In recent years, more and more plug-in hybrid electric vehicles (PHEVs) have been put to use in smart grid. In this paper, we consider a dynamic aggregator-PHEV system, where the aggregator convinces the PHEVs to use ...
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In recent years, more and more plug-in hybrid electric vehicles (PHEVs) have been put to use in smart grid. In this paper, we consider a dynamic aggregator-PHEV system, where the aggregator convinces the PHEVs to use electricity rather than gas by setting an appropriate charging price dynamically. We propose a payoff-maximizing algorithm for the aggregator to decide not only the charging price but also the electricity amount purchased from real-time power market based on Lyapunov optimization. Furthermore, we transform the power purchase problem into the energy allocation problem among all the PHEVs. The proposed algorithm operates in real time and does not require any prior knowledge of the statistical information of the system. Theoretically, we demonstrate the proposed algorithm can guarantee system stability and achieve a result that is away from the optimum by O(1/V ), where V is a control parameter. The effectiveness and robustness of the algorithm is validated through simulation results.
Monitoring system of furnace ash fouling is the foundation of the soot-blowing operation on furnace *** furnace exit gas temperature(FEGT) is the key parameter in monitoring system,a new CM-LSSVM-PLS method is propose...
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Monitoring system of furnace ash fouling is the foundation of the soot-blowing operation on furnace *** furnace exit gas temperature(FEGT) is the key parameter in monitoring system,a new CM-LSSVM-PLS method is proposed to predict *** the process of CM-LSSVM-PLS method,considering the characteristics of operational data,c-means(CM) cluster algorithm is used to partition the training data into several different *** are subsequently developed in the individual subsets based on least squares support vector machine(LSSVM).Finally,partial least squares(PLS) algorithm is employed as the combination *** single LSSVM is established to make a comparison with CM-LSSVM-PLS *** proposed model is verified through operation data of a 300 MW generating *** comparison result shows that the new CM-LSSVM-PLS method can predict FEGT accurately while the time consumed in modeling decrease drastically.
The increasing demands on the indoor location service inspire the wide attentions to investigate the indoor position algorithms. Access point(AP) selection is critical important for increasing the estimation accuracy ...
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The increasing demands on the indoor location service inspire the wide attentions to investigate the indoor position algorithms. Access point(AP) selection is critical important for increasing the estimation accuracy of the indoor location. In this paper, the key features in influencing the accuracy of indoor location systems are investigated. Base on the analysis results, we present an AP selection strategy for indoor location by proposing a novel AP selection index for test point. By using the experiment data, the K-Nearest Neighbor(KNN) and weighted-KNN(WKNN) indoor location methods are carried out to illustrate the performance proposed AP selection strategy. The performance of our AP selection strategy is validated by comparing with the exhaustive AP selection strategy, the fisher AP selection strategy and the largest RSSI strength AP selection strategy. The experiment results show that the proposed AP selection strategy can improve the location accuracy of indoor location with Wi-Fi.
In the combustion system and ash fouling system of boiler,the furnace exit gas temperature(FEGT)is the key parameter for ensuring high *** it is hard to achieve satisfactory performance through conventional control st...
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In the combustion system and ash fouling system of boiler,the furnace exit gas temperature(FEGT)is the key parameter for ensuring high *** it is hard to achieve satisfactory performance through conventional control strategy,the control problem of FEGT has become critical and significant in coal-fired boiler *** this paper,a new predictive control scheme based on particle swarm optimization(PSO)and CM-LSSVM-PLS model is *** the proposed control scheme,a new CM-LSSVM-PLS method is proposed and used as the predictive model to predict the future *** the process of CM-LSSVM-PLS method,c-means cluster(CM)algorithm is used to partition the training data into several different subsets by considering the characteristics of operational *** sub-models are subsequently developed in the individual subsets based on least squares support vector machine(LSSVM).Then,partial least squares algorithm(PLS)is employed as the combination ***,PSO is used as the receding optimization *** proposed control is verified through operation data of a 300MW generating *** simulation results show that the effectiveness of our proposed control scheme.
Consensus is a fundamental and important problem for cooperative *** paper mainly studies the consensus of networked multi-agent systems with nonlinear couplings via pinning *** adaptive desired weighting consensus pr...
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ISBN:
(纸本)9781479947249
Consensus is a fundamental and important problem for cooperative *** paper mainly studies the consensus of networked multi-agent systems with nonlinear couplings via pinning *** adaptive desired weighting consensus protocol is proposed to control a small fraction of pinned agents for directed ***,an adaptive controller gain average consensus protocol is presented via the selected pinning agents for weighted directed *** conditions for achieving the desired consensus asymptotically are ***,theoretical results are validated via simulations.
In this paper, we present a new adaptive backstepping control design method to solve the overparametrization problem in parameter estimation. Unlike the existing schemes, the concept of tuning functions is not ***, th...
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In this paper, we present a new adaptive backstepping control design method to solve the overparametrization problem in parameter estimation. Unlike the existing schemes, the concept of tuning functions is not ***, the number of parameter estimates is reduced to be minimal, which is exactly the same as that of unknown parameters. The parametric strict-feedback system is employed to illustrate our design procedure.
作者:
Li, JiaojieZhang, WeiSu, HoushengYang, YupuDepartment of Automation
Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Department of Measurement and Control Technology
Shanghai Dian Ji University Shanghai China School of Automation
Key Laboratory of Image Information Processing and Intelligent Control (Huazhong University of Science and Technology) Ministry of Education National Key Laboratory of Science and Technology on Multispectral Information Processing Huazhong University of Science and Technology Wuhan China
In this paper, we study the flocking problem of multi-agent systems with obstacle avoidance, in the situation when only a fraction of the agents have information on the obstacles. Obstacles of arbitrary shape are allo...
In this paper, we study the flocking problem of multi-agent systems with obstacle avoidance, in the situation when only a fraction of the agents have information on the obstacles. Obstacles of arbitrary shape are allowed, no matter if their boundary is smooth or non-smooth, and no matter it they are convex or non-convex. A novel geometry representation rule is proposed to transfer obstacles to a dense obstacle-agents lattice structure. Non-convex regions of the obstacles are detected and supplemented using a geometric rule. The uninformed agents can detect a section of the obstacles boundary using only a range position sensor. We prove that with the proposed protocol, uninformed agents which maintain a joint path with any informed agent can avoid obstacles that move uniformly and assemble around a point along with the informed agents. Eventually all the assembled agents reach consensus on their velocity. In the entire flocking process, no distinct pair of agents collide with each other, nor collide with obstacles. The assembled agents are guaranteed not to be lost in any non-convex region of the obstacles within a distance constraint. Numerical simulations demonstrate the flocking algorithm with obstacle avoidance both in 2D and 3D space. The situation when every agent is informed is considered as a special case.
There are currently several ways of wireless access to support vehicular communication, including vehicular ad-hoc networks (VANETs) and cellular networks (off-the-shelf 3G and LTE). It is necessary to make a seamless...
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ISBN:
(纸本)9781479944484
There are currently several ways of wireless access to support vehicular communication, including vehicular ad-hoc networks (VANETs) and cellular networks (off-the-shelf 3G and LTE). It is necessary to make a seamless handover decision to guarantee quality of service (QoS) of communications for a vehicle moving in the regions covered by more than one access networks. In this paper, we provide a performance guaranteed optimized handover decision algorithm. With this algorithm, the communication of vehicles can handover through heterogeneous wireless access networks not only to reach overall load balance among all access points, but also to maximize the data rate of the whole networks as well as the vehicles' fairness. In addition, in the process of decision making, the data rate of handover vehicles is estimated. Simulations are performed to demonstrate the efficiency of the proposed algorithm.
Model predictive control (MPC) has attracted wide attention in process industries with its ability to handle constrained multivariable processes. Computational complexity can become a limiting factor when MPC is appli...
Model predictive control (MPC) has attracted wide attention in process industries with its ability to handle constrained multivariable processes. Computational complexity can become a limiting factor when MPC is applied to large-scale systems with fast sampling times. In this paper, a control scheme known as multi-step robust MPC is presented for polytopic uncertain multi-input systems. Only one or several state feedback laws are optimized at each time interval to reduce computational complexity. A set invariance condition for polytopic uncertain systems is identified and the invariant set is determined by solving a linear matrix inequality (LMI) optimization problem. Based on the set invariance condition, a min-max multi-step robust MPC scheme is proposed. Numerical simulations show the effectiveness of the proposed scheme.
Fractional order proportional-integral-derivative (FOPID) controller generalizes the standard PID controller. Compared to PID controller, FOPID controller has more parameters and the tuning of parameters is more compl...
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Fractional order proportional-integral-derivative (FOPID) controller generalizes the standard PID controller. Compared to PID controller, FOPID controller has more parameters and the tuning of parameters is more complex. In this paper, an improved artificial bee colony algorithm, which combines cyclic exchange neighborhood with chaos (CNC-ABC), is proposed for the sake of tuning the parameters of FOPID controller. The characteristic of the proposed CNC-ABC exists in two folds: one is that it enlarges the search scope of the solution by utilizing cyclic exchange neighborhood techniques, speeds up the convergence of artificial bee colony algorithm (ABC). The other is that it has potential to get out of local optima by exploiting the ergodicity of chaos. The proposed CNC-ABC algorithm is used to optimize the parameters of the FOPID controller for an automatic voltage regulator (AVR) system. Numerical simulations show that the CNC-ABC FOPID controller has better performance than other FOPID and PID controllers.
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