—Cyber Movement Organization (CMO) is a special kind of social movement organization on the Web. In this paper, we propose a model to simulate the mobilizing process of CMO, which consists of the individual unit, org...
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—Cyber Movement Organization (CMO) is a special kind of social movement organization on the Web. In this paper, we propose a model to simulate the mobilizing process of CMO, which consists of the individual unit, organization unit, and the mobilizing mechanisms. The mobilizing mechanisms has three sub-mechanisms: the participation mechanism, the choice mechanism, and the inviting mechanism. A dataset of more than two million “human flesh search” related microblogs is used to validate the model. Empirical results show that our model can capture the key features of the real-world mobilizing process.
Similarity computation is especially significant in collaborative filtering algorithms. In the existed literatures or large recommender systems, researchers generally use cosine similarity or Pearson correlation coeff...
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A head pursuit optimal adaptive sliding mode guidance law is proposed to intercept high speed target in a novel head pursuit scenario with low maneuver requirement and energy consumption. Head pursuit is a new traject...
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A head pursuit optimal adaptive sliding mode guidance law is proposed to intercept high speed target in a novel head pursuit scenario with low maneuver requirement and energy consumption. Head pursuit is a new trajectory strategy which the interceptor with smaller velocity is placed in front of the target and both of them fly in the same direction. This engagement could reduce relative speed and energy consumption by its special trajectory strategy. Optimal strategy is derived on the basis of minimal control energy to achieve satisfactory precision. But this optimal strategy could only deal with non-maneuver target. Thus, an adaptive sliding mode method is implemented to eliminate the error, which is caused by the target maneuver. And implementation of this method does not need to know the detail information of target acceleration but some estimation to its limitation. What's more, with the constraint the optimal strategy exerts on the acceleration, the maneuver requirement is reduced and the energy consumption is cut down. The robustness and stability of this method has been proved theoretically. At last, the performance and precision of this method is verified with some numerical instances.
In this paper, the modelling of a class of distributed water supply networks is considered, where the modelling of pipes, valves, pump stations and reservoirs are presented separately. Two laws, nodal mass balance and...
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Repetitive model predictive control is an effective method to track a periodic signal as well as reject a periodic disturbance. However, since repetitive controller uses discrete-time model, there always exists ripple...
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Repetitive model predictive control is an effective method to track a periodic signal as well as reject a periodic disturbance. However, since repetitive controller uses discrete-time model, there always exists ripple when controlling a continuous system with periodic disturbance. This paper proposes a new way for repetitive model predictive control by using multi-rate model. Due to the multi-rate model, the model predictive controller can optimize the system outputs during the period between two sampling times, and then provide a more delicate control action, which can result in the reduced ripple. The simulation demonstrates its effectiveness.
This paper proposes a novel MPPT method, which will provide a correct tracking direction under the condition of non-abrupt atmospheric changes, especially non-irradiation conditions. We also present a model predictive...
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This paper proposes a novel MPPT method, which will provide a correct tracking direction under the condition of non-abrupt atmospheric changes, especially non-irradiation conditions. We also present a model predictive control method based on a cost function, which help to derive the predictions for each possible switching state. The control scheme obtained is capable of controlling the dc-link current to a desired MPPT reference current, while injecting sinusoidal current to the grid with reduced total harmonic distortion. Finally, the simulation results illustrate the effectiveness of our proposed method.
For the last 30 years the theory and technology of model predictive control (MPC) have been developed rapidly. However, facing the increasing requirements on the constrained optimization control arising from the rapid...
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For the last 30 years the theory and technology of model predictive control (MPC) have been developed rapidly. However, facing the increasing requirements on the constrained optimization control arising from the rapid development of economy and society, the current MPC theory and technology is still faced with great challenges. In this paper, the development of MPC theory and industrial applications are briefly reviewed and the limitations of current MPC theory and technology are analyzed. The necessity to strengthen the MPC research with respect to enhancing its effectiveness, scientificness, and usability is pointed out. We briefly summarize recent developments and new trends in the area of MPC theoretical study and applications, and point out that the investigation of MPC for large scale systems, fast dynamic systems, low cost systems and nonlinear systems will be of significance for further development of MPC theory and broadening MPC application fields.
As the development of plugin hybrid electric vehicles (PHEV), this kind of hybrid vehicles have great potential in increasing the efficiency of energy and reducing carbon emission. The plug-in-feature not only means c...
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As the development of plugin hybrid electric vehicles (PHEV), this kind of hybrid vehicles have great potential in increasing the efficiency of energy and reducing carbon emission. The plug-in-feature not only means charging quickly and conveniently, but also brings power grid a great challenge in dynamic stability. Considering the information asymmetric characteristic in electricity market, we propose a contract based charging strategy with profit maximization of power sector as the object while guaranteeing the PHEV users' non-negative utility. We prove the result of the strategy via simulations based on meticulous modeling of PHEV.
This paper proposes an incremental smooth support vector regression (ISSVR) method for TS fuzzy modeling. Under certain assumptions on membership functions, we propose an optimization problem for TS fuzzy modeling bas...
This paper proposes an incremental smooth support vector regression (ISSVR) method for TS fuzzy modeling. Under certain assumptions on membership functions, we propose an optimization problem for TS fuzzy modeling based on the structural risk minimization principle. We show that this problem is an SVR problem with non-positive definite kernels. It cannot be solved using conventional SVR. Then we establish a connection between this TS fuzzy modeling problem and smooth support vector regression (SSVR), which is a smoothing strategy for solving SVR. The problem is always solvable using SSVR because SSVR puts no restrictions on the kernel. Then we apply an incremental approach to the SSVR by selecting informative samples from the training dataset. Taking advantage of SSVR, more forms of membership functions can be used in our model compared with conventional methods. Experiments show that the proposed ISSVR-based TS fuzzy model has good generalization ability with small number of fuzzy rules.
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