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World Congress on Intelligent control and Automation (WCICA)

作者： Na Luo Wei Feng Xiaoqiang Wang Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China

Dynamic optimization has attracted much attention for its wide applications in engineering problems. However, it is still a challenge for high nonlinear, multi-dimensional and multimodal problems. Estimation of Distribution Algorithm was proposed in which probabilistic models extracted relevant features of the complex search space and then generated new individuals during optimization. In order to decrease the dependences among control variables in dynamic optimization, affinity propagation was applied to cluster the individuals in evolutionary iterations. In each cluster, the probabilistic density function of Gaussian mixture model refined the promising spaces with high quality solutions and avoided the random combination of different control variables. To evaluate the performance of the new approach, three dynamic optimization problems of chemical process are used as cases comparing with three state-of-the-art global optimization methods. The results showed that the new approach could achieve the best solution in most cases with less computational effort and higher efficiency.

关键词： Statistics Probabilistic logic optimization Sociology Algorithm design and analysis Robustness Genetic algorithms

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Multi-time Scale Hierarchical Predictive control for Energy Management of Microgrid System with Smart Users

Multi-time Scale Hierarchical Predictive Control for Energy ...

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第26届中国控制与决策会议

作者： Jun Xu Yuanyuan Zou Yugang Niu Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China Univ.of Science and Technology Key Laboratory of System Control and Information Processing Ministry of Education

In this paper, a multi-time scale hierarchal model predictive control strategy is proposed to optimize energy management problem of a microgrid with multiple smart users. According to the power flow among different energy modules, a hierarchical system model and a multi-time scale hierarchal energy optimization management problem are established. The centralized controller in the upper layer is to optimize the charge/discharge time and energy of storage devices, controllable supply power adjustment and dispatch of the aggregators. The optimization problem in the lower layer is to meet users' demands in real time. Meanwhile, in order to improve the disturbances caused by the randomness of renewable energy and variant loads, a multi-time scale optimization scheme is applied. At the slow scale, the upper optimization problem is solved, and the optimal energy scheduling in the long-term can be achieved. At the fast scale, the energy balance between supply and demand of smart users can be realized in the short-term. Finally, simulation results illustrate the effectiveness of proposed method.

关键词： Smart user,Microgrid,Energy management,Multi-time scale time-hierarchal,Model predictive control

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Statistical process monitoring based on improved principal component analysis and its application to chemical processes

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2013年第7期14卷 520-534页

作者： Chu-dong TONG Xue-feng YAN Yu-xin MA Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

In this paper, a novel criterion is proposed to determine the retained principal components (PCs) that capture the dominant variability of online monitored data. The variations of PCs were calculated according to their mean and covariance changes between the modeling sample and the online monitored data. The retained PCs containing dominant variations were selected and defined as correlative PCs (CPCs). The new Hotelling's T2 statistic based on CPCs was then employed to monitor the process. Case studies on the simulated continuous stirred tank reactor and the well-known Tennessee Eastman process demonstrated the feasibility and effectiveness of the CPCs-based fault detection methods.

关键词： Fault detection Principal component analysis (PCA) Correlative principal components (CPCs) Tennessee Eastman process

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Quantized H∞ control for stochastic nonlinear networked systems

Quantized H∞ control for stochastic nonlinear networked sys...

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Chinese control and Decision Conference, CCDC

作者： Huaicheng Yan Hongbo Shi Hao Zhang Haitao Zhao Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education Shanghai 200237 China Tongji University Shanghai Shanghai CN

In this paper, we are concerned with the quantized H ∞ control problem for a class of stochastic systems with random communication delays. The system under consideration involves signals quantization, Itô stochastic disturbance as well as random communication delays. The measured output and the control input quantization are considered simultaneously. We aim at designing an observer-based controller such that the dynamics of the filtering error is guaranteed to be exponentially stable in the mean square, and a prescribed H ∞ disturbance attenuation level is also achieved. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.

关键词： Educational institutions Delays Quantization (signal) Electronic mail Stochastic systems Laboratories optimization

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Stable Distributed Model Predictive control strategy based on agent coordination

Stable Distributed Model Predictive Control strategy based o...

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Chinese control Conference (CCC)

作者： Mengling Wang Hongbo Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai Shanghai CN

Many systems composed by several interacting subsystems are usually controlled by a distributed control framework. Distributed Model Predictive control (DMPC) strategy, in which each subsystem is controlled by a local MPC controller, has advantages of accommodating constraints, less computational cost and high flexibility. In order to improve the global performance and guarantee the system stability, a stabilized DMPC strategy is proposed in this paper, in which subsystems interact through inputs. At first, local initial feasible solutions are achieved based on a Minkowski functional to guarantee the local closed-loop system stabilization. And then the global optimal solutions are obtained through coordination strategy for the sake of reducing iteration time and accelerating the convergence speed efficiently. Finally, the accuracy and efficiency of the proposed scheme is put to test through simulation.

关键词： Cost function Equations Mathematical model Predictive control Stability analysis Trajectory

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Stabilization of LTI Systems over Finite-State Fading Channels

Stabilization of LTI Systems over Finite-State Fading Channe...

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第26届中国控制与决策会议

作者： Nan Xiao Yugang Niu Lihua Xie Key Laboratory of Advanced Control and Optimization for Chemical Process (East China University of Science and Technology) Ministry of Education EXQUISITUS Centre for E-CitySchool of Electrical and Electronic EngineeringNanyang Technological University

ISBN: (纸本)9781479937097

This paper considers the state feedback stabilization over finite-state fading channels, where the stochastic characteristic of time-varying fading channels is assumed to be driven by a finite-state random process. The finite-state process is used to represent different channel fading amplitudes and/or to model different configurations of the overall physical environment. Necessary and sufficient conditions are given for stabilization over finite-state Markov fading *** the case of finite-state i.i.d. fading channels, explicit network requirements for stabilization are presented for both single-input case and multi-input case. Our results cover some existing results as special cases.

关键词： Feedback Stabilization,Finite-State Fading Channels,Networked control

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Optimal control Nodes Selection for Consensus in Multi-agent Systems

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IFAC Proceedings Volumes 2014年第3期47卷 11697-11702页

作者： Wen Yang Xiaofan Wang Hongbo Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology) Ministry of Education Shanghai 200237 Department of Automation Shanghai Jiaotong University Shanghai 200240

In a resource limited multi-agent system, it is of practical importance to select a fraction of nodes (agents) to provide control inputs such that consensus can be achieved with optimized performance in terms of network cost and/or convergence speed. In this paper, we investigate the problem of how to select control nodes so as to minimize the network cost, where the control nodes are selected at the beginning and will be fixed all the time. This problem can be transformed to a combinatorial optimization problem, and further relaxed to a convex optimization problem with reweighted l 1 norm. We propose a suboptimal algorithm to solve the convex optimization problem. Finally, we offer several numerical examples to illustrate the efficiency of the proposed strategies, and investigate the relationship how the degrees of control nodes will influence network cost and convergence speed.

关键词： Node selection Convex optimization Multi-agent systems

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An improved discrete artificial bee colony algorithm for hybrid flow shop problems

Communications in Computer and Information Science

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Communications in Computer and Information Science 2013年 355卷 294-302页

作者： Cui, Zhe Gu, Xingsheng Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai 200237 China

Being a typical NP-hard combinatorial optimization problem, the hybrid flow shop (HFS) problem widely exists in manufacturing systems. In this paper, we firstly establish the model of the HFS problem by employing the vector representation. Then an improved discrete artificial bee colony (IDABC) algorithm is proposed for this problem to minimize the makespan. In the IDABC algorithm, a novel differential evolution and a modified variable neighborhood search are studied to generating new solutions for the employed and onlooker bees. The destruction and construction procedures are utilized to obtain solutions for the scout bees. The simulation results clearly imply that the proposed IDABC algorithm is highly effective and efficient as compared to six state-of-the-art algorithms on the same benchmark instances. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Manufacture

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A Synthesis Approach to Predictive control for Networked control Systems

A Synthesis Approach to Predictive Control for Networked Con...

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第三十三届中国控制会议

作者： Yuanyuan Zou James Lam Yugang Niu Dewei Li Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and Technology Department of Mechanical Engineering The University of Hong Kong Department of Automation Shanghai Jiao Tong University

ISBN: (纸本)9781479947249

This paper studies a synthesis approach to predictive control for networked control systems with data loss and quantization. An augmented Markov jump linear model with polytopic uncertainties is modeled to describe the quantization errors and possible data loss. Based on this model, a predictive control synthesis approach is developed, which involves online optimization of a infinite horizon objective and conditions to deal with system constraints. The proposed MPC algorithm guarantees closed-loop mean-square stability and constraints satisfaction.

关键词： Predictive control,Networked control Systems,Stability

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Receding Horizon control and Scheduling of Quantized control Systems with Communication Constraints

Receding Horizon Control and Scheduling of Quantized Control...

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IEEE Annual Conference on Decision and control

作者： Yuanyuan Zou Yugang Niu Shaoyuan Li Dewei Li Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai 200237 China Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China

ISBN: (纸本)9781467360890

This paper investigates the problem of joint design of a receding horizon control and the medium access scheduling for quantized control systems over limited bandwidth networks, in which only a limited number of actuators are allowed to communicate with the controller at each time instant. By introducing a communication scheduling matrix to describe the medium access status and considering the influence of quantizers, we can model the control system as a switched model with structured norm-bounded uncertainties. The stabilizing channels with guaranteed stability are chosen first. Based on the stabilizing channels, a receding horizon control strategy with optimal dynamic resource allocation is proposed by minimizing the upper bound on a finite-horizon quadratic performance index. Simulation results show the effectiveness of the developed method finally.

关键词： control systems Media Access Horizon quantizer control strategy Stabilising Communication Research Resource utilization actuators quadratic performance index

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