In this paper, a hybrid automatic optimization strategy is proposed for the design of underwater robot lines. Isight is introduced as an integration platform. The construction of this platform is based on the user pro...In this paper, a hybrid automatic optimization strategy is proposed for the design of underwater robot lines. Isight is introduced as an integration platform. The construction of this platform is based on the user programming and several commercial software including UG6.0, GAMBIT2.4.6 and FLUENT12.0. An intelligent parameter optimization method, the particle swarm optimization, is incorporated into the platform. To verify the strategy proposed, a simulation is conducted on the underwater robot model 5470, which originates from the DTRC SUBOFF project. With the automatic optimization platform, the minimal resistance is taken as the optimization goal;the wet surface area as the constraint condition; the length of the fore-body, maximum body radius and after-body＇s minimum radius as the design variables. With the CFD calculation, the RANS equations and the standard turbulence model are used for direct numerical simulation. By analyses of the simulation results, it is concluded that the platform is of high efficiency and feasibility. Through the platform, a variety of schemes for the design of the lines are generated and the optimal solution is achieved. The combination of the intelligent optimization algorithm and the numerical simulation ensures a global optimal solution and improves the efficiency of the searching solutions.展开更多
The inversions of complex geophysical data always solve multi-parameter, nonlinear, and multimodal optimization problems. Searching for the optimal inversion solutions is similar to the social behavior observed in swa...The inversions of complex geophysical data always solve multi-parameter, nonlinear, and multimodal optimization problems. Searching for the optimal inversion solutions is similar to the social behavior observed in swarms such as birds and ants when searching for food. In this article, first the particle swarm optimization algorithm was described in detail, and ant colony algorithm improved. Then the methods were applied to three different kinds of geophysical inversion problems： （1） a linear problem which is sensitive to noise, （2） a synchronous inversion of linear and nonlinear problems, and （3） a nonlinear problem. The results validate their feasibility and efficiency. Compared with the conventional genetic algorithm and simulated annealing, they have the advantages of higher convergence speed and accuracy. Compared with the quasi-Newton method and Levenberg-Marquardt method, they work better with the ability to overcome the locally optimal solutions.展开更多
Many engineering optimization problems frequently encounter continuous variables and discrete variables which adds considerably to the solution complexity. Very few of the existing methods can yield a globally optimal...Many engineering optimization problems frequently encounter continuous variables and discrete variables which adds considerably to the solution complexity. Very few of the existing methods can yield a globally optimal solution when the objective functions are non-convex and non-differentiable. This paper presents a hybrid swarm intelligence ap-proach (HSIA) for solving these nonlinear optimization problems which contain integer, discrete, zero-one and continuous variables. HSIA provides an improvement in global search reliability in a mixed-variable space and converges steadily to a good solution. An approach to handle various kinds of variables and constraints is discussed. Comparison testing of several examples of mixed-variable optimization problems in the literature showed that the proposed approach is superior to current methods for finding the best solution, in terms of both solution quality and algorithm robustness.展开更多
We proposed an optimal design method to expand the bandwidth for the control of large hydraulic Stewart platform.The method is based on generalized natural frequency and takes hydraulic oil into consideration.A Lagran...We proposed an optimal design method to expand the bandwidth for the control of large hydraulic Stewart platform.The method is based on generalized natural frequency and takes hydraulic oil into consideration.A Lagrangian formulation which considers the whole leg inertia is presented to obtain the accurate equivalent mass matrix.Using the model,the effect of leg inertia and the influence of design parameters on the generalized natural frequency are investigated.Finally,numerical examples are presented to validate and confirm the efficiency of the mathematical model.The results show that the leg inertia,especially the piston part plays an important role in the dynamics.The optimum diameter ratio of the base to the moving platform is between 2 and 3,and the optimum joint angle ratio of the base to the moving platform is about 1.The smaller joint angles and a longer leg stroke are favorable for raising system frequencies.The system oil should be preprocessed for large platforms with a requirement for good dynamic performance.展开更多
Due to its simplicity and ease of use, the standard grey wolf optimizer （GWO） is attracting much attention. However, due to its imperfect search structure and possible risk of being trapped in local optima, its appl...Due to its simplicity and ease of use, the standard grey wolf optimizer （GWO） is attracting much attention. However, due to its imperfect search structure and possible risk of being trapped in local optima, its application has been limited. To perfect the performance of the algorithm, an optimized GWO is proposed based on a mutation operator and eliminating-reconstructing mechanism （MR-GWO）. By analyzing GWO, it is found that it conducts search with only three leading wolves at the core, and balances the exploration and exploitation abilities by adjusting only the parameter a, which means the wolves lose some diversity to some extent. Therefore, a mutation operator is introduced to facilitate better searching wolves, and an eliminating- reconstructing mechanism is used for the poor search wolves, which not only effectively expands the stochastic search, but also accelerates its convergence, and these two operations complement each other well. To verify its validity, MR-GWO is applied to the global optimization experiment of 13 standard continuous functions and a radial basis function （RBF） network approximation experiment. Through a comparison with other algorithms, it is proven that MR-GWO has a strong advantage.展开更多
Pigeon-inspired optimization(PIO) is a new swarm intelligence optimization algorithm, which is inspired by the behavior of homing pigeons. A variant of pigeon-inspired optimization named multi-objective pigeon-inspire...Pigeon-inspired optimization(PIO) is a new swarm intelligence optimization algorithm, which is inspired by the behavior of homing pigeons. A variant of pigeon-inspired optimization named multi-objective pigeon-inspired optimization(MPIO) is proposed in this paper. It is also adopted to solve the multi-objective optimization problems in designing the parameters of brushless direct current motors, which has two objective variables, five design variables, and five constraint variables. Furthermore, comparative experimental results with the modified non-dominated sorting genetic algorithm are given to show the feasibility, validity and superiority of our proposed MIPO algorithm.展开更多
文摘In this paper, a hybrid automatic optimization strategy is proposed for the design of underwater robot lines. Isight is introduced as an integration platform. The construction of this platform is based on the user programming and several commercial software including UG6.0, GAMBIT2.4.6 and FLUENT12.0. An intelligent parameter optimization method, the particle swarm optimization, is incorporated into the platform. To verify the strategy proposed, a simulation is conducted on the underwater robot model 5470, which originates from the DTRC SUBOFF project. With the automatic optimization platform, the minimal resistance is taken as the optimization goal;the wet surface area as the constraint condition; the length of the fore-body, maximum body radius and after-body＇s minimum radius as the design variables. With the CFD calculation, the RANS equations and the standard turbulence model are used for direct numerical simulation. By analyses of the simulation results, it is concluded that the platform is of high efficiency and feasibility. Through the platform, a variety of schemes for the design of the lines are generated and the optimal solution is achieved. The combination of the intelligent optimization algorithm and the numerical simulation ensures a global optimal solution and improves the efficiency of the searching solutions.
基金supported by the 973 Program(Grant No 2007CB209600)Open Fund(No.GDL0706) of the Key Laboratory of Geo-detection(China University of Geosciences,Beijing),Ministry of Education
文摘The inversions of complex geophysical data always solve multi-parameter, nonlinear, and multimodal optimization problems. Searching for the optimal inversion solutions is similar to the social behavior observed in swarms such as birds and ants when searching for food. In this article, first the particle swarm optimization algorithm was described in detail, and ant colony algorithm improved. Then the methods were applied to three different kinds of geophysical inversion problems： （1） a linear problem which is sensitive to noise, （2） a synchronous inversion of linear and nonlinear problems, and （3） a nonlinear problem. The results validate their feasibility and efficiency. Compared with the conventional genetic algorithm and simulated annealing, they have the advantages of higher convergence speed and accuracy. Compared with the quasi-Newton method and Levenberg-Marquardt method, they work better with the ability to overcome the locally optimal solutions.
基金Project supported by the National Natural Science Foundation ofChina (Nos. 60074040 6022506) and the Teaching and ResearchAward Program for Outstanding Young Teachers in Higher Edu-cation Institutions of China
文摘Many engineering optimization problems frequently encounter continuous variables and discrete variables which adds considerably to the solution complexity. Very few of the existing methods can yield a globally optimal solution when the objective functions are non-convex and non-differentiable. This paper presents a hybrid swarm intelligence ap-proach (HSIA) for solving these nonlinear optimization problems which contain integer, discrete, zero-one and continuous variables. HSIA provides an improvement in global search reliability in a mixed-variable space and converges steadily to a good solution. An approach to handle various kinds of variables and constraints is discussed. Comparison testing of several examples of mixed-variable optimization problems in the literature showed that the proposed approach is superior to current methods for finding the best solution, in terms of both solution quality and algorithm robustness.
基金supported by the National Basic Research Program(973)of China(No.2006CB705400)the National Natural Science Founda-tion of China(No.50705082)the National Natural Science Fund for Distinguished Young Scholar(No.50425518),China
文摘We proposed an optimal design method to expand the bandwidth for the control of large hydraulic Stewart platform.The method is based on generalized natural frequency and takes hydraulic oil into consideration.A Lagrangian formulation which considers the whole leg inertia is presented to obtain the accurate equivalent mass matrix.Using the model,the effect of leg inertia and the influence of design parameters on the generalized natural frequency are investigated.Finally,numerical examples are presented to validate and confirm the efficiency of the mathematical model.The results show that the leg inertia,especially the piston part plays an important role in the dynamics.The optimum diameter ratio of the base to the moving platform is between 2 and 3,and the optimum joint angle ratio of the base to the moving platform is about 1.The smaller joint angles and a longer leg stroke are favorable for raising system frequencies.The system oil should be preprocessed for large platforms with a requirement for good dynamic performance.
基金supported by the National High-Tech R&D Program(863)of China(No.2015AA7041003)the Scientific Research Plan Projects of Shanxi Education Department(No.17JK0825)the Scientific Research Plan Projects of Xianyang Normal University(No.15XSYK036)
文摘Due to its simplicity and ease of use, the standard grey wolf optimizer （GWO） is attracting much attention. However, due to its imperfect search structure and possible risk of being trapped in local optima, its application has been limited. To perfect the performance of the algorithm, an optimized GWO is proposed based on a mutation operator and eliminating-reconstructing mechanism （MR-GWO）. By analyzing GWO, it is found that it conducts search with only three leading wolves at the core, and balances the exploration and exploitation abilities by adjusting only the parameter a, which means the wolves lose some diversity to some extent. Therefore, a mutation operator is introduced to facilitate better searching wolves, and an eliminating- reconstructing mechanism is used for the poor search wolves, which not only effectively expands the stochastic search, but also accelerates its convergence, and these two operations complement each other well. To verify its validity, MR-GWO is applied to the global optimization experiment of 13 standard continuous functions and a radial basis function （RBF） network approximation experiment. Through a comparison with other algorithms, it is proven that MR-GWO has a strong advantage.
基金partially supported by the National Natural Science Foundation of China(Grant Nos.61425008,61333004 and 61273054)National Key Basic Research Program of China("973"Project)(Grant Nos.2014CB046401 and 2013CB035503)Top-Notch Young Talents Program of China,Aeronautical Foundation of China(Grant No.20135851042)
文摘Pigeon-inspired optimization(PIO) is a new swarm intelligence optimization algorithm, which is inspired by the behavior of homing pigeons. A variant of pigeon-inspired optimization named multi-objective pigeon-inspired optimization(MPIO) is proposed in this paper. It is also adopted to solve the multi-objective optimization problems in designing the parameters of brushless direct current motors, which has two objective variables, five design variables, and five constraint variables. Furthermore, comparative experimental results with the modified non-dominated sorting genetic algorithm are given to show the feasibility, validity and superiority of our proposed MIPO algorithm.
