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Impact of the controller model complexity on model predictive control performance for buildings

ENERGY AND BUILDINGS 2017年 152卷 739-751页

作者： Picard, Damien Drgona, Jan Kvasnica, Michal Helsen, Lieve Katholieke Univ Leuven Dept Mech Engn Leuven Belgium Slovak Univ Technol Bratislava Radlinskeho 9 SK-81237 Bratislava Slovakia EnergyVille Thor Pk Waterschei Belgium

model predictive control (MPC) for heating, ventilation and air conditioning (HVAC) in buildings requires accurate controller models of the building envelope and its HVAC systems. controller models are typically obtained by means of black-or grey-box system identification or using a white-box modelling approach. However, the necessary level of model complexity used by each method in order to obtain good MPC performance remains a priori unknown and no systematic method or examples showing the optimal complexity is available. This paper systematically investigates the required controller model complexity necessary to obtain optimal control performance for a given building. First, a 6-room house is modeled in detail using building energy simulation software. The building model is then linearized to obtain a linear time invariant (LTI) state-space model (SSM) and the upper bound of the control performance is computed using an MPC with the SSM both as controller and as plant model. The accuracy of the SSM (containing more than 250 states) is then artificially decreased by reducing its number of states to different orders ranging from 4 to 100 using balanced truncation model order reduction technique. The performances of MPCs using these controller models are then compared with the upper bound for both a standard MPC formulation (S-MPC) and an offset-free formulation (OSF-MPC) and with the performance of a rule-based controller (RBC). The procedure is repeated for the same house model with a higher level of insulation and for a lighter weight construction. This paper shows that the controller model should contain a minimum of states to model each zone separately, and that the walls and floors separating the zones should also have enough states to act as a low pass filter with correct cut-off frequency. The minimum number of states further increases with the building mass content. In the case of the investigated 6-room house, the thermal comfort achieved by MPC using a con

关键词： Building climate control Optimization model predictive control model order reduction controller model

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Demonstration of an MPC framework for all-air systems in non-residential buildings

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BUILDING AND ENVIRONMENT 2022年 217卷 1页

作者： Merema, Bart Saelens, Dirk Breesch, Hilde Katholieke Univ Leuven Dept Civil Engn B-9000 Ghent Belgium Katholieke Univ Leuven Dept Civil Engn B-3000 Leuven Belgium EnergyVille B-3600 Genk Belgium DeltaQ B-1000 Brussels Belgium

In educational buildings, the HVAC system is a major contributor to the total energy use. It is well-known that energy reductions could be achieved by more advanced control strategies for HVAC systems. A model predictive control (MPC) strategy could be a viable solution. Contrary to the standard rule based control (RBC), the predictive control can adjust in the supply air temperature, airflow rate prior to the start of a lecture. This study aims to develop and demonstrate an MPC framework for an all-air system that controls both the room temperature and the CO2-concentrations. To predict these variables two model identification techniques were compared: auto-regressive with exogenous input (ARX-MPC) linear model and a grey-box resistor-capacitor nonlinear model (RC-NMPC). In addition, a cost function that minimized the energy use while guaranteeing thermal comfort and indoor air quality (IAQ) was formulated. This study showed that the ARX-MPC was preferred over the RC-NMPC given its simplicity. As for the model identification, the ARX model was less computationally time-consuming than the grey-box model. Furthermore, the RC-NMPC required more computational time than the ARX-MPC, since the RC-NMPC required a non-linear solver while the ARX-MPC used a linear one. The developed MPC framework was than implemented through BACnet in a real-use educational building to test its actual performance. The energy savings calculated for the implemented MPC strategies with an occupancy based heating set-point were respectively 10%-40% for electric energy use and 21%-55% for thermal energy use.

关键词： Building climate control model predictive control controller model Optimization Field test

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Optimized deep learning neural network predictive controller for continuous stirred tank reactor

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COMPUTERS & ELECTRICAL ENGINEERING 2018年 71卷 782-797页

作者： Deepa, S. N. Baranilingesan, I. Anna Univ Dept Elect & Elect Engn Reg Campus Coimbatore Coimbatore 641046 Tamil Nadu India

In this paper, a deep learning neural network model predictive controller (DLNNMPC) is designed to analyse the performance of a non-linear continuous stirred tank reactor (CSTR) that performs parallel and series reactions. The data generated employing the state space model of CSTR is used to train the designed deep learning neural network controller. Deep Learning Neural Network (DLNN) progresses the training with its weights tuned by the proposed hybrid version of evolutionary algorithms - Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA). The developed hybrid PSO - GSA based DLNN model of continuous stirred tank reactor is employed in this paper for model predictive controller design. The effectiveness of the proposed DLNNMPC tuned by hybrid PSO - GSA for CSTR is validated for its performance on comparison with that of other designed Proportional - Integral (PI) and Proportional - Integral - Derivative (PID) controllers as available in early literatures for the same problem under consideration. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Continuous stirred tank reactor Deep learning neural network controller model predictive control Particle swarm optimization Gravitational search algorithm controller model

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A model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints

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SENSORS 2018年第2期18卷 628-628页

作者： Sundharam, Sakthivel Manikandan Navet, Nicolas Altmeyer, Sebastian Havet, Lionel Univ Luxembourg CSC Res Unit Lab Adv Software Syst LASSY L-4364 Esch Sur Alzette Luxembourg Univ Amsterdam CSA Grp NL-1098XH Amsterdam Netherlands RealTime At Work RTaW 4 Rue Piroux F-54000 Nancy France

model-Driven Engineering (MDE) is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS). The design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of his field (for instance, a control engineer concentrates on designing a stable controller), he neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency). This may cause some of the functional and non-functional requirements not to be met satisfactorily. In this work, we present a co-design framework based on timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design verified by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on CPAL (Cyber-Physical Action Language), an MDE design environment based on model-interpretation, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. The application of our framework is exemplified in the design of an automotive cruise control system.

关键词： model-driven engineering control software timing tolerance contract controller model schedulability stability input jitters varying execution-times output jitters input-to-output delay co-simulation real-time scheduling control system performance

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A model-Based Development Environment for Rapid-Prototyping of Latency-Sensitive Automotive Control Software 6

A Model-Based Development Environment for Rapid-Prototyping ...

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6th International Symposium on Embedded Computing and System Design (ISED)

作者： Sundharam, Sakthivel Manikandan Havet, Lionel Altmeyer, Sebastian Navet, Nicolas Univ Luxembourg FSTC LASSY L-1359 Luxembourg Luxembourg RealTime At Work RTaW 615 Rue Jardin Bot F-54600 Villers Les Nancy France Univ Amsterdam CSA Grp NL-1098 XH Amsterdam Netherlands

ISBN: (纸本)9781509025428

The innovation in the field of automotive embedded systems has been increasingly relying on software-implemented functions. The control laws of these functions typically assume deterministic sampling rates and constant delays from input to output. However, on the target processors, the execution times of the software will depend on many factors such as the amount of interferences from other tasks, resulting in varying delays from sensing to actuating. Three approaches supported by tools, namely TrueTime, T-Res, and SimEvents, have been developed to facilitate the evaluation of how timing latencies affect control performance. However, these approaches support the simulation of control algorithms, but not their actual implementation. In this paper, we present a model interpretation engine running in a co-simulation environment to study control performances while considering the run-time delays in to account. Introspection features natively available facilitate the implementation of self-adaptive and fault-tolerance strategies to mitigate and compensate the run-time latencies. A DC servo controller is used as a supporting example to illustrate our approach. Experiments on controller tasks with injected delays show that our approach is on par with the existing techniques with respect to simulation. We then discuss the main benefits of our development approach that are the support for rapid-prototyping and the re-use of the simulation model at run-time, resulting in productivity and quality gains.

关键词： model-Based Development Control software controller model Task release jitters Varying execution-times Co-simulation Real-time scheduling Control system performance

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Generalmanual 000024193

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2016年

Generalmanual 000024193 by published by

关键词： access access point access points antenna controller controller model ethernet generalmanual harmony harmony access harmony openair harmony power lan lan module openair openair access point point controller power proxim web browser

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Cdc :: 1700 :: System 17 Applications Guide Jun73

引用

2016年

Cdc :: 1700 :: System 17 Applications Guide Jun73 by published by

关键词： analog applications cdc cdc system computer control control data controller controller model data guide jun73 magnetic tape mass storage model number output paper tape process control series summary description system system configurator

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AN ELECTRO-RHEOLOGICAL (ER) ROBOTIC SYSTEM: controller VALIDATION, TREND STUDY, COMPARISON WITH DC SERVOMOTORS, POSITION REPEATABILITY

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INTERNATIONAL JOURNAL OF MODERN PHYSICS B 2008年第29期22卷 5111-5144页

作者： Tan, K. P. Stanway, R. Bullough, W. A. Univ Sheffield Dept Mech Engn Sheffield S1 3JD S Yorkshire England

Industrial robot arms experience position inaccuracies due to the output cogging torques of the DC servomotors. Therefore, in an attempt to resolve these position problems, an electro-rheological (ER) robotic system is considered as an actuator to drive the robot arm rapidly in both directions. This ER robotic system consists of two ER clutches, an ER brake, a gear train, an encoder and a robot arm. The ER clutches produce clockwise and anti-clockwise rotations. The ER brake decelerates and halts the robot arm. The main aim of this paper is to validate a controller model of the ER robotic arm. Next, a trend study is used to determine the optimum working conditions of the ER actuated-robotic arm. The robotic displacements of both the ER rotary devices and the commercial DC servomotors are compared in terms of position accuracy and speed of response. Finally, the repeatability of the robotic end positions is examined in order to determine the importance of the ER brake.

关键词： DC servomotors electro-rheological robotic system controller model trend study position accuracy speed of response repeatability

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The Realistic Robot Simulation (RRS) Interface

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IFAC Proceedings Volumes 1994年第4期27卷 321-324页

作者： Rolf Bernhardt Gerhard Schreck Cornelius Willnow Fraunhofer-Institute for Production Systems and Design Technology (IPK Berlin) Pascalstraße 8-9 D-10587 Berlin Germany Tel +49 30 39006-0 Fax +49 30 39110 37

Tools for simulation and off-line programming became an important means for economic application of industrial robots. Until now the accuracy of the simulations was not sufficiently precise for reliable down-load and execution of the off-line generated programs. A main cause for this was the controller specific motion behaviour of the robots that could not be simulated with sufficent accuracy. The RRS-project was created to overcome this deficite. By defining a suitable interface, it was made possible to integrate original controller software for motion behaviour into off-line programming systems.

关键词： industrial robots off-line programming simulation controller model kinematic modelling

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