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, organ...
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This paper considers reset controlsystems with output *** present sufficient conditions for the quadratic stability and finite L2 gain ***,the results are extended to piecewise quadratic stability which is much less ...
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ISBN:
(纸本)9781479947249
This paper considers reset controlsystems with output *** present sufficient conditions for the quadratic stability and finite L2 gain ***,the results are extended to piecewise quadratic stability which is much less ***,an iterative algorithm is proposed to design the reset *** the obtained results are given as linear matrix inequalities(LMIs) that can be solved *** examples are given to illustrate the results.
In this paper, a novel real-coded genetic algorithm is presented to generate offspring towards a promising polygon field with k+1 vertex, which represents a set of promising points in the entire population at a partic...
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In this paper, a novel real-coded genetic algorithm is presented to generate offspring towards a promising polygon field with k+1 vertex, which represents a set of promising points in the entire population at a particular generation. A set of 19 test problems available in the global parameter optimization literature is used to test the performance of the proposed real-coded genetic algorithms. Several performance comparisons with five significant real-coded genetic algorithms, three state-of-the-art differential evolution algorithms and three others significant evolutionary computing techniques are performed. The comparative study shows the proposed approach is statistically significantly better than or at least comparable to twelve significant evolutionary computing techniques over a test suite of 19 benchmark functions.
In this paper, we consider the control of large-scale processes with both input and state couplings. A distributed model predictive control(MPC) strategy for tracking based on the reference trajectories is presented. ...
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ISBN:
(纸本)9781479947249
In this paper, we consider the control of large-scale processes with both input and state couplings. A distributed model predictive control(MPC) strategy for tracking based on the reference trajectories is presented. The proposed distributed MPC strategy requires decomposing a large-scale system into several smaller ones and solving convex optimization problems independently. Distributed MPC tracking strategies for unconstrained and constrained processes are presented, respectively. An iterative algorithm is presented to coordinate the distributed MPC controllers. The proposed algorithm is applied to a four-tank process to demonstrate the effectiveness.
In the existing adaptively secure ABE (attribute-based encryption) schemes, the decryption cost goes linearly with the number of attributes that are used in decryption. An adaptively secure key-policy ABE (FKP-ABE) sc...
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As well-known, model predictive control is closely related to optimal control. This paper studies relationships between them and provides a unified framework for optimality analysis of model predictive controllers (MP...
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As well-known, model predictive control is closely related to optimal control. This paper studies relationships between them and provides a unified framework for optimality analysis of model predictive controllers (MPC). The optimality is evaluated by comparing total performance of MPC with finite and infinite horizon optimal cost. Based on relaxed value iteration method, upper and lower bounds of optimality evaluation functions are expressed explicitly in terms of optimization horizon. These results reveal detailed characteristics on performance of closed-loop MPC systems due to using “receding horizon optimization” implementation style.
This paper studies the robust consensus problem for second-order multi-agent systems with nonuniform time-delays and switching topologies in the presence of external disturbances, where each agent has a self-delay and...
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ISBN:
(纸本)9781479938926
This paper studies the robust consensus problem for second-order multi-agent systems with nonuniform time-delays and switching topologies in the presence of external disturbances, where each agent has a self-delay and each delay is independent of each other. A neighbor-based rule is used for the agents with nonuniform time-delays and external disturbances. A sufficient condition is derived under which all agents achieve consensus while satisfying desired H ∞ performance. Finally, the effectiveness of the obtained theoretical results is demonstrated through numerical simulations.
The main objective of this paper is to describe the application of Unscented Kalman Filter (UKF) estimation algorithm to the problem of fault detection and estimation of the sensor failures in the heat exchanger syste...
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The main objective of this paper is to describe the application of Unscented Kalman Filter (UKF) estimation algorithm to the problem of fault detection and estimation of the sensor failures in the heat exchanger systems. The proposed fault detection is based on innovation sequence implementing UKF which is used to generate residuals when a sensor fault is presented. By evaluating the generated residual, it is possible to see if any problems of sensor have occurred. And the estimated state and decision function are built; the indication of sensor malfunction is achieved by UKF, so makes it possible for us to see where the fault is. Experiments in a heat exchanger have demonstrated the power of this method. The proposed algorithm has evident advantages such as less computation, easy programming, easy application and generalization and so on.
The Organic Rankine Cycle (ORC) has attracted a lot of interests for its ability to recover low-grade heat and the possibility to be implemented in decentralized low-capacity power plants. In this paper, a new optimal...
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The Organic Rankine Cycle (ORC) has attracted a lot of interests for its ability to recover low-grade heat and the possibility to be implemented in decentralized low-capacity power plants. In this paper, a new optimal temperature control method is proposed for ORC systems with non-Gaussian disturbances which influence the quality of exhaust gas. The objective here is to control the speed of the pump so that the superheated vapor temperature follows a target one. It means that the error between those two temperatures is minimized both in magnitude and randomness, which are characterized by mean value and entropy, respectively. Therefore, the proposed control strategy is regarded as a multi-objective optimization problem. To solve this problem, a Multi-Objective Estimation of Distribution Algorithm (MOEDA) is adopted to obtain all the possible optimal control inputs. Simulation results show the effectiveness of the proposed technique.
In this paper, the fault classification problem for waste heat recovery system based on support vector machine (SVM) is investigated. Firstly, two-class SVM classification algorithm is reviewed. Then the model and six...
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ISBN:
(纸本)9781479943142
In this paper, the fault classification problem for waste heat recovery system based on support vector machine (SVM) is investigated. Firstly, two-class SVM classification algorithm is reviewed. Then the model and six kinds of faults in waste heat recovery systems (WHRSs) are briefly described. In order to effectively isolate these faults in WHRSs, key features are extracted using principal component analysis (PCA), the multi-class classification problem is then decomposed into five two-class classifiers by using improved one-against-rest approach. Consequently, the SVM classifiers are designed to train and test samples by using collected process variables. The comparison between SVM and back-propagation neural networks applied to a WHRS is discussed. Simulation results demonstrate that SVM can obtain better fault diagnosis performance.
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