Applied Mechanics and Materials Vol. 151

Abstract: Introduce some basic knowledge, methods and theory of using the finite element software ANSYS to carry out contact analysis, and then establish the contact simulation analysis finite element model for CTP imaging drum and plate by using the software ANSYS. A numerical simulation analysis on the imaging drum and the plate indicates that the analysis results are consistent with the experimental results, so as to lay the foundation for the reliability and stability of dynamic design and optimization design of CTP imaging drum.

Abstract: In this paper,the motion planning problem for mobile robot is addressed. Motion planning (MP) has diversified over the past few decades to include many different approaches such as cell decomposition, road maps, potential fields, and genetic algorithms. Often the goal of motion planning is not just obstacle avoidance but optimization of certain parameters as well. A motion planning algorithms based on Rapidly-exploring random Tree(RRT) is present in the paper. Then the RRT algorithm has been extended which combines the SLAM algorithm.The Extend-RRT-SLAM has been simulated in MobileSim.Simulation results show Extend-RRT-SLAM to be very effective for robot motion planning.

Abstract: This paper is concerned with Q-learning , a very popular algorithm for reinforcement learning ,for obstacle avoidance through neural networks. The principle tells that the focus always must be on both ecological nice tasks and behaviours when designing on robot. Many robot systems have used behavior-based systems since the 1980’s.In this paper, the Khepera robot is trained through the proposed algorithm of Q-learning using the neural networks for the task of obstacle avoidance. In experiments with real and simulated robots, the neural networks approach can be used to make it possible for Q-learning to handle changes in the environment.

Abstract: To solve the traffic congestion control problem on oversaturated network, the control problem is formulated as a conflicted multi-objective control problem., a new stability preference multi-objective compatible optimization control(SPMOCC) algorithm is proposed to solve the conflicted multi-objective control problem. In the proposed SPMOCC algorithm, NSGA-II algorithm is adjusted by proposing non-even Pareto front spread preserving strategy to obtain some special area on the Pareto front; a stability preference selection strategy is proposed to obtain stable controller. The proposed SPMOCC is used to solve the oversaturated traffic network control problem in a core area of 11 junctions under the simulation environment. It is proved that the proposed compatible optimization control algorithm can handle the oversaturated traffic network control problem effectively than the fixed time control method.

Abstract: Configuration technology is a new technology for monitoring in the current society; it is the result of the development of computer control technology. To traffic light control system, it is to combine the use of configuration technology and procedures related to PLC, and through software simulation and traffic lights light changes, traffic light control system could achieve the monitoring problem, and if the system is in good condition, its application can save a lot of labor powers and materials.

Abstract: In order to gain the maximum destroy when the concrete facilities are penetrated by projectile, the best detonation position must be controlled. So a signal processor system was designed to record the penetration acceleration. The acceleration character and the control algorithm of penetration depth were studied by simulation. The displacement integrated by acceleration was verified to be effective, which could control the detonation of projectile in the right position.

Abstract: In order to obtain an optimal transmission scheme for the joints of supported leg of a multi-legged walking robot, the experience, which comes from the research of a large-scale six-legged heavy-duty walking robot, is used for reference. Five kinds of transmission schemes are respectively listed, and they are respectively analyzed in detail. Based on the comprehensive performance comparison, the listing approach is employed to synthetically compare on excellences and shortcomings among transmission schemes. The best transmission scheme is obtained through the comparative analysis, which provides technique support for the design and analysis on the multi-legged walking robot.

Abstract: The application based on Backpropagation (BP) Algorithm network is conducted on identifying the categories and numbers of mechanical equipments by acoustic signal in battlefield targets. Collected signal was pre-processed and extracted the power spectrum feature of acoustic signal as input vectors of neural networks, then classified by neural networks and pattern recognition theorem. We employ the acoustic signals of six kinds of normal equipments as training samples to train the network. The experiment shows that the ratio of recognition of the acoustic signal processing system based on neural networks proposed is better than the conventional methods.

Abstract: Compared with the noisy chaotic neural network, hysteretic noisy chaotic neural network always exhibits better optimization performance at higher noise levels, but exhibits worse optimization performance at lower noise levels. In order to enable the hysteretic noisy chaotic neural network to behave more excellent optimization performance not only at higher noise levels but also at lower noise levels, we introduce a noise compensation factor to the original hysteretic noisy chaotic neural network, and present noise compensation based hysteretic noisy chaotic neural network. The proposed network can outperform the hysteretic noisy chaotic neural network by the interaction of hysteretic activation function and the noise compensation factor. One benchmark broadcast scheduling problem is used to verify the superiority of the proposed network. The simulation results show that the proposed network takes advantages over the noisy chaotic neural network, the hysteretic noisy chaotic neural network and other algorithms.

Abstract: A novel transiently chaotic neural network with radial basis function is proposed by analyzing the capability of chaotic search and the effect in solving combinational optimization problem. The character of Radial basis function is higher nonlinear and better function approaching ability. So a novel transiently chaotic neural network is presented by transferring sigmoid activation function into non-monotonous activation function which is composed by Contrary Multiquadric function and Sigmoid. This network is used to solve Traveling Salesman Problem (TSP), and the simulation result indicates that it can avoid the limit of being trapped into the local minima and converge to the global minima with high speed.