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An Improved Output Feedback MPC scheme for Constrained Linear systems

IFAC-PapersOnLine 2017年第1期50卷 15506-15511页

作者： Subramanian, Sankaranarayanan Lucia, Sergio Engell, Sebastian Process Dynamics and Operations Group DortmundTU United States Otto-von-Guericke-University Magdeburg Laboratory for Systems Theory and Automatic Control Institute of Automation Engineering Germany

We propose an output feedback model predictive control (MPC) scheme that is independent of the estimation method employed. The proposed approach is non-conservative by design as the feedback information subject to estimation errors is explicitly considered in the predictions. The proposed scheme is robust to both the plant-model mismatch and the estimation error and avoids the unnecessary conservatism introduced by other existing output feedback MPC approaches in the literature. We achieve this by making use of all the available information at every time-step and formulate a control policy with the assumption that bounds for the estimation error are available at all times. We show that the proposed scheme is recursively feasible and demonstrate its advantages using a double-integrator example. © 2017

关键词： Feedback Errors Estimation Linear systems Model predictive control Predictive control systems Robust control Constrained linear systems Constrained systems Estimation methods Feed back information Multi stage Output feedback Plant model mismatches Robust model predictive control

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Interdependent order allocation in the two-echelon supply chain using agent-based negotiation 36

Interdependent order allocation in the two-echelon supply ch...

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第36届中国控制会议

作者： Jian Wang Huimin Miao System Engineering Institute School of AutomationHuazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Hubei Province Key Laboratory of Systems Science in Metallurgical Process Wuhan University of Science and Technology

ISBN: (纸本)9781538629185

Nowadays,many researches study the negotiation-based order allocation problem in the supply chain environment,aiming to improve the efficiency of the allocation and the profits of the supply chain *** competition and cooperation in supplier’s side are mainly addressed because of independent *** this paper,we analyze an interdependent order allocation problem in a two-echelon supply *** supply chain consists of a manufacturer echelon and a supplier *** to the interdependence,both the competition and cooperation in the manufacturer echelon are *** agent-based negotiation algorithm is developed to support the order allocation process and the conflicts *** show in experiments that orders under various supply chain contexts can be successfully allocated through the algorithm.

关键词： Supply chain system order allocation agent-based negotiation

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Distributed Least Squares Solver for Network Linear Equations

arXiv

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arXiv 2018年

作者： Yang, Tao George, Jemin Qin, Jiahu Yi, Xinlei Wu, Junfeng State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China U.S. Army Research Laboratory AdelphiMD20783 United States Department of Automation University of Science and Technology of China Hefei230027 China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden College of Control Science and Engineering Zhejiang University Hangzhou310027 China

In this paper, we study the problem of finding the least square solutions of over-determined linear algebraic equations over networks in a distributed manner. Each node has access to one of the linear equations and holds a dynamic state. We first propose a distributed least square solver over connected undirected interaction graphs and establish a necessary and sufficient on the step-size under which the algorithm exponentially converges to the least square solution. Next, we develop a distributed least square solver over strongly connected directed graphs and show that the proposed algorithm exponentially converges to the least square solution provided the step-size is sufficiently small. Moreover, we develop a finite-time least square solver by equipping the proposed algorithms with a finite-time decentralized computation mechanism. The theoretical findings are validated and illustrated by numerical simulation examples. Copyright © 2018, The Authors. All rights reserved.

关键词： Linear equations

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Human intention estimation based on hidden Markov model motion validation for safe flexible robotized warehouses

arXiv

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arXiv 2018年

作者： Petković, Tomislav Puljiz, David Marković, Ivan Hein, Björn University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Laboratory for Autonomous Systems and Mobile Robotics Unska 3 ZagrebHR-10000 Croatia Karlsruhe Institute of Technology Institute for Anthropomatics and Robotics Intelligent Process Automation and Robotics Lab Kaiserstraße 12 Deutschland KarlsruheDE-76131

With the substantial growth of logistics businesses the need for larger warehouses and their automation arises, thus using robots as assistants to human workers is becoming a priority. In order to operate efficiently and safely, robot assistants or the supervising system should recognize human intentions in real-time. Theory of mind (ToM) is an intuitive human conception of other humans' mental state, i.e., beliefs and desires, and how they cause behavior. In this paper we propose a ToM based human intention estimation algorithm for flexible robotized warehouses. We observe human's, i.e., worker's motion and validate it with respect to the goal locations using generalized Voronoi diagram based path planning. These observations are then processed by the proposed hidden Markov model framework which estimates worker intentions in an online manner, capable of handling changing environments. To test the proposed intention estimation we ran experiments in a real-world laboratory warehouse with a worker wearing Microsoft Hololens augmented reality glasses. Furthermore, in order to demonstrate the scalability of the approach to larger warehouses, we propose to use virtual reality digital warehouse twins in order to realistically simulate worker behavior. We conducted intention estimation experiments in the larger warehouse digital twin with up to 24 running robots. We demonstrate that the proposed framework estimates warehouse worker intentions precisely and in the end we discuss the experimental results. Copyright © 2018, The Authors. All rights reserved.

关键词： Virtual reality

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A novel tube-based output feedback MPC for constrained linear systems

A novel tube-based output feedback MPC for constrained linea...

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American control Conference

作者： Sankaranarayanan Subramanian Sergio Lucia Sebastian Engell Process Dynamics and Operations Group TU Dortmund Germany Otto-von-Guericke-University Magdeburg Laboratory for Systems Theory and Automatic Control Institute of Automation Engineering Germany

ISBN: (纸本)9781509045839

Model Predictive control (MPC) is an advanced strategy for the control of multi-variable and constrained dynamical systems. Tube-based MPC is a robust control technique that handles uncertainties present in the model. Since full state information is seldom available in practical systems, the estimation error must also be taken into account in addition to model uncertainties to achieve closed-loop stability and constraint satisfaction despite estimation and model errors. In this paper, we propose a novel strategy for the design of a tube-based output feedback MPC which is independent of the estimation method employed. We formulate a control policy by choosing a candidate estimate that is consistent with the reachable sets of the system under control. The proposed method can be combined with any estimation scheme as long as the assumed error bounds are satisfied. We show that the proposed method is recursively feasible, robustly exponentially stable, and performs better than other available strategies.

关键词： Maximum Allowable Concentration Linear system control strategy Output feedback constraint satisfaction problems model error control technology model uncertainty Statistical analysis

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Robust frequency control design on micro-grid with unknown dead-zone nonlinearity

Robust frequency control design on micro-grid with unknown d...

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Youth Academic Annual Conference of Chinese Association of automation (YAC)

作者： Chaoxu Mu Ding Wang Changyin Sun School of Automation Southeast University Nanjing China Tianjin Key Laboratory of Process Measurement and Control Tianjin University Tianjin China The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781538629024

The frequency stability is very critical for the safe operation of power system. Meanwhile, distributed energy storages and unknown governor dead band (GDB) will cause system frequency deterioration when the load-frequency control (LFC) is not able to tackle these uncertainties. The stability of an island smart grid is a challenging topic because the less power sources can be regulated to handle power unbalance. In this paper, a neural network-based adaptive sliding mode controller is designed to be as the load frequency controller for an island smart grid with electrical vehicles (EVs), load disturbances and unknown governor dead band. The on-line neural compensation technology is employed to enable the sliding mode frequency control adaptive, thus the frequency stability of power system is improved. Simulation results on a benchmark island smart grid with governors, micro-turbine, EVs, load changes are provided to illustrate the competitive performance.

关键词： Smart grids Frequency control Power system stability Stability analysis Sliding mode control Biological neural networks Benchmark testing

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A Numerical Implementation of an Extended Luenberger Observer for a Class of Semilinear Hyperbolic PIDEs

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IFAC-PapersOnLine 2016年第8期49卷 216-221页

作者： Deutschmann, Andreas Jadachowski, Lukas Kugi, Andreas Automation and Control Institute Complex Dynamical Systems Group Vienna University of Technology Vienna Austria Christian Doppler Laboratory for Model-Based Process Control in the Steel Industry Vienna University of Technology Vienna Austria

In this paper, an extended Luenberger observer for a class of semilinear hyperbolic PIDEs is proposed to solve the problem of state estimation. The nonlinear observer error dynamics is linearized and then stabilized locally by applying the backstepping method for time-varying linear hyperbolic PIDEs presented recently. Since the resulting kernel equation is computationally quite expensive, a numerical algorithm is proposed to obtain the solution in an efficient way. Finally, this algorithm is applied to an example with multiple equilibrium points, and the influence of the design parameters on the stability is investigated in more detail. © 2016

关键词： Backstepping

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Dead-Time Compensator for Multi Time-delay systems:the Scalar Case

Dead-Time Compensator for Multi Time-delay Systems:the Scala...

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第36届中国控制会议

作者： Pedro Albertos Pedro García Qiang Chen Xiaoli Luan Fei Liu Department of Systems Engineering and Control Instituto de Automática e Informática Industrial Universitat Politècnica de València Key Laboratory of Advance Process Control for Light Industries Institute of Automation Jiangnan University

This paper deals with the control of simple process models where multiple time-delays appear. These delays can be input, output or state delays. For the case of input/output time-delays, a general solution is retrieved from the *** state time-delays, the scalar case is considered and a precompensator is used to cancel the delay. The proposed algorithms are applied to the control of a simple academic example.

关键词： Input/output time-delays State time-delays Unstable delayed systems

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The spectral element method as an efficient tool for transient simulations of hydraulic systems

arXiv

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arXiv 2017年

作者： Mennemann, J.-F. Marko, L. Schmidt, J. Kemmetmüller, W. Kugi, A. Automation and Control Institute Complex Dynamical Systems TU Wien Gusshausstrasse 27-29 Vienna1040 Austria Christian Doppler Laboratory for Model-Based Process Control in the Steel Industry TU Wien Gusshausstrasse 27-29 Vienna1040 Austria

This paper presents transient numerical simulations of hydraulic systems in engineering applications using the spectral element method (SEM). Along with a detailed description of the underlying numerical method, it is shown that the SEM yields highly accurate numerical approximations at modest computational costs, which is in particular useful for optimization-based control applications. In order to enable fast explicit time stepping methods, the boundary conditions are imposed weakly using a numerically stable upwind discretization. The benefits of the SEM in the area of hydraulic system simulations are demonstrated in various examples including several simulations of strong water hammer effects. Due to its exceptional convergence characteristics, the SEM is particularly well suited to be used in real-time capable control applications. As an example, it is shown that the time evolution of pressure waves in a large scale pumped-storage power plant can be well approximated using a low-dimensional system representation utilizing a minimum number of dynamical states. Copyright © 2017, The Authors. All rights reserved.

关键词： Hydraulic equipment

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Neural Adaptive control of Microgrid Frequency Regulation with Wind Power

Neural Adaptive Control of Microgrid Frequency Regulation wi...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Weiqiang Liu Chaoxu Mu Ding Wang Chao Luo Chao Ren Tianjin Key Laboratory of Process Measurement and Control Tianjin University Tianjin China School of Automation Southeast University Nanjing China The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China School of Electrical Engineering Wuhan University Wuhan China

Due to the uncertainty of power load demand and the stochastic power generation from renewable energy, frequency fluctuation becomes a major concern of power system, especially for a microgrid. In this paper, an improved proportional-integral (PI) controller based on the neural adaptive control method is proposed to deal with the load frequency control (LFC) problem in a microgrid with wind power. The designed neural adaptive control auxiliary controller is used to provide the adaptive supplement control signal to PI controller in a real-time manner. Simulation studies on a benchmark microgrid system are carried out between the proposed compound controller and traditional PI controller. The simulation results demonstrate the proposed method has a superior performance for stabilizing the frequency over the traditional PI control under disturbances from the load change and wind power.

关键词： Adaptive control Microgrids Frequency control Wind turbines Benchmark testing Power system stability

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