Key Laboratory of Gansu Advanced Control for Industrial Process

Lanzhou, China

Key Laboratory of Gansu Advanced Control for Industrial Process

Lanzhou, China
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Dang C.,Lanzhou University of Technology | Dang C.,Key Laboratory of Gansu Advanced Control for Industrial Process | Liu H.,Lanzhou University of Technology | Zhang X.,Lanzhou University of Technology
2013 25th Chinese Control and Decision Conference, CCDC 2013 | Year: 2013

This article in-depth analyzes the control character of the Z-source inverter in photovoltaic power generation system. According to these problems of the dynamic performance of the Z-source inverter output and boosting controlling strategy lead to double switched frequency etc. A new improved boosting modulation strategy is presented. Based on SVPWM, changing turning on or off time of the same bridge switches to insert 6 shoot-through states in the single-cycle of traditional zero vector. Compared with the conventional boosting modulation strategy, the modulation is not only to stabilize the output performance of Z source inverter in a certain extent, and can effectively reduce the switching frequency. In addition, According to inaccurate problem of inserting the shoot-through time for traditional modulation strategy, this article presents the strategy to control accurately the shoot-through time through the slope of the modulation signal, to make Z-source inverter more controllable. These advantages of improved precision boosting modulation strategy are verified by simulation and experiment. © 2013 IEEE.

Zhao F.Q.,Lanzhou University of Technology | Zhao F.Q.,Key Laboratory of Gansu Advanced Control for Industrial Process | Tang J.X.,Lanzhou University of Technology | Yang Y.H.,Lanzhou University of Technology
Journal of Computers | Year: 2012

Manufacturing supply chain(SC) faces changing business environment and various customer demands. Pareto Ant Colony Optimisation (P-ACO) in order to obtain the non-dominated set of different SC designs was utilized as the guidance for designing manufacturing SC. PACO explores the solution space on the basis of applying the Ant Colony Optimisation algorithm and implementing more than one pheromone matrix, one for every objective. The SC design problem has been addressed by using Pareto Ant Colony Optimisation in which two objectives are minimised simultaneously. There were tested two ways in which the quantity of pheromones in the PM is incremented. In the SPM, the pheromone increment is a function of the two objectives, cost and time, while in MPM the pheromone matrix is divided into two pheromones, one for the cost and another one for the time. It could be concluded that the number of solutions do not depend on if the pheromone is split or is a function of the two variables because both method explore the same solution space. Although both methods explore the same solution space, the POS generated by every one is different. The POS that is generated when the pheromone matrix is split got solutions with lower time and cost than SMP because in the probabilistic decision rule a value of λ = 0.2 is used. It means that the ants preferred solution with a low cost instead of solutions with low time. The strategy of letting the best-so-far ant deposit pheromone over the PM accelerates the algorithm to get the optimal POS although the number of ants in the colony is small. An experimental example is used to test the algorithm and show the benefits of utilising two pheromone matrices and multiple ant colonies in SC optimisation problem. © 2012 ACADEMY PUBLISHER.

Zhao F.,Lanzhou University of Technology | Zhao F.,Key Laboratory of Gansu Advanced Control for Industrial Process | Tang J.,Lanzhou University of Technology | Wang J.,Lanzhou University of Technology | Wei C.,Lanzhou University of Technology
Journal of Computers | Year: 2011

The particle swarm optimization algorithm (PSO) has two typical problems as in other adaptive evolutionary algorithms, which are based on swarm intelligence search. To deal with the problems of the slow convergence rate and the tendency to trap into premature, an improved particle swarm optimization with decline disturbance index (DDPSO) is presented in this paper. The index was added when the velocity of the particle is prone to stagnation in the middle and later evolution periods. The modification improves the ability of particles to explore the global and local optimization solutions, and reduces the probability of being trapped into the local optima. Theoretical analysis, which is based on stochastic processes, proves that the trajectory of particle is a Markov processes and DDPSO algorithm converges to the global optimal solution with mean square merit. Experimental simulations show that the improved algorithm can not only improve the convergence of the algorithm significantly, but also avoid trapping into local optimization solution.

Zhao F.,Lanzhou University of Technology | Zhao F.,Northwestern Polytechnical University | Zhao F.,Key Laboratory of Gansu Advanced Control for Industrial Process | Yang Y.,Lanzhou University of Technology | And 2 more authors.
Advanced Science Letters | Year: 2012

Dynamic rescheduling model and its solution method are of significant importance for the dynamic scheduling problem in manufacturing system. However, few attempts have been done on the universal communication and negotiation mechanism for the dynamic rescheduling problem and corresponding solution approach. A dynamic rescheduling model, which is based on Multi-Agent System (MAS), was proposed. A memetic algorithm with PSO (particle swarm optimization) and DE (differential evolution) was presented as the solution method to the rescheduling model. Furthermore, the simulation results in dynamic scheduling accompanying with its perturbation show that the proposed model and the algorithm are effective to the dynamic scheduling problem in manufacturing system. © 2012 American Scientific Publishers.

Dang C.-L.,Lanzhou University of Technology | Dang C.-L.,Key Laboratory of Gansu Advanced Control for Industrial Process | Yan J.,Lanzhou University of Technology | Zhang X.-Y.,Lanzhou University of Technology | Zhang X.-Y.,Key Laboratory of Gansu Advanced Control for Industrial Process
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | Year: 2011

Dynamic voltage restorer (DVR) has been considered to be a cost-effective custom power device, which alleviates voltage sags. The compensation capability index for DVR is compensation duration. To maximize compensation duration of DVR device when compensated voltage sags, a novel time optimal compensation strategy is proposed, and the novel strategy is implemented by controlling the phase angle β between load voltage phasor and supply voltage phasor. In order to reduce disturbances to loads and smoothen transient processes at the beginning and end of compensation, the proposed strategy adopts a control method that β changes progressively by constant step △β and determines the compensating direction by identifying signs of specific variables, according to T-β curve. This control method for β avoids directly computing optimal β and has less calculation. The simulation results illustrate that the proposed strategy can obtain longer compensation duration and utilize more DC-link energy for DVR, compared with minimum energy compensation strategy.

Zhang M.-G.,Lanzhou University of Technology | Zhang M.-G.,Key Laboratory of Gansu Advanced Control for Industrial Process | Li L.-R.,Lanzhou University of Technology
PEAM 2011 - Proceedings: 2011 IEEE Power Engineering and Automation Conference | Year: 2011

Load forecasting, especially short-term load forecasting is of great significance for the planning, scheduling, marketing of power system. In order to predict the daily load as accurate as possible,a combined prediction method based on Least Squares Support Vector Machine (LS-SVM) and BP Neural Network (BPNN) is proposed in this paper. The historical load of relational better six-day ahead and the day type are selected as input,and got 1-dimensional output variable. Two sets of different prediction results are obtained from LS-SVM method and BPNN method, which is combined by using the method of minimum variance to research the final prediction results. The load prediction results of northwest grid show that the combined forecasting method has better prediction accuracy than LS-SVM and BPNN method. Therefore, this method is efficient and practical for a short-term load forecasting of electric power system. © 2011 IEEE.

Zhao F.G.,Lanzhou University of Technology | Zhao F.G.,Key Laboratory of Gansu Advanced Control for Industrial Process | Li X.Y.,Lanzhou University of Technology | Zhang Q.Y.,Lanzhou University of Technology | Jonrinaldi,University of Exeter
Journal of Software | Year: 2012

For the whole matching cannot handle partial occlusion and lack of specificity, a new method using Polar- Radius-Invariant-Moment, which is based on Key-Points to extract features for target's shape recognition, is presented in this paper. Firstly, key-points of the hand shape are extracted through discrete curve evolution method. Secondly, Polar-Radius-Invariant-Moment based on Key- Points is used to describe the characteristics of the gesture shape. Finally, Euclidean distance is utilized in gesture recognition to verify the validity of this method. Hand objects are selected as the test case to testify the performance of the method. Simulation results prove that this method has a better classification character than that of obtained by the Polar-Radius-Invariant-Moment with recognizing the object shape rapidly and accurately, and that it also can keep highly stable even if the object contour was ill-segmented or noisy. © 2012 ACADEMY PUBLISHER.

Li W.,Lanzhou University of Technology | Li W.,Key Laboratory of Gansu Advanced Control for Industrial Process | Cheng Y.,Lanzhou University of Technology | Xu D.,Lanzhou University of Technology
Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) | Year: 2011

Method of inverse system for fault tolerance was presented, in which the method of nonlinear uncertain systems was the only part of the inverse reversible. After a robust sliding mode observer was introduced, the irreversible part and the actuator failures were estimated on-line. Thus modified inverse model was compensated and the faults were adjusted on-line, so that it accurately in numerical approximation on the non-linear uncertainty of the inverse model of the controlled object. Simulation results show that the proposed method not only for the non-explicit multivariable unknown nonlinear uncertain system has good control effect, but also in case of actuator failures have good fault-tolerance effect.

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