Artificial Physics Optimization (APO) algorithm is a population-based stochastic algorithm based on Physicomimetics framework. The algorithm utilizes an attraction-repulsion mechanism to move individuals toward optima...
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Artificial Physics Optimization (APO) algorithm is a population-based stochastic algorithm based on Physicomimetics framework. The algorithm utilizes an attraction-repulsion mechanism to move individuals toward optimality. The convergence analysis of APO algorithm is made theoretically. By regarding each individual's position on each evolutionary step as a stochastic vector, APO algorithm determined by non-negative real parameter tuple {w, G} is analyzed using discrete-time linear system theory. The convergent condition of APO algorithm and corresponding parameter selection guidelines are derived. The simulation results show that the convergent condition is effective in guiding the parameter selection of APO algorithm and can help to explain why those parameters work well.
Group search optimizer (GSO) is a new novel swarm intelligent technique by simulating animal behavioral ecology. However, as a stochastic optimization algorithm, it is still easily trapped into local optima when deali...
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Group search optimizer (GSO) is a new novel swarm intelligent technique by simulating animal behavioral ecology. However, as a stochastic optimization algorithm, it is still easily trapped into local optima when dealing with multi-modal optimization problems. Therefore, in this paper, a new variant of GSO is designed by hybriding Metropolis rule to further enhancing the capability escaping from local optima. simulation results show the performance of this new variant is superior to the standard group search optimizer and particle swarm optimization in multi-model problems especially for high-dimensional cases.
Crank block steering mechanism optimization is a nonlinear constrained optimization problem, which is important for forklift truck to get preferable steering performance. Particle swarm optimization (PSO) with feasibi...
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As one of valid modeling and coordinated controlling tools, the particle swarm optimization algorithm can be extended for applying to task of swarm robotic search. To gain an insight into effects of key parameters on ...
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A rapid reentry trajectory planning method for a common aero vehicle (CAV) subject to all path constraints is developed. The reentry trajectory is divided into initial descent phase and quasi-equilibrium glide phase w...
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ISBN:
(纸本)9781424460434
A rapid reentry trajectory planning method for a common aero vehicle (CAV) subject to all path constraints is developed. The reentry trajectory is divided into initial descent phase and quasi-equilibrium glide phase which possesses a majority of the reentry period. An improved quasi-equilibrium glide condition is utilized to convert reentry corridor constraints to the control variable constraints and get a simple relation between the range-to-go and velocity. Accordingly the longitudinal reference trajectory is computed through the one-parameter search of bank angle model and the corresponding tracking law is designed using linear quadratic regulator theory. To enhance the maneuvering capability, a geometrical control approach considering no-fly zone constraints is applied to the lateral guidance. Finally, the performance of this method is verified by computer simulation.
This article introduces an open architecture for arc welding robot controller with self-defined Harting-bus structure. Each sub-board composes the controller and is connected to a bus base-plate through unified electr...
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ISBN:
(纸本)9781849192385
This article introduces an open architecture for arc welding robot controller with self-defined Harting-bus structure. Each sub-board composes the controller and is connected to a bus base-plate through unified electrical interface (Harting-Terminal). Each module is flexible and it can be customized to further promotion of the controller so that non R&D personnel can be able to cut or extend the controller function according to specific engineering requirements. In the swing welding control stage, a track interpolation algorithm that gives priority to analytical method is applied to arc welding robot controller. The algorithm can be applied to the swing welding of straight line, and also to the sinusoidal-swing welding that takes spatial smooth curve as the baseline. Preliminary experimental results show that the arc welding robot controller can realize the motion control of 6 degree-of-freedom with industrial welding operation, and particularly it can achieve good results for sinusoidal-swing welding along with spatial circular arc and quadratic curve.
Chaotic synchronization criteria for a class of dynamical networks with each node being RCL-shunted Josephson junction is proposed in this paper. The proposed algorithms, which are established in terms of linear matri...
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ISBN:
(纸本)9787894631046
Chaotic synchronization criteria for a class of dynamical networks with each node being RCL-shunted Josephson junction is proposed in this paper. The proposed algorithms, which are established in terms of linear matrix inequalities (LMIs), guarantee the synchronized states to be global asymptotically stable. In addition, an interesting conclusion is reached that the chaotic synchronization in the coupled whole 3N-dimensional networks can be converted into that of 3-dimensional space.
The direction of each individual velocity vector is very useful information for search in Artificial Physics Optimization (APO) algorithm. APO's simple way to dealing with the errant individual exceeded the lower ...
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The direction of each individual velocity vector is very useful information for search in Artificial Physics Optimization (APO) algorithm. APO's simple way to dealing with the errant individual exceeded the lower or upper bounds constrains changes the direction of its motion vector. A shrinkage coefficient is introduced to ensure that each individual is within the decision space without changing its direction. One-dimensional search method is merged into the vector model of APO (VM-APO) to improve its local search capability. The simulation results confirm that the performance of the hybrid vector APO with one-dimensional search method is effective.
Particle swarm optimization with passive congregation (PSOPC) is a novel variant by incorporating a passive congregation. However, we argue the analysis for the third item velocity update equation. In PSOPC, this item...
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In particle swarm, optimization, all particles obey the same movementmotions. This conflicts the natural phenomenon. Due to the different foodpressure, each particle has different movement pattern in each ***, in this...
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