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Asian control Conference

作者： Haijuan Zhao Yugang Niu Yuanyuan Zou The Key Laboratory of Advanced Control and Optimization for Chemical Process East China University of Science and Technology Key Laboratory of System Control and Information Processing Department of Automation Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781728102634

This paper is concerned with the sliding mode control (SMC) problem for a class of uncertain switched systems subject to partly known sojourn probabilities. The sojourn probability is the probability of a switched system staying in each subsystem, which may be available or unavailable. A key issue is how to design a sliding mode controller to guarantee the stability performance of the reconstructed switched systems subject to the partly known sojourn probabilities. To this end, by using a set of stochastic variables, the switched system model is reconstructed with partly known sojourn probabilities. And then, the sliding mode control law is constructed to ensure the reachability of the designed common sliding surface. Furthermore, the sufficient condition is derived to ensure the mean-square stability of the closed-loop system under the partly unknown sojourn probabilities. Finally, a numerical example is provided to illustrate the proposed method.

关键词： Switched systems Switches Closed loop systems Stability analysis Sliding mode control Trajectory

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When autonomous systems meet accuracy and transferability through AI: A survey

arXiv

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arXiv 2020年

作者： Zhang, Chongzhen Wang, Jianrui Yen, Gary G. Zhao, Chaoqiang Sun, Qiyu Tang, Yang Qian, Feng Kurths, Jürgen Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China School of Electrical and Computer Engineering Oklahoma State University StillwaterOK74075 United States Potsdam Institute for Climate Impact Research Potsdam14473 Germany Institute of Physics Humboldt University of Berlin Berlin12489 Germany

With widespread applications of artificial intelligence (AI), the capabilities of the perception, understanding, decision-making and control for autonomous systems have improved significantly in the past years. When autonomous systems consider the performance of accuracy and transferability, several AI methods, like adversarial learning, reinforcement learning (RL) and meta-learning, show their powerful performance. Here, we review the learning-based approaches in autonomous systems from the perspectives of accuracy and transferability. Accuracy means that a well-trained model shows good results during the testing phase, in which the testing set shares a same task or a data distribution with the training set. Transferability means that when a well-trained model is transferred to other testing domains, the accuracy is still good. Firstly, we introduce some basic concepts of transfer learning and then present some preliminaries of adversarial learning, RL and meta-learning. Secondly, we focus on reviewing the accuracy or transferability or both of them to show the advantages of adversarial learning, like generative adversarial networks (GANs), in typical computer vision tasks in autonomous systems, including image style transfer, image super-resolution, image deblurring/dehazing/rain removal, semantic segmentation, depth estimation, pedestrian detection and person re-identification (re-ID). Then, we further review the performance of RL and meta-learning from the aspects of accuracy or transferability or both of them in autonomous systems, involving pedestrian tracking, robot navigation and robotic manipulation. Finally, we discuss several challenges and future topics for using adversarial learning, RL and meta-learning in autonomous systems. Copyright © 2020, The Authors. All rights reserved.

关键词： Reinforcement learning

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Sliding Mode control for Networked control System Under Fading Channels

Sliding Mode Control for Networked Control System Under Fadi...

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control Technology and Applications (CCTA),

作者： Jiarui Li Yugang Niu Yuanyuan Zou Key Laboratory of Advanced Control and optimization for Chemical Process (East China University of Science and Technology) Ministry of Education Shanghai China Department of Automation Shanghai Jiao Tong University Shanghai China

In this work, the discrete-time sliding mode control problem for the networked control systems under fading channels is investigated. Moreover, the state signals will be quantized through a logarithmic quantizer before transmitted to the controller. Subsequently, a sliding surface relating to fading coefficient is designed to cope with the fading measurements. It is shown that the designed sliding mode controller can drive the state trajectories into the neighborhood of the specified sliding surface and the closed-loop system is asymptotically stable in the sense of mean square. In the end, a numerical simulation is given.

关键词： Fading channels Quantization (signal) Symmetric matrices Sliding mode control Closed loop systems Lyapunov methods Networked control systems

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Sliding Mode control of State-Saturated Systems Under Dynamic Event-Triggered Protocol

Sliding Mode Control of State-Saturated Systems Under Dynami...

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Asian control Conference

作者： Jun Song Yugang Niu Bei Chen The Key Laboratory of Advanced Control and Optimization for Chemical Process East China University of Science and Technology Shanghai China School of Electric and Electronic Engineering Shanghai University of Engineering Science Shanghai China

ISBN: (纸本)9781728102634

This paper endeavors to investigate the sliding mode control (SMC) issue of the networked state-saturated systems. For the energy saving purpose in network communication, a dynamic event-triggering mechanism is employed to SMC design by introducing interval dynamic variable. With the aid of some appropriate Lyapunov functionals, the sufficient conditions are derived to ensure the asymptotic stability of the sliding mode dynamics and the reachability of the specified sliding surface. Moreover, a convex optimization algorithm is formulated to solve the dynamic event-triggering SMC law. Finally, a numerical example is provided to illustrate the effectiveness of the proposed results.

关键词： Zirconium Heuristic algorithms Symmetric matrices Sliding mode control Asymptotic stability Protocols Nonlinear dynamical systems

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Oriented PLDL Nanofibers

Oriented PLDL Nanofibers

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Microelectronics Technology and Devices (SBMicro)

作者： Nayara M. da S. Carvalho Marcele F. Passos Maria Regina W. Maciel Rubens Maciel Filho Rogerio Furlan Laboratory of Optimization Design and Advanced Process Control School of Chemical Engineering University of Campinas Campinas Brazil National Institute of Biofabrication School of Chemical Engineering University of Campinas Campinas Brazil Department of Physics and Electronics University of Puerto Rico at Humacao Humacao Puerto Rico

In this work, we present novel results of poly (Lco-D, L lactic acid) (PLDL) nanofibers deposited using a nonconventional electrospinning process. It allows to obtain fibers with vertical and horizontal alignment simultaneously. Extending the deposition time, a membrane-like structure with oriented fibers can be collected that is a prospective material for biomedical applications. Fibers with a higher concentration of PLDL, dissolved in chloroform and acetone, resulted in well-formed fibers with small diameters (600 nm to 710 nm).

关键词： Electrodes Optical fiber devices Optical fiber polarization Plastics Tissue engineering Silicon Chlorine compounds

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Dynamic optimization of Chemical processes using Symbiotic Organisms Search Algorithm

Dynamic Optimization of Chemical Processes using Symbiotic O...

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Chinese Automation Congress (CAC)

作者： Peng Tian Xu Chen Wenxiang Zhao Wenli Du School of Electrical and Information Engineering Jiangsu University Zhenjiang Jiangsu China Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai China

Chemical process optimization problems are often modeled as dynamic optimization problems (DOPs). Due to the nonlinear, multimodal and multi-dimensional nature of DOPs, efficient solution of DOPs is a very challenging task. In this paper, a new intelligent search algorithm called symbiotic organisms search (SOS) is proposed for tackling the chemical DOPs. SOS mainly mimics three symbiotic relationships in ecosystem, namely mutualism, commensalism and parasitism, to perform global search. In addition, compared with previous intelligent search algorithms, SOS has the advantages of no tuning parameters, easy to implement and high performance. Combined with control vector parameterization, the proposed SOS is applied to solve five chemical DOPs with different levels of complexity. Simulation results show that SOS can achieve solutions with accuracy comparable to those methods in the literature, and thus can be regarded as an effective tool for the chemical DOPs.

关键词： optimization Heuristic algorithms Chemicals Symbiosis Sociology Statistics Organisms

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Predictive control for Continuous Stirred Tank Reactors

Predictive Control for Continuous Stirred Tank Reactors

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2019 International Conference on Informatics, control and Robotics 2019信息学、控制和机器人学国际会议(ICICR2019)

作者： Ioana NASCU Ioan NASCU Wen-li DU Sai GU Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Department of Chemical and Process Engineering University of Surrey Department of Automation Technical University of Cluj-Napoca

The paper focuses on the implementation of a model based predictive control(MBPC) method, for Continuous Stirred Tank Reactors. First, the modelling problem of a single irreversible exothermic reaction, taking place in a perfectly mixed continuously stirred tank reactor(CSTR) is presented. The dynamic model consists of differential material and energy balance equations. The control strategy is investigated and evaluated by performing simulations and analyzing the results. The disturbance rejection capacity of the control system(regulatory control performances) have been tested and compared with those obtained using a classical Proportional Integral Derivative(PID) based controller. The results show that this control strategy has good performances and can be efficiently used to control the CSTR.

关键词： Predictive control PID control Chemical reactor process model

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A data-approach for industrial utility systems optimization under uncertainty

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Energy 2019年 182卷 559-569页

作者： Zhao, Liang You, Fengqi Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China Robert Frederick Smith School of Chemical and Biomolecular Engineering Cornell University IthacaNY14853 United States

Energy optimization of utility system helps to reduce the operating cost and save energy for the industrial plants. Widespread uncertainties such as device efficiency and process demand pose new challenges for this issue. A hybrid modeling framework is presented by introducing the operating data into mechanism model to adapt the changes of device efficiency and operating conditions. Mathematical models of boilers, steam turbines, and letdown valves are then developed in the framework. Based on the process historical data of a real-world plant, a Dirichlet process mixture model is used to capture the support information of uncertain parameters. Bridging data-driven robust optimization (DDRO) and utility system optimization under uncertainty, a robust mixed-integer nonlinear programming (MINLP) model is developed by utilizing the derived uncertainty set. The robust counterpart of the developed model can be reformulated as a tractable MINLP problem including conic quadratic constraints that could be solved efficiently. A real-world case study is carried out to demonstrate the effectiveness of the proposed approach in protecting against uncertainties and achieving a good trade-off between optimality and robustness of the operational decisions for industrial utility systems. © 2019 Elsevier Ltd

关键词： Boilers

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Performance monitoring of non-gaussian chemical processes with modes-switching using globality-locality preserving projection

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Frontiers of Chemical Science and Engineering 2017年第3期11卷 429-439页

作者： Xin Peng Yang Tang Wenli Du Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai 200237 China

In this paper, we propose a novel performance monitoring and fault detection method, which is based on modified structure analysis and globality and locality preserving （MSAGL） projection, for non-Gaussian processes with multiple operation conditions. By using locality preserving projection to analyze the embedding geometrical manifold and extracting the non-Gaussian features by independent component analysis, MSAGL preserves both the global and local structures of the data simultaneously. Furthermore, the tradeoff parameter of MSAGL is tuned adaptively in order to find the projection direction optimal for revealing the hidden structural information. The validity and effectiveness of this approach are illustrated by applying the proposed technique to the Tennessee Eastman process simulation under multiple operation conditions. The results demonstrate the advantages of the proposed method over conventional eigendecomposition-based monitoring methotis.

关键词： non-Gaussian processes subspace projection independent component analysis locality preserving projection finite mixture model

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A novel hybrid estimation of distribution algorithm for solving hybrid flowshop scheduling problem with unrelated parallel machine

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Journal of Central South University 2017年第8期24卷 1779-1788页

作者：孙泽文顾幸生 Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education(East China University of Science and Technology)Shanghai 200237China

The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.

关键词： hybrid estimation of distribution algorithm teaching learning based optimization strategy hybrid flow shop unrelated parallel machine scheduling

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