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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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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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A new improved Alopex-based evolutionary algorithm and its application to parameter estimation

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Journal of Central South University 2013年第1期20卷 123-133页

作者：桑志祥李绍军董跃华 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education (East China University of Science and Technology)

In this work, focusing on the demerit of AEA (Alopex-based evolutionary algorithm) algorithm, an improved AEA algorithm (AEA-C) which was fused AEA with clonal selection algorithm was proposed. Considering the irrationality of the method that generated candidate solutions at each iteration of AEA, clonal selection algorithm could be applied to improve the method. The performance of the proposed new algorithm was studied by using 22 benchmark functions and was compared with original AEA given the same conditions. The experimental results show that the AEA-C clearly outperforms the original AEA for almost all the 22 benchmark functions with 10, 30, 50 dimensions in success rates, solution quality and stability. Furthermore, AEA-C was applied to estimate 6 kinetics parameters of the fermentation dynamics models. The standard deviation of the objective function calculated by the AEA-C is 41.46 and is far less than that of other literatures' results, and the fitting curves obtained by AEA-C are more in line with the actual fermentation process curves.

关键词： Alopex evolutionary algorithm Alopex-based evolutionary algorithm clone selection parameter estimation

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Synchronization of heterogeneous dynamical networks via distributed impulsive control

Synchronization of heterogeneous dynamical networks via dist...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Wangli He Qing-Long Han Feng Qian The Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Centre for Intelligent and Networked Systems Central Queensland University

ISBN: (纸本)9781479940318

This paper studies global synchronization between a heterogeneous dynamical network and a known target trajectory via distributed impulsive control. Synchronization with an error level, called quasi-synchronization, is analyzed by utilizing the time-varying Lyapunov function. Some sufficient quasi-synchronization conditions are presented and explicit expressions of error levels are derived. Furthermore, the effects of the pinning control matrix and the coupling strength are explored. Unlike the continuous pinning feedback control, it is shown that a large coupling strength will destroy synchronization in the present of impulsive controller, which is also verified by our simulations.

关键词： Lyapunov methods distributed control interconnected systems matrix algebra time-varying systems trajectory control coupling strength distributed impulsive control global synchronization heterogeneous dynamical network pinning control matrix quasisynchronization target trajectory time-varying Lyapunov function Couplings Educational institutions Eigenvalues and eigenfunctions Symmetric matrices Synchronization Trajectory

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Adaptive neural control for pure-feedback nonlinear time-delay systems with unknown dead-zone: a Lyapunov-Razumikhin method

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控制理论与应用（英文版） 2013年第1期11卷 18-26页

作者： Zhaoxu YU Jianxu LUO Ji LIU Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

This paper addresses the problem of adaptive neural control for a class of uncertain pure-feedback nonlinear systems with multiple unknown state time-varying delays and unknown dead-zone. Based on a novel combination of the Razumikhin functional method, the backstepping technique and the neural network parameterization, an adaptive neural control scheme is developed for such systems. All closed-loop signals are shown to be semiglobally uniformly ultimately bounded, and the tracking error remains in a small neighborhood of the origin. Finally, a simulation example is given to demonstrate the effectiveness of the proposed control schemes.

关键词： Pure-feedback nonlinear systems Adaptive neural control Razumikhin functional Time-delay Deadzone

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chemical process dynamic optimization based on hybrid differential evolution algorithm integrated with Alopex

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Journal of Central South University 2013年第4期20卷 950-959页

作者：范勤勤吕照民颜学峰郭美锦 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education (East China University of Science and Technology)

To solve dynamic optimization problem of chemical process (CPDOP), a hybrid differential evolution algorithm, which is integrated with Alopex and named as Alopex-DE, was proposed. In Alopex-DE, each original individual has its own symbiotic individual, which consists of control parameters. Differential evolution operator is applied for the original individuals to search the global optimization solution. Alopex algorithm is used to co-evolve the symbiotic individuals during the original individual evolution and enhance the fitness of the original individuals. Thus, control parameters are self-adaptively adjusted by Alopex to obtain the real-time optimum values for the original population. To illustrate the whole performance of Alopex-DE, several varietal DEs were applied to optimize 13 benchmark functions. The results show that the whole performance of Alopex-DE is the best. Further, Alopex-DE was applied to solve 4 typical CPDOPs, and the effect of the discrete time degree on the optimization solution was analyzed. The satisfactory result is obtained.

关键词： evolutionary computation dynamic optimization differential evolution algorithm Alopex algorithm self-adaptivity

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Unbiased Minimum-Variance Filtering for Systems with Randomly Multi-Step Sensor Delays

Unbiased Minimum-Variance Filtering for Systems with Randoml...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Yilian Zhang Fuwen Yang Qing-Long Han Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Centre for Intelligent and Networked Systems Central Queensland University

ISBN: (纸本)9781479940318

In this paper, a linear unbiased minimum-variance filtering problem is considered for a class of systems with randomly multi-step sensor delays. A new mathematical model is established for the multi-step sensor delays. Different from the augmented method for dealing with delayed systems, a linear unbiased minimum-variance filter design method is proposed without augmenting the state vector, which effectively reduces the filter dimensions. A recursive algorithm for calculating the filter gain matrix is developed. The simulation results illustrate the effectiveness of the proposed method.

关键词： Networked control systems Filtering Recursive estimation Kalman filters Delay systems Stochastic processes Sensor system Communication networks

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H∞ controller design of event-triggered networked control systems

H∞ controller design of event-triggered networked control s...

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International Conference on Mechatronics and control (ICMC)

作者： Sheng Yan Huaicheng Yan Hongbo Shi Hao Zhang Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai China Department of Control Theory and and Engineering Tongji University Shanghai China

ISBN: (纸本)9781479925391

This paper deals with H ∞ controller design problem for event-triggered networked control systems (NCSs), where the next task release time and finishing time are predicted based on the sampled states. A new model of NCSs that involves the network conditions, state and event-triggered communication strategy is proposed. Based on this model, some novel criteria for the asymptotic stability analysis and H ∞ state feedback controller design of the event-triggered NCSs with time-varying delay are established to guarantee a prescribed H ∞ disturbance rejection attenuation level. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method.

关键词： Delays State feedback Networked control systems Actuators Stability analysis control design

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