The limiting performa nce analysis is used to study the optimal shock and impact isolation of mechanic al systems. The use of wavelets to approximate time-domain control functions is investigated. The formulation for...The limiting performa nce analysis is used to study the optimal shock and impact isolation of mechanic al systems. The use of wavelets to approximate time-domain control functions is investigated. The formulation for numerical computation is developed. Numerical examples include the optimal shock isolation of a SDOF system and the optimal i mpact isolation of a MDOF system. Computational results show that compactly supp orted wavelets can represent abrupt changes in control functions better than tri gonometric series and considerably increase computational efficiency.展开更多
In order to solve instability problem of calculation precision resulting from the selection of each target weight in evaluating weapon systems, a weighted sum based method is proposed. Specif- ically, the subjective w...In order to solve instability problem of calculation precision resulting from the selection of each target weight in evaluating weapon systems, a weighted sum based method is proposed. Specif- ically, the subjective weights depending on experts＇ experience are substituted by the optimal weights. The optimal weights are acquired through constructing a mathematical programming model based on subjective weights and objective weights. The method of solving subjective weights is the same as before, and the objective weights were solved by means of grey theory. The case analysis shows that the method of improved weighted sum can improve the evaluation precision up to more than 5% , and minimize the instability of calculation precision resulting from only using subjective weights. The method that the optimal weights substituted the subjective weights is brought forward in improving evaluation precision for the first time. The ideas of the optimal weights and the pro- posed method are described and analyzed.展开更多
This paper describes empirical research on the model, optimization and supervisory control of beer fermentation.Conditions in the laboratory were made as similar as possible to brewery industry conditions. Since mathe...This paper describes empirical research on the model, optimization and supervisory control of beer fermentation.Conditions in the laboratory were made as similar as possible to brewery industry conditions. Since mathematical models that consider realistic industrial conditions were not available, a new mathematical model design involving industrial conditions was first developed. Batch fermentations are multiobjective dynamic processes that must be guided along optimal paths to obtain good results.The paper describes a direct way to apply a Pareto set approach with multiobjective evolutionary algorithms (MOEAs).Successful finding of optimal ways to drive these processes were reported.Once obtained, the mathematical fermentation model was used to optimize the fermentation process by using an intelligent control based on certain rules.展开更多
Task allocation is a key issue of agent cooperation mechanism in Multi-Agent Systems. The important features of an agent system such as the latency of the network infrastructure, dynamic topology, and node heterogenei...Task allocation is a key issue of agent cooperation mechanism in Multi-Agent Systems. The important features of an agent system such as the latency of the network infrastructure, dynamic topology, and node heterogeneity impose new challenges on the task allocation in Multi-Agent environments. Based on the traditional parallel computing task allocation method and Ant Colony Optimization (ACO), a novel task allocation method named Collection Path Ant Colony Optimization (CPACO) is proposed to achieve global optimization and reduce processing time. The existing problems of ACO are analyzed; CPACO overcomes such problems by modifying the heuristic function and the update strategy in the Ant-Cycle Model and establishing a threedimensional path pheromone storage space. The experimental results show that CPACO consumed only 10.3% of the time taken by the Global Search Algorithm and exhibited better performance than the Forward Optimal Heuristic Algorithm.展开更多
Efficient optimization strategy of multibody systems is developed in this paper. Aug- mented Lagrange method is used to transform constrained optimal problem into unconstrained form firstly. Then methods based on seco...Efficient optimization strategy of multibody systems is developed in this paper. Aug- mented Lagrange method is used to transform constrained optimal problem into unconstrained form firstly. Then methods based on second order sensitivity are used to solve the unconstrained problem, where the sensitivity is solved by hybrid method. Generalized-α method and generalized-α projection method for the differential-algebraic equation, which shows more efficient properties with the lager time step, are presented to get state variables and adjoint variables during the optimization procedure. Numerical results validate the accuracy and efficiency of the methods is presented.展开更多
文摘The limiting performa nce analysis is used to study the optimal shock and impact isolation of mechanic al systems. The use of wavelets to approximate time-domain control functions is investigated. The formulation for numerical computation is developed. Numerical examples include the optimal shock isolation of a SDOF system and the optimal i mpact isolation of a MDOF system. Computational results show that compactly supp orted wavelets can represent abrupt changes in control functions better than tri gonometric series and considerably increase computational efficiency.
基金Supported by the Natonal Natural Science Foundation of China(5145781)
文摘In order to solve instability problem of calculation precision resulting from the selection of each target weight in evaluating weapon systems, a weighted sum based method is proposed. Specif- ically, the subjective weights depending on experts＇ experience are substituted by the optimal weights. The optimal weights are acquired through constructing a mathematical programming model based on subjective weights and objective weights. The method of solving subjective weights is the same as before, and the objective weights were solved by means of grey theory. The case analysis shows that the method of improved weighted sum can improve the evaluation precision up to more than 5% , and minimize the instability of calculation precision resulting from only using subjective weights. The method that the optimal weights substituted the subjective weights is brought forward in improving evaluation precision for the first time. The ideas of the optimal weights and the pro- posed method are described and analyzed.
文摘This paper describes empirical research on the model, optimization and supervisory control of beer fermentation.Conditions in the laboratory were made as similar as possible to brewery industry conditions. Since mathematical models that consider realistic industrial conditions were not available, a new mathematical model design involving industrial conditions was first developed. Batch fermentations are multiobjective dynamic processes that must be guided along optimal paths to obtain good results.The paper describes a direct way to apply a Pareto set approach with multiobjective evolutionary algorithms (MOEAs).Successful finding of optimal ways to drive these processes were reported.Once obtained, the mathematical fermentation model was used to optimize the fermentation process by using an intelligent control based on certain rules.
基金supported by National Natural Science Foundation of China under Grant No.61170117Major National Science and Technology Programs under Grant No.2010ZX07102006+3 种基金National Key Technology R&D Program under Grant No.2012BAH25B02the National 973 Program of China under Grant No.2011CB505402the Guangdong Province University-Industry Cooperation under Grant No.2011A090200008the Scientific Research Foundation, Returned Overseas Chinese Scholars, State Education Ministry
文摘Task allocation is a key issue of agent cooperation mechanism in Multi-Agent Systems. The important features of an agent system such as the latency of the network infrastructure, dynamic topology, and node heterogeneity impose new challenges on the task allocation in Multi-Agent environments. Based on the traditional parallel computing task allocation method and Ant Colony Optimization (ACO), a novel task allocation method named Collection Path Ant Colony Optimization (CPACO) is proposed to achieve global optimization and reduce processing time. The existing problems of ACO are analyzed; CPACO overcomes such problems by modifying the heuristic function and the update strategy in the Ant-Cycle Model and establishing a threedimensional path pheromone storage space. The experimental results show that CPACO consumed only 10.3% of the time taken by the Global Search Algorithm and exhibited better performance than the Forward Optimal Heuristic Algorithm.
基金supported by the National Natural Science Foundation of China (11002075 and 10972110)
文摘Efficient optimization strategy of multibody systems is developed in this paper. Aug- mented Lagrange method is used to transform constrained optimal problem into unconstrained form firstly. Then methods based on second order sensitivity are used to solve the unconstrained problem, where the sensitivity is solved by hybrid method. Generalized-α method and generalized-α projection method for the differential-algebraic equation, which shows more efficient properties with the lager time step, are presented to get state variables and adjoint variables during the optimization procedure. Numerical results validate the accuracy and efficiency of the methods is presented.
