nonlinear Conjugate Gradient Method for Unconstrained Optimization Problems

In this paper,an efficient conjugate gradient method is given to solve the general unconstrained optimization problems,which can guarantee the sufficient descent property and the global convergence with the strong Wolfe line search conditions.Numerical results show that the new method is efficient and stationary by comparing with PRP＋ method,so it can be widely used in scientific computation.

Application of a Derivative-Free Method with Projection Skill to Solve an Optimization Problem

Improving numerical forecasting skill in the atmospheric and oceanic sciences by solving optimization problems is an important issue. One such method is to compute the conditional nonlinear optimal perturbation(CNOP), which has been applied widely in predictability studies. In this study, the Differential Evolution(DE) algorithm, which is a derivative-free algorithm and has been applied to obtain CNOPs for exploring the uncertainty of terrestrial ecosystem processes, was employed to obtain the CNOPs for finite-dimensional optimization problems with ball constraint conditions using Burgers' equation. The aim was first to test if the CNOP calculated by the DE algorithm is similar to that computed by traditional optimization algorithms, such as the Spectral Projected Gradient(SPG2) algorithm. The second motive was to supply a possible route through which the CNOP approach can be applied in predictability studies in the atmospheric and oceanic sciences without obtaining a model adjoint system, or for optimization problems with non-differentiable cost functions. A projection skill was first explanted to the DE algorithm to calculate the CNOPs. To validate the algorithm, the SPG2 algorithm was also applied to obtain the CNOPs for the same optimization problems. The results showed that the CNOPs obtained by the DE algorithm were nearly the same as those obtained by the SPG2 algorithm in terms of their spatial distributions and nonlinear evolutions. The implication is that the DE algorithm could be employed to calculate the optimal values of optimization problems, especially for non-differentiable and nonlinear optimization problems associated with the atmospheric and oceanic sciences.

Determination of reasonable finished state of self-anchored suspension bridges

A systematic and generic procedure for the determination of the reasonable finished state of self-anchored suspension bridges is proposed, the realization of which is mainly through adjustment of the hanger tensions. The initial hanger tensions are first obtained through an iterative analysis by combining the girder-tower-only finite element(FE) model with the analytical program for shape finding of the spatial cable system. These initial hanger tensions, together with the corresponding cable coordinates and internal forces, are then included into the FE model of the total bridge system, the nonlinear analysis of which involves the optimization technique. Calculations are repeated until the optimization algorithm converges to the most optimal hanger tensions(i.e. the desired reasonable finished bridge state). The "temperature rigid arm" is introduced to offset the unavoidable initial deformations of the girder and tower, which are due to the huge axial forces originated from the main cable. Moreover, by changing the stiffness coefficient K in the girder-tower-only FE model, the stiffness proportion of the main girder, the tower or the cable subsystem in the whole structural system could be adjusted according to the design intentions. The effectiveness of the proposed method is examined and demonstrated by one simple tutorial example and one self-anchored suspension bridge.

Multi-Objective Optimal Approach for Injection Molding Based on Surrogate Model and Particle Swarm Optimization Algorithm

An integrated optimization strategy based on Kriging model and multi-objective particle swarm optimization(PSO) algorithm was constructed.As a new surrogate model technology,Kriging model has better fitting precision for nonlinear problem.The Kriging model was adopted to replace computer aided engineering(CAE) simulation as fitness function of multi-objective PSO algorithm,and the computation cost can be reduced greatly.By introducing multi-objective handling mechanism of crowding distance and mutation operator to multiobjective PSO algorithm,the entire Pareto front can be approximated better.It is shown that the multi-objective optimization strategy can get higher solving accuracy and computation efficiency under small sample.