Aim at the hysteretic nonlinearity characteristic of the giant magnetostrictive actuator in control, an internal model control method based on support vector regression is presented in this paper. Its models are built...
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Aim at the hysteretic nonlinearity characteristic of the giant magnetostrictive actuator in control, an internal model control method based on support vector regression is presented in this paper. Its models are built by support vector regression using the input and output data of the actuator and the internal model control is achieved. The simulation results show the method in this paper has better control precision.
Collision avoidance is always difficult in the planning path for a mobile robot. In this paper, the virtual force field between a mobile robot and an obstacle is formed and regulated to maintain a desired distance by ...
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Collision avoidance is always difficult in the planning path for a mobile robot. In this paper, the virtual force field between a mobile robot and an obstacle is formed and regulated to maintain a desired distance by hybrid force control algorithm. Since uncertainties from robot dynamics and obstacle degrade the performance of a collision avoidance task, intelligent control is used to compensate for the uncertainties. A radial basis function (RBF) neural network is used to regulate the force field of an accurate distance between a robot and an obstacle in this paper and then simulation studies are conducted to confirm that the proposed algorithm is effective.
This paper proposes an effective framework to boost the efficiency of covariance matching. In this framework, covariance matrices are used to match object in complex environment by fusing multiple features. Then, Gene...
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This paper proposes an effective framework to boost the efficiency of covariance matching. In this framework, covariance matrices are used to match object in complex environment by fusing multiple features. Then, Genetic Algorithm (GA) is employed to improve the processing speed of covariance matching. To take advantage of the property of GA for the optimization in large search spaces to covariance matching, a fitness function is designed using the distances between the covariance matrices of model and candidate regions. Experimental results show that the proposed approach can improve the processing speed of covariance matching observably. The computing speed of the proposed method is at least 7 times than that of exhaustive searching.
In this paper, we present the inverse kinematical of a novel 6-DOF orthogonal parallel mechanism. The displacements Δl i (i = 1,..., 6) of steering gears were deduced from the position and orientation of the moving ...
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In this paper, we present the inverse kinematical of a novel 6-DOF orthogonal parallel mechanism. The displacements Δl i (i = 1,..., 6) of steering gears were deduced from the position and orientation of the moving platform. The desired trajectory was assumed to be more complex nonlinear curves, simulations are performed for the real time trajectory tracking of the mechanism. By using Matlab software, the analysis and simulation of mechanism can be carried out conveniently, and the efficiency of the design can be upgraded. The simulation curves of each displacement were provided and analyzed though simulative research. The results will be used for synthesis of the control law in the form of error feedback, and measurements results of actual movements by means of sensors. The analysis can help to realize the trajectory tracking control fast and accurately.
To tackle the problem of slippage during the cold rolling process of a tandem mill, a schedule optimization model for preventing slippage was established based on slip factor. Aiming to the shortages of the standard g...
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To tackle the problem of slippage during the cold rolling process of a tandem mill, a schedule optimization model for preventing slippage was established based on slip factor. Aiming to the shortages of the standard genetic algorithm, such as premature convergence, oscillation and over-randomization, an improved adaptive genetic algorithm was applied to optimize the system. In the algorithm a population-sorted multi-roulette-wheel selection operator was put forward for reducing the selected error generated by roulette-wheel randomization and promoting the probability of selecting better individuals. Simultaneously the algorithm decides the crossover rate and mutation rate of chromosome based on the individual adaptive value in the calculation process, makes the start phase variable obviously and the later phase stable slowly, and ensures population development, seeking balance and entire convergence. Experimental results and actual application show that the schedule optimization model can reduce the slip probability prominently, improve the product quality, and achieve a better economic benefit.
Spectrum allocation is one of the most important problems in cognitive radio networks. However, the channel differentiated algorithms have not been emphasized in the current literature. This paper first proposes a cla...
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ISBN:
(纸本)9787894631046
Spectrum allocation is one of the most important problems in cognitive radio networks. However, the channel differentiated algorithms have not been emphasized in the current literature. This paper first proposes a classification criterion for heterogeneous channels. Then, an allocation algorithm for the channel classification is provided with the consideration of channel differences and spatial reuse of primary user's channels. Simulation result shows that the proposed algorithm improves the spectrum utilization and other network performance.
Node localization becomes an important issue in the wireless sensor network as its broad applications in environment monitoring, emergency rescue and battlefield surveillance, etc. Basically, the DV-Hop localization m...
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Node localization becomes an important issue in the wireless sensor network as its broad applications in environment monitoring, emergency rescue and battlefield surveillance, etc. Basically, the DV-Hop localization mechanism can work well with the assistance of beacon nodes that have the capability of self-positioning. However, if the network is invaded by a wormhole attack, the attacker can tunnel the packets via the wormhole link to cause severe impacts on the DV-Hop localization process. The distance-vector propagation phase during the DV-Hop localization even aggravates the positioning result, compared to the localization schemes without wormhole attacks. In this paper, we analyze the impacts of wormhole attack on DV-Hop localization scheme. Based on the basic DV-Hop localization process, we propose a label-based secure localization scheme to defend against the wormhole attack. Simulation results demonstrate that our proposed secure localization scheme is capable of detecting the wormhole attack and resisting its adverse impacts with a high probability.
In this paper, we formulate multi-channel assignment in Wireless Sensor Networks (WSNs) as an optimization problem and show it is NP-hard. We then propose a distributed Game Based Channel Assignment algorithm (GBCA) t...
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ISBN:
(纸本)9781424458363
In this paper, we formulate multi-channel assignment in Wireless Sensor Networks (WSNs) as an optimization problem and show it is NP-hard. We then propose a distributed Game Based Channel Assignment algorithm (GBCA) to solve the problem. GBCA takes into account both the network topology information and transmission routing information. We prove that there exists at least one Nash Equilibrium in the channel assignment game. Furthermore, we analyze the sub-optimality of Nash Equilibrium and the convergence of the Best Response in the game. Simulation results are given to demonstrate that GBCA can reduce interference significantly and achieve satisfactory network performance in terms of delivery ratio, throughput, channel access delay and energy consumption.
In order to solve the problem of trajectory tracking for a class of novel serial-parallel hybrid humanoid arm(HHA), which has parameters uncertainty, frictions, disturbance, abrasion and pulse forces derived from mo...
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In order to solve the problem of trajectory tracking for a class of novel serial-parallel hybrid humanoid arm(HHA), which has parameters uncertainty, frictions, disturbance, abrasion and pulse forces derived from motors, a multistep dynamics modeling strategy is proposed and a robust controller based on neural network(NN)-adaptive algorithm is designed. At the first step of dynamics modeling, the dynamics model of the reduced HHA is established by Lagrange method. At the second step of dynamics modeling, the parameter uncertain part resulting mainly from the idealization of the HHA is learned by adaptive algorithm. In the trajectory tracking controller, the radial basis function(RBF) NN, whose optimal weights are learned online by adaptive algorithm, is used to learn the upper limit function of the total uncertainties including frictions, disturbances, abrasion and pulse forces. To a great extent, the conservatism of this robust trajectory tracking controller is reduced, and by this controller the HHA can impersonate mostly human actions. The proof and simulation results testify the validity of the adaptive strategy for parameter learning and the neural network-adaptive strategy for the trajectory tracking control.
Based on the design concept of virtual instrument and the design method of function modulation, using PC machine and data acquisition card as hardware system, proposed a design of sewage multi-parameter online monitor...
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