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27th Chinese control and Decision Conference, CCDC 2015

作者： Gu, Xinxin Wen, Jiwei Li, Peng Key Laboratory of Advanced Process Control for Light Industry Ministry of Education School of Internet of Things Engineering Jiangnan University Wuxi China

ISBN: (纸本)9781479970179

This paper mainly studies the continuous-time Markov Jump Linear Systems (MJLSs) problem based on model predictive control (MPC). Sufficient conditions of the optimization problem, which could guarantee the mean square stability of the close-loop MJLS, are given at every sample time. Since the MPC strategy is aggregated into continuous-time MJLSs, a discrete-time controller is employed to deal with a continuous-time plant and the adopted cost function not only refers to the knowledge of system state but also considers the sampling period. In addition, the feasibility of MPC scheme and the mean square stability of the MJLS are deeply discussed by using the invariant ellipsoid. Finally, the main results are verified by a numerical example. © 2015 IEEE.

关键词： Continuous-time Markov jump linear systems Invariant ellipsoid Model predictive control

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Model Predictive control for Continuous-time Markov Jump Linear Systems

Model Predictive Control for Continuous-time Markov Jump Lin...

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第27届中国控制与决策会议

作者： Gu Xinxin Wen Jiwei Peng Li Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) School of Internet of Things EngineeringJiangnan University

ISBN: (纸本)9781479970186

This paper mainly studies the continuous-time Markov Jump Linear Systems(MJLSs) problem based on model predictive control(MPC).Sufficient conditions of the optimization problem,which could guarantee the mean square stability of the close-loop MJLS,are given at every sample *** the MPC strategy is aggregated into continuous-time MJLSs,a discrete-time controller is employed to deal with a continuous-time plant and the adopted cost function not only refers to the knowledge of system state but also considers the sampling *** addition,the feasibility of MPC scheme and the mean square stability of the MJLS are deeply discussed by using the invariant ***,the main results are verified by a numerical example.

关键词： Continuous-time Markov jump linear systems,Model predictive control,Invariant ellipsoid

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Re. ``Discrete Representation of Non-dominated Sets in Multi-objective Linear Programming'' [European Journal of Operational Research 255 (2016) 687–698]

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European Journal of Operational Research 2017年第3期260卷 828-828页

作者： Lizhen Shao Matthias Ehrgott Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 10 0 083 China Department of Management Science Lancaster University Management School Bailrigg Lancaster LA1 4YX United Kingdom

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Neural-observer-based adaptive control for stochastic nonlinear time-delay systems with unknown control directions

Neural-observer-based adaptive control for stochastic nonlin...

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第三十四届中国控制会议

作者： Yu Zhaoxu Li Shugang Li Fangfei Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology Department of Industrial Engineering and Logistics Shanghai Jiao Tong University Department of Mathematics East China University of Science and Technology

ISBN: (纸本)9789881563897

The problem of output feedback adaptive stabilization is addressed for a class of stochastic nonlinear systems with unknown time-varying delays and unknown control directions in this paper. Firstly, the unknown control coefficients are lumped together by using a linear state transformation, and the original system is transformed into a new system for which control design becomes feasible. Then, after the design of a novel neural observer, an output feedback adaptive neural network(NN) controller is developed for such systems by combining the Dynamic Surface control(DSC) technique, the Nussbaum gain function(NGF)method and the Lyapunov-Krasovskii method. The proposed controller ensures that all signals in the closed-loop systems are bounded in probability. Finally, a simulation example is given to verify the effectiveness and applicability of the proposed control design.

关键词： Stochastic systems,output feedback,neural network(NN),unknown control direction,time-varying delay

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Hellinger distance based probability distribution approach to performance monitoring of nonlinear control systems

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Chinese Journal of Chemical Engineering 2015年第12期23卷 1945-1950页

作者：李晨黄彪钱锋 Key Laboratory of Advanced Control and Optimization Ministry of EducationEast China University of Science and Technology Department of Chemical and Materials Engineering University of Alberta

control performance monitoring has attracted great attention in both academia and industry over the past two decades. However, most research efforts have been devoted to the performance monitoring of linear control systems, without considering the pervasive nonlinearities(e.g. valve stiction) present in most industrial control systems. In this work, a novel probability distribution distance based index is proposed to monitor the performance of non-linear control systems. The proposed method uses Hellinger distance to evaluate change of control system performance. Several simulation examples are given to illustrate the effectiveness of the proposed method.

关键词： control performance monitoring Kernel density estimation Hellinger distance Nonlinear system

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Neural-observer-based adaptive control for stochastic nonlinear time-delay systems with unknown control directions 34

Neural-observer-based adaptive control for stochastic nonlin...

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34th Chinese control Conference, CCC 2015

作者： Zhaoxu, Yu Shugang, Li Fangfei, Li Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology Shanghai China Department of Industrial Engineering and Logistics Shanghai Jiao Tong University Shanghai China Department of Mathematics East China University of Science and Technology Shanghai China

ISBN: (纸本)9789881563897

The problem of output feedback adaptive stabilization is addressed for a class of stochastic nonlinear systems with unknown time-varying delays and unknown control directions in this paper. Firstly, the unknown control coefficients are lumped together by using a linear state transformation, and the original system is transformed into a new system for which control design becomes feasible. Then, after the design of a novel neural observer, an output feedback adaptive neural network (NN) controller is developed for such systems by combining the Dynamic Surface control (DSC) technique, the Nussbaum gain function (NGF) method and the Lyapunov-Krasovskii method. The proposed controller ensures that all signals in the closed-loop systems are bounded in probability. Finally, a simulation example is given to verify the effectiveness and applicability of the proposed control design. © 2015 Technical Committee on control Theory, Chinese Association of Automation.

关键词： neural network (NN) output feedback Stochastic systems time-varying delay unknown control direction

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Design and control of a p-xylene oxidation process

Design and control of a p-xylene oxidation process

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作者： Tao, Lili Hu, Zhihua Qian, Feng College of Engineering Shanghai Second Polytechnic University Shanghai201209 China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China

The p-xylene (PX) oxidation process is of great industrial importance because of the strong demand of the global polyester fiber. A steady-state model of the PX oxidation has been studied by many researchers. In our previous work, a novel industrial p-xylene oxidation reactor model using the free radical mechanism based kinetics has been developed. However, the disturbances such as production rate change, feed composition variability and reactor temperature changes widely exist in the industry process. In this paper, dynamic simulation of the PX oxidation reactor was designed by Aspen Dynamics and used to develop an effective plantwide control structure, which was capable of effectively handling the disturbances in the load and the temperature of the reactor. Step responses of the control structure to the disturbances were shown and served as the foundation of the smooth operation and advanced control strategy of this process in our future work. © 2015 Elsevier B.V.

关键词： Oxidation

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Robust optimization for a Multi-Product Integrated Problem of Planning and Scheduling under Products Uncertainty

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Journal of Applied Mathematics and Physics 2015年第1期3卷 16-24页

作者： Mengwen Chen Cuiwen Cao Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China

This paper presents robust optimization models for a multi-product integrated problem of planning and scheduling (based on the work of Terrazas-Moreno & Grossmann (2011) [1]) under products prices uncertainty. With the objective of maximizing the total profit in planning time horizon, the planning section determines the amount of each product, each product distributed to each market, and the inventory level in each manufacturing site during each scheduling time period;the scheduling section determines the products sequence, start and end time of each product running in each production site during each scheduling time period. The uncertainty sets used in robust optimization model are box set, ellipsoidal set, polyhedral set, combined box and ellipsoidal set, combined box and polyhedral set, combined box, ellipsoidal and polyhedral set. The genetic algorithm is utilized to solve the robust optimization models. Case studies show that the solutions obtained from robust optimization models are better than the solutions obtained from the original integrated planning and scheduling when the prices are changed.

关键词： Uncertainty Robust optimization Integrated Problem of Planning and Scheduling GA

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A novel 3-layer mixed cultural evolutionary optimization framework for optimal operation of syngas production in a Texaco coal-water slurry gasifier

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Chinese Journal of Chemical Engineering 2015年第9期23卷 1484-1501页

作者：曹萃文张亚坤于腾顾幸生辛忠李杰 Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology State Key Laboratory of Chemical Engineering East China University of Science and Technology State Key Laboratory of Multiphase Complex Systems Institute of Processing Engineering Chinese Academy of Sciences

Optimizing operational parameters for syngas production of Texaco coal-water slurry gasifier studied in this paper is a complicated nonlinear constrained problem concerning 3 BP(Error Back Propagation) neural networks. To solve this model, a new 3-layer cultural evolving algorithm framework which has a population space, a medium space and a belief space is firstly conceived. Standard differential evolution algorithm(DE), genetic algorithm(GA), and particle swarm optimization algorithm(PSO) are embedded in this framework to build 3-layer mixed cultural DE/GA/PSO(3LM-CDE, 3LM-CGA, and 3LM-CPSO) algorithms. The accuracy and efficiency of the proposed hybrid algorithms are firstly tested in 20 benchmark nonlinear constrained functions. Then, the operational optimization model for syngas production in a Texaco coal-water slurry gasifier of a real-world chemical plant is solved effectively. The simulation results are encouraging that the 3-layer cultural algorithm evolving framework suggests ways in which the performance of DE, GA, PSO and other population-based evolutionary algorithms(EAs) can be improved,and the optimal operational parameters based on 3LM-CDE algorithm of the syngas production in the Texaco coalwater slurry gasifier shows outstanding computing results than actual industry use and other algorithms.

关键词： 3-Layer mixed cultural evolutionary framework Optimal operation Syngas production Coal-water slurry gasifier

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Design and control of a p-xylene oxidation process

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Chinese Journal of Chemical Engineering 2015年第12期23卷 1935-1944页

作者：陶莉莉胡志华钱锋 College of Engineering Shanghai Second Polytechnic University Key laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and Technology

The p-xylene(PX) oxidation process is of great industrial importance because of the strong demand of the global polyester fiber.A steady-state model of the PX oxidation has been studied by many *** our previous work,a novel industrial p-xylene oxidation reactor model using the free radical mechanism based kinetics has been ***,the disturbances such as production rate change,feed composition variability and reactor temperature changes widely exist in the industry *** this paper,dynamic simulation of the PX oxidation reactor was designed by Aspen Dynamics and used to develop an effective plantwide control structure,which was capable of effectively handling the disturbances in the load and the temperature of the *** responses of the control structure to the disturbances were shown and served as the foundation of the smooth operation and advanced control strategy of this process in our future work.

关键词： p-Xylene oxidation Dynamic simulation Aspen Dynamics process design and control

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