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A novel hybrid dynamic programming algorithm for a two-stage supply chain scheduling problem

8th International Conference on Learning and intelligent OptimizatioN, LION 2014

作者： Pei, Jun Liu, Xinbao Fan, Wenjuan Pardalos, Panos M. Liu, Lin School of Management Hefei University of Technology Hefei 230009 China Center for Applied Optimization Department of Industrial and Systems Engineering University of Florida Gainesville FL 32601 United States Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education Hefei 230009 China Department of Computer Science North Carolina State University Raleigh NC 27695-7534 United States

ISBN: (纸本)9783319095837

This study addresses a two-stage supply chain scheduling problem, where the jobs need to be processed on the manufacturer's serial batching machine and then transported by vehicles to the customer for further processing. The size and processing time of the jobs are varying due to the differences of types, and setup time is needed before processing one batch. For the problem with minimizing the makespan, we formalize it as a mixed integer programming model. In addition, the structural properties and lower bound of the problem are provided. Based on the analysis above, a novel hybrid dynamic programming algorithm, combining dynamic programming and heuristics, is proposed to solve the problem. Furthermore, its time complexity is also analyzed. By comparing the experimental results of our proposed algorithm with the heuristics B F F and L F F , we demonstrate that our proposed algorithm has better performance and can solve the problem in a reasonable time. © 2014 Springer International Publishing.

关键词： Dynamic programming

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Identification of Linear Parameter Varying systems with Missing Output Data Using Generalized Expectation-Maximization Algorithm

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IFAC Proceedings Volumes 2014年第3期47卷 9364-9369页

作者： X. Yang W. Xiong B. Huang H. Gao Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin Heilongjiang 150080 China Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Jiangnan University Wuxi Jiangsu 214122 China Department of Chemical and Materials Engineering University of Alberta Edmonton Alberta T6G 2G6 Canada Research Institute of Mechatronics and Automation Bohai University Jinzhou 121013 China and Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin Heilongjiang 150080 China

This paper is concerned with the identification problems of linear parameter varying (LPV) systems with randomly missing output data. Since one local linearized model cannot capture the global dynamics of the nonlinear industrial process, the multiple-model LPV model in which the global model is constructed by smoothly weighted combination of multiple local models is considered here. The problem of missing output variables data is commonly encountered in practice. In order to handle the multiple-model identification problems of LPV systems with incomplete data, the local model is taken to have a finite impulse response (FIR) model structure and the generalized expectation-maximization (EM) algorithm is adopted to estimate the unknown parameters of the global LPV model. To avoid the problems of ill-conditioned matrices and high sensitivity of parameters to noise, the prior information on the coefficients of each local FIR model is employed to construct the prior probability of unknown parameters. Then the maximum a posteriori (MAP) estimates of the global model parameters are derived via the generalized EM algorithm. The numerical example is presented to demonstrate the effectiveness of the proposed method.

关键词： Linear parameter varying systems Generalized EM algorithm Missing output data Maximum a posteriori estimates

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Setpoints Compensation in Industrial processes via Multirate Output Feedback Control

Setpoints Compensation in Industrial Processes via Multirate...

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9th Asian Control Conference (ASCC)

作者： Yin, Shen Liu, Fangzhou Gao, Huijun Qiu, Jianbin Chai, Tianyou Fan, Jialu Karimi, Hamid Reza Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin 150080 China State Key Laboratory for Synthetical Automation of Process Industries Northeastern University Shenyang 110004 China Department of Engineering University of Agder Grimstad N-4898 Norway

ISBN: (纸本)9781467357692;9781467357678

This paper investigates the setpoints compensation for a class of complex industrial processes. Plants at the device layer are controlled by the local regulation controllers, and a multirate output feedback control approach for setpoint compensation is proposed such that the subsystems can reach the dynamically changed setpoints and the given economic objective can also be tracked via certain economic performance index (EPI). First, a sampled-data multivariable direct output feedback proportional integral (PI) controller is designed to regulate the performance of the subsystems. Second, the outputs and control inputs of the plants at the device layer are sampled at operation layer sampling time to form an EPI. Thus the multirate problem is solved by a lifting method. Third, static setpoints are generated by real time optimization (RTO) and the dynamic setpoints are calculated by the compensator according to the error between the EPI and objective at each operation layer step. Finally, a rougher flotation process model is employed to demonstrate the effectiveness of the proposed method.

关键词： PI control compensation complex networks control system synthesis feedback multivariable control systems optimisation process control sampled data systems

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Fuzzy modeling of activated sludge wastewater treatment processes and predictive control of dissolved oxygen

Fuzzy modeling of activated sludge wastewater treatment proc...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Ting Yang Lixian Zhang Mohammed Chadli Research Center of Intelligent Control and Systems Harbin Institute of Technology Harbin Heilongjiang China Process System Engineering Laboratory MIT USA Laboratory of Modeling Information and Systems University of Picardie Jules Verne Amiens France

ISBN: (纸本)9781467351942

In this paper, the problems of fuzzy modeling of activated sludge wastewater treatment processes and predictive control of dissolved oxygen are investigated. A structure identification algorithm is proposed, by which the structure of the fuzzy rules can be constructed according to the Activated Sludge Model No.1 (ASM1). Utilizing the fuzzy c-means cluster algorithm, the required fuzzy space of input variables is derived and the consequent parameters are identified using the method of least squares. Based on the obtained fuzzy model, the control signal is formulated by solving a convex optimization problem such that the dissolved oxygen concentration in an aerobic reactor of the wastewater treatment plant can be maintained at the set-point. Compared with the traditional PID control, the proposed fuzzy modelbased predictive control paradigm achieves satisfactory benefits in terms of both transient and steady performance.

关键词： Predictive models Wastewater treatment Predictive control Mathematical model Data models Inductors

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Robust filtering for systems with state-dependent uncertainties and application to a class of tunnel diode circuits

Robust filtering for systems with state-dependent uncertaint...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Lixian Zhang Ting Yang Xudong Zhao Yanzheng Zhu Process System Engineering Laboratory MIT USA Research Center of Intelligent Control and Systems Harbin Institute of Technology Harbin Heilongjiang China College of Information and Control Engineering China University of Petroleum Qingdao China

ISBN: (纸本)9781467351942

The paper is concerned with the problem of robust filtering for a class of systems with state-dependent uncertainties and energy-bounded disturbance. The state-dependent uncertainties can more precisely describe many practical dynamic systems with parameters varying with system states, such as spring stiffness, nonlinear resistor and friction coefficient. A non-quadratic Lyapunov function is adopted, upon which the sufficient condition for the filtering performance analysis is first derived. Then, the parameter-dependent full-order filter is designed such that the corresponding filtering error system is globally asymptotically stable and guarantees a noise attenuation performance index. A numerical example of a class of tunnel diode circuit systems is provided to show the effectiveness of the derived theoretical results.

关键词： Uncertainty Noise Attenuation Performance analysis Symmetric matrices Robustness Uncertain systems

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Forecasting time series with a logarithmic model for the Polynomial Artificial Neural Networks

Forecasting time series with a logarithmic model for the Pol...

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International Joint Conference on Neural Networks (IJCNN)

作者： J. C. Luna-Sanchez E. Gomez-Ramirez K. Najim E. Ikonen Intelligent Systems Group Faculty of Engineering La Salle University Mexico D.F. Mexico Process Control Laboratory ENSIACET Toulouse France Department of Process and Environmental engineering Systems Engineering Laboratory University of Oulu Oulu Finland

The adaptation made for the Polynomial Artificial Neural Networks (PANN) using not only integer exponentials but also fractional exponentials, have shown evidence of its better performance, especially, when it works with non-linear and chaotic time series. In this paper we show the comparison of the PANN improved model of fractional exponentials with a new logarithmic model. We show that this new model have even better performance than the last PANN improved model.

关键词： Mathematical model Modeling Polynomials Genetic algorithms Time series analysis Training Artificial neural networks

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INS/EKF-based stride length, height and direction intent detection for walking assistance robots

INS/EKF-based stride length, height and direction intent det...

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IEEE International Conference on Rehabilitation Robotics (ICORR)

作者： Dario Brescianini Jun-Young Jung In-Hun Jang Hyun Sub Park Robert Riener Department of Mechanical and Process Engineering ETH Zurich Zurich Switzerland Department of Intelligent Robotics University of Science and Technology Daejeon South Korea Division of Applied Robot Technology Korea Institute of Industrial and Technology Ansan South Korea Spinal Cord Injury Center University Hospital Balgrist Zurich Switzerland Sensory-Motor Systems Laboratory Institute of Robotics and Intelligent Systems ETH Zurich Zurich Switzerland

We propose an algorithm used to obtain the information on stride length, height difference, and direction based on user's intent during walking. For exoskeleton robots used to assist paraplegic patients' walking, this information is used to generate gait patterns by themselves in on-line. To obtain this information, we attach an inertial measurement unit(IMU) on crutches and apply an extended kalman filter-based error correction method to reduce the phenomena of drift due to bias of the IMU. The proposed method is verifed in real walking scenarios including walking, climbing up-stairs, and changing direction of walking with normal.

关键词： Legged locomotion Trajectory Exoskeletons Navigation Measurement uncertainty Robot sensing systems

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Superparamagnetic photosensitive polymer nanocomposite for microactuators

Superparamagnetic photosensitive polymer nanocomposite for m...

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TRANSDUCERS 2009 - 15th International Conference on Solid-State Sensors, Actuators and Microsystems

作者： Suter, M. Graf, S. Ergeneman, O. Schmid, S. Camenzind, A. Nelson, B.J. Hierold, C. Micro and Nanosystems Department of Mechanical and Process Engineering ETH Zurich Switzerland Institute of Robotics and Intelligent Systems Department of Mechanical and Process Engineering ETH Zurich Switzerland Particle Technology Laboratory Department of Mechanical and Process Engineering ETH Zurich Switzerland

ISBN: (纸本)9781424441938

We present a photosensitive polymer composite with superparamagnetic characteristics for the fabrication of microactuators. A uniform distribution of particles in the photosensitive polymer matrix SU-8 is achieved by applying superparamagnetic nanoparticles with the aid of a surfactant. The composite contains Fe3O4 nanoparticles up to 3 vol.% (12 wt.%) with diameters of around 13 nm. Superparamagnetic composite microcantilevers are successfully fabricated and actuated in resonance by the magnetic field of an external coil. ©2009 IEEE.

关键词： Magnetite

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Classes of optimal network topologies under multiple efficiency and robustness constraints

Classes of optimal network topologies under multiple efficie...

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IEEE International Conference on systems, Man and Cybernetics

作者： Sanket Patil Srinath Srinivasa Venkat Venkatasubramanian Open Systems Laboratory International Institute of Information Technology Bangalore India Laboratory for Intelligent Process Systems School of Chemical Engineering Purdue University West Lafayette IN USA

We address the problem of designing optimal network topologies under arbitrary optimality requirements. Using three critical system parameters, efficiency, robustness and cost, we evolve optimal topologies under different environmental conditions. Two prominent classes of topologies emerge as optimal: (1) Star-like topologies, with high efficiency, high resilience to random failures and low cost, and (2) ¿Circular Skip Lists¿ (CSL), with high robustness to random failures as well as targeted attacks, and high efficiency at moderate cost. We analyze CSLs to observe that they show several structural motifs that are optimal with respect to a variety of metrics.

关键词： Network topology Robustness DH-HEMTs Telecommunication traffic Resilience Cost function USA Councils Laboratories intelligent networks Circuits

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Bayesian inference for fault-tolerant control

Bayesian inference for fault-tolerant control

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International Symposium on Resilient Control systems, ISRCS

作者： Kris Villez Venkat Venkatasubramanian Shankar Narasimhan Laboratory of Intelligent Process Systems (LIPS) School of Chemical Engineering Purdue University West Lafayette IN USA Department of Chemical Engineering Indian Institute of Technology Madras Chennai India

In this contribution, we present initial developments in view of model-based fault-tolerant control (FTC). In this context, we use an original method based on the Kalman-filter by which fault detection, diagnosis and accommodation is possible provided that an accurate model is available. Since this is not generally true, we attempt to alleviate this necessity by means of accounting for uncertainty, in both model as well as in the measurements used for fault diagnosis. Our preliminary results are focused on the diagnosis step in the FTC scheme.

关键词： Bayesian methods Fault tolerance Fault diagnosis Feeds Fault detection Uncertainty Fault tolerant systems Inductors Actuators Chemical engineering

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