Multi-population and diffusion UMDA for dynamic multimodal problems

In dynamic environments,it is important to track changing optimal solutions over time.Univariate marginal distribution algorithm（UMDA） which is a class algorithm of estimation of distribution algorithms attracts more and more attention in recent years.In this paper a new multi-population and diffusion UMDA（MDUMDA） is proposed for dynamic multimodal problems.The multi-population approach is used to locate multiple local optima which are useful to find the global optimal solution quickly to dynamic multimodal problems.The diffusion model is used to increase the diversity in a guided fashion,which makes the neighbor individuals of previous optimal solutions move gradually from the previous optimal solutions and enlarge the search space.This approach uses both the information of current population and the part history information of the optimal solutions.Finally experimental studies on the moving peaks benchmark are carried out to evaluate the proposed algorithm and compare the performance of MDUMDA and multi-population quantum swarm optimization（MQSO） from the literature.The experimental results show that the MDUMDA is effective for the function with moving optimum and can adapt to the dynamic environments rapidly.

Research Status and Application Prospect of Aluminum Matrix Composites

Aluminum matrix composite is one of the most attractive metal matrix composites.It is a kind of material with strong vitality emerging in response to the needs of modern scientific development.Compared with traditional materials,aluminum matrix composites have the advantages of low density,good electric conductivity and heat conductivity,good wear resistance and oxidation resistance,high specific strength and stiffness,high temperature resistance,good heat treatment performance and flexible preparation process,which make them widely used in the fields of aviation,aerospace,and automobile.In this paper,the factors affecting the properties of aluminum matrix composites,the strengthening mechanism,classification and preparation methods of aluminum matrix composites are summarized.The research status,development direction and application prospect of aluminum matrix composites are briefly introduced.

EMMAE failure detection system and failure evaluation over flight performance

Purpose-The purpose of this paper is to present the research into fault detection and isolation(FDI)and evaluation of the reduction of performance after failures occurred in the flight control system(FCS)during its mission operation.Design/methodology/approach–The FDI is accomplished via using the multiple models scheme which is developed based on the Extend Kalman Filter(EKF)algorithm.Towards this objective,the healthy mode of the FCS under different type of failures,including the control surfaces and structural,should be considered.It developed a bank of extended multiple models adaptive estimation(EMMAE)to detect and isolate the above mentioned failures in the FCS.In addition,the performances including the flight envelope,the voyage and endurance in cruising are proposed to reference and evaluate the process of mission,especially for UAV under failure conditions.Findings-The contribution of this paper is to provide the information not only about the failures,but also considering whether the UAV can accomplish the task for the ground station.Originality/value-The main contribution of this paper is in the areas of the structural and control surface faults researching,which are occurred in the mission procedures and emphasized the identification of those failures’magnitudes.The FDI scheme includes the performance evaluation,while the evaluation obtained through the extensive numerical simulations and saved in the offline database.As a consequence,it is more accurate and less computationally demanding while evaluating the performance.