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Robust Model Predictive control: Implementation Issues with Comparative Analysis

Robust Model Predictive Control: Implementation Issues with ...

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Joint Meeting of the 2nd ifac Workshop on Linear Parameter Varying systems (LPVS) / 9th ifac symposium on Robust control Design (ROCOND)

作者： Gesser, Rodrigo S. Lima, Daniel M. Normey-Rico, Julio E. Univ Fed Santa Catarina Dept Automacao & Sistemas Florianopolis SC Brazil Univ Fed Santa Catarina Dept Engn Blumenau SC Brazil

Robust Model Predictive control (RMPC) is related to a variety of methods designed to guarantee control performance using optimization algorithms while considering systems with uncertainties. Many RMPC methods were created with different formulations, however there is lack of studies comparing their performances using pre-established metrics. Thus, the objective of this paper is to analyze and compare different RMPC methods using a Continuous Stirred Tank Reactor (CSTR) plant with parametric uncertainties as a case of study. The methods are sorted by Min-max MPC, Tube-based MPC and LMI-based MPC, which were carefully chosen based on their relevance in the current literature. The metrics used to compare the methods are separated in off-line, related to configuration of the controller prior to its use, and on-line, which are related to the computational cost of the algorithm and difficulties that may arise during its application. Based on simulation results, it will be shown that the LMI-based methods are slower for calculating the control signal, but are easier to implement. Whereas, both Min-max and Tube-based methods require calculation of robust control invariant sets which might be difficult for more complex systems, however they are much faster when comparing to LMI. (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Robust control Model Predictive control Uncertainty

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Reliability Analysis of CVCS with Extended GO-FLOW Methodology by Considering Automatic control Functions

Reliability Analysis of CVCS with Extended GO-FLOW Methodolo...

引用

10th International-Federation-of-Automatic-control (ifac) symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)

作者： Lu Hongxing Yang Ming Li Wei Dai Xinyu Yang Jun Yoshikawa, Hidekazu Harbin Engn Univ Coll Nucl Sci & Technol Harbin Heilongjiang Peoples R China South China Univ Technol Sch Elect Power Guangzhou Guangdong Peoples R China NPIC Cengdu Sichuan Peoples R China

Automatic control System (ACS) has been more widely applied in nuclear power plants (NPP) in order to achieve better performance, convenience and economics. Some new challenges are also emerging in reliability analysis of ACS because of its complexity and strict regulatory requirements of NPP. The dynamic behavior of ACS is difficult to be expressed by traditional system reliability analysis techniques such as fault tree analysis and/or event tree which are widely applied for probabilistic safety assessment in NPPs. This paper presents an extended GO-FLOW methodology by introducing several supplementary operators for modelling control logic generally used in NPP systems. A Chemical and Volume control System (CVCS) in Pressurized Water Reactor (PWR) NPP is taken as an example to demonstrate the usage of improved GO-FLOW methodology in modeling and reliability estimation of a process system coupled with automatic control functions. (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Dynamic modeling Probabilistic models Safety analysis ACS analysis GO-FLOW

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Data-driven System Identification of an Innovation Community Model

Data-driven System Identification of an Innovation Community...

引用

16th ifac symposium on Information control Problems in Manufacturing (INCOM)

作者： Olcay, Ertug Dengler, Christian Lohmann, Boris Tech Univ Munich Dept Mech Engn Chair Automat Control Boltzmannstr 15 D-85748 Garching Germany

With the growing global competition, the importance of innovations for the success of many companies is increasing significantly. An important concept in an innovation process is the innovation communities, which develop and implement innovative ideas. The modeling of such non-physical systems is not a simple task. However, this can be performed with the agent based modeling technique in a more natural way than by differential equations. Unfortunately, the resulting agent-based model is not well-suited for control design. By using input and output data, it is possible to approximate an agent-based model as a Takagi-Sugeno (TS) fuzzy model. In this work, approximation of an agent-based model as a TS fuzzy model is presented. (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： System Identification Multi-Agent Simulation Model-Based Planning

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modelling of Rail Guided Vehicles serving an automated parts-to-picker system

Modelling of Rail Guided Vehicles serving an automated parts...

引用

16th ifac symposium on Information control Problems in Manufacturing (INCOM)

作者： Martina, Calzavara Alessandro, Persona Fabio, Sgarbossa Univ Padua Dept Management & Engn Stradella San Nicola 3 I-36100 Vicenza Italy

An automated parts-to-picker picking system usually consists of an automated warehouse, with Automatic Storage and Retrieval systems (AS/RS) that retrieve the Stock Keeping Units (SKUs) of the various needed products from their stocking locations, and of a picking area, with human operators or robots that pick the needed items in order to create a mixed shipping unit. The automated warehouse and the picking area are connected by an automated transportation system, which moves the SKUs from the warehouse to the picking stations and vice versa. The transportation system can be, for example, a ring rail conveyor on which various Rail Guided Vehicles (RGVs) are able to carry one SKU at a time. The present paper proposes a preliminary simulative analysis and, then, a mathematical formulation for this transportation system, useful to properly estimate the number of RGVs that are required to fulfill a certain picking throughput. In fact, it is shown that the picking throughput does not increase linearly with the number of vehicles employed, due to congestion issues. (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： warehouse picking parts-to-picker rail guided vehicles picking throughput

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Linear Parameter Varying control Synthesis for the atmospheric phase VEGA launcher

Linear Parameter Varying Control Synthesis for the atmospher...

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Joint Meeting of the 2nd ifac Workshop on Linear Parameter Varying systems (LPVS) / 9th ifac symposium on Robust control Design (ROCOND)

作者： Navarro-Tapia, D. Marcos, A. Bennani, S. Roux, C. Univ Bristol Technol Aerosp Control TASC Lab Bristol BS8 1TR Avon England ESA ESTEC NL-2201 AZ Noordwijk Netherlands ELV SpA I-00034 Colleferro Italy

This article presents the design of the atmospheric control system of a launch vehicle using the Linear Parameter Varying (LPV) synthesis technique. The main goal is to facilitate the transfer of this technique, already well known for providing a systematic design approach with reduced effort, to the European launcher industrial domain. In this paper, a grid-based LPV approach is applied to the actual VEGA VV05 mission data for the joint design of the rigid-body controller and the flexible bending filter in one single design procedure. The LPV controller is analysed in terms of classical linear stability margins and evaluated and compared with the VEGA baseline controller via Monte-Carlo analyses using a high-fidelity, nonlinear simulator. The results show that the LPV controller provides satisfactory stability margins and excellent performance and robustness characteristics while offering a more systematic and methodological design approach. (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： aerospace control robust control

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Autotuning of a Robust Fractional Order PID controller

Autotuning of a Robust Fractional Order PID Controller

引用

Joint Meeting of the 2nd ifac Workshop on Linear Parameter Varying systems (LPVS) / 9th ifac symposium on Robust control Design (ROCOND)

作者： De Keyser, Robin Muresan, Cristina I. Ionescu, Clara M. Univ Ghent DySC Res Grp Dynam Syst & Control Ghent Belgium Tech Univ Cluj Napoca Dept Automat Cluj Napoca Romania

Fractional order PI/PD controllers are generalizations of the well-known PI/PD controllers with an extra parameter usually used to enhance the robustness of the closed loop system. In this paper, an autotuning method, referred to as the fractional order KC autotuner, is presented for tuning fractional order PI/PD controllers. The method is an extension of a previously presented autotuning principle and produces controllers, which are robust to system gain variations. Additionally, the method can also be adapted to obtain robust controllers to time delay, time constant variations, etc. The advantages of this autotuning method reside in the simplicity of the approach: 1) it requires solely one single sine test on the process;2) it does not need the process model and 3) it eliminates the complex nonlinear equations in the traditional fractional order controller design procedure. Numerical examples are included to validate the method. (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： fractional order controllers autotuning method robustness iso-damping stability

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Introduction of a Prognostic Decision Making in a Fault Tolerant control Context

Introduction of a Prognostic Decision Making in a Fault Tole...

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10th International-Federation-of-Automatic-control (ifac) symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)

作者： Cieslak, J. Gucik-Derigny, D. Bordeaux Univ CNRS UMR 5218 IMS Lab 351 Cours Liberat F-33405 Talence France

The paper deals with the design of an enhanced active Fault Tolerant control (FTC) scheme based on the concept of supervisory control for uncertain Linear Time Invariant (LTI) systems. The improvement lies on the introduction of a Prognostic Decision Making (PDM) unit and a Virtual Fault Mechanism (VFM) in the supervisory FTC setup. The main purpose is to forecast the switching control thanks to the fault prediction to better mitigate the reconfiguration transients, while exponential stability is guaranteed by the dwell-time conditions. Since the diagnosis task is maintained in FTC setup to safely react to unforeseeable events, the solution proposes a structure where diagnosis, prognostic and accommodation tasks can work together in harmony. This work is applied to the academic aeronautical benchmark to highlight its potential. Copyright 2018 ifac (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Fault Tolerant control Supervisory control Prognostic Decision Making Fault Diagnosis

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Material Distribution and Transportation in a Norwegian Hospital: A Case Study

Material Distribution and Transportation in a Norwegian Hosp...

引用

16th ifac symposium on Information control Problems in Manufacturing (INCOM)

作者： Fragapane, Giuseppe Ismael Bertnum, Aili Biriita Hvolby, Hans-Henrik Strandhagen, Jan Ola Norwegian Univ Sci & Technol NTNU Dept Mech & Ind Engn Trondheim Norway Aalborg Univ Ctr Logist Dept Mat & Prod Aalborg Denmark

Automated Guided Vehicles have shown significant importance in material transportation and distribution in today's hospitals. The increasing trends of shorter hospital stays and increase of treatments and surgeries in clinics, present new challenges for the supply of goods. The rise in patients in hospitals, and consequently the increase of treatments and surgeries, cause a growth of material usage and goods movement. This study used the control Model methodology to analyze the material and information flow within the case hospital. Information sharing and integration is still a major issue in the case hospital. The study aims to stimulate further research in material handling and distribution in hospitals. (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Automated Guided Vehicles systems control Model Hospital Logistics

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Differentially-Private Distributed Fault Diagnosis for Large-Scale Nonlinear Uncertain systems

Differentially-Private Distributed Fault Diagnosis for Large...

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10th International-Federation-of-Automatic-control (ifac) symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)

作者： Rostampour, Vahab Ferrari, Riccardo Teixeira, Andre M. H. Keviczky, Tamas Delft Univ Technol Delft Ctr Syst & Control Mekelweg 2 NL-2628 CD Delft Netherlands Uppsala Univ Dept Engn Sci POB 534 SE-75121 Uppsala Sweden

Distributed fault diagnosis has been proposed as an effective technique for monitoring large scale, nonlinear and uncertain systems. It is based on the decomposition of the large scale system into a number of interconnected subsystems, each one monitored by a dedicated Local Fault Detector (LFD). Neighboring LFDs, in order to successfully account for subsystems interconnection, are thus required to communicate with each other some of the measurements from their subsystems. Anyway, such communication may expose private information of a given subsystem, such as its local input. To avoid this problem, we propose here to use differential privacy to pre-process data before transmission. (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Privacy Preserving Differential Privacy Distributed Fault Diagnosis Uncertain Network of Nonlinear systems

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Diagnosis of Interconnected systems via well tuned Model-Based Coupling Algorithms

Diagnosis of Interconnected Systems via well tuned Model-Bas...

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10th International-Federation-of-Automatic-control (ifac) symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)

作者： Tranninger, Markus Stettinger, Georg Benedikt, Martin Horn, Martin Graz Univ Technol Inst Automat & Control A-8010 Graz Austria VIRTUAL VEHICLE Res Ctr Area E Elect Elect & Software A-8010 Graz Austria

This paper presents a heuristic tuning method for a recently proposed model-based coupling algorithm. The purpose of the coupling algorithm is to mitigate effects caused by non ideal coupling of different subsystems where coupling imperfections like time delays, data losses or noisy measurements degrade the overall system performance. If the coupling algorithm is well tuned, a consistency criterion can be used for online closed-loop diagnosis. The simplicity and effectiveness of the proposed tuning and diagnosis approach is demonstrated via a laboratory experiment. (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Model Based Coupling Extended Kalman Filter Heuristic Tuning Identification Consistency Diagnosis

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