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Classical and Advanced control Methods Applied to an Anaerobic Digestion Reactor Model

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Classical and Advanced Control Methods Applied to an Anaerob...

CHILEAN Conference on Electrical, Electronics engineering, Information and Communication Technologies (CHILECON)

作者： E. Fernandez W. Ipanaque R. Cajo R. De Keyser Automatic and Control Systems laboratory Piura University Piura Perú Automatic and Control Systems lab Piura University Piura Peru Faculty of Engineering and Architecture Research group on Dynamical Systems and Control Ghent University Gent Belgium Faculty of Engineering and Architecture Research group on Dynamical Systems and Control Ghent University Ghent Belgium

ISBN: (纸本)9781728131863

In this work, advanced method of process control as Extended Prediction Self-Adaptive control (EPSAC) and Nonlinear Extended Prediction Self-Adaptive control (NEPSAC) are implemented and compared with the traditional PID controller tuned by a novel KC autotuning method and a classical FRtool method. The controllers are designed based on a linear and non-linear reactor model of the Anaerobic digestion pilot plant located in Peru. The performance evaluation of the controllers is realized through MATLAB environment with model parameters obtained experimentally. Also, a linear model has been developed using a novel estimation method of a Second Order Plus Dead-Time models (SOPDT). The results show that NEPSAC outperforms the other controllers.

关键词： adaptive control bioreactors linear systems nonlinear control systems predictive control process control temperature control three-term control Process control Three term control systems Nonlinear control systems Predictive control Temperature control adaptive control Bioreactors Linear system Proportional Integral Derivative control controllers control Methods DEAD TIME Anaerobic digestion anaerobic treatment Advanced controls

Minimax theorems for finite blocklength lossy joint source-channel coding over an AVC

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arXiv 2019年

作者： Vora, Anuj S. Kulkarni, Ankur A. Systems and Control Engineering group Indian Institute of Technology Bombay Mumbai400076 India

Motivated by applications in the security of cyber-physical systems, we pose the finite blocklength communication problem in the presence of a jammer as a zero-sum game between the encoder-decoder team and the jammer, by allowing the communicating team as well as the jammer only locally randomized strategies. The communicating team’s problem is non-convex under locally randomized codes, and hence, in general, a minimax theorem need not hold for this game. However, we show that approximate minimax theorems hold in the sense that the minimax and maximin values of the game approach each other asymptotically. In particular, for rates strictly below a critical threshold, both the minimax and maximin values approach zero, and for rates strictly above it, they both approach unity. We then show a second order minimax theorem, i.e., for rates exactly approaching the threshold with along a specific scaling, the minimax and maximin values approach the same constant value, that is neither zero nor one. Critical to these results is our derivation of finite blocklength bounds on the minimax and maximin values of the game and our derivation of second order dispersion-based *** Codes 94A15, 91A99 Copyright © 2019, The Authors. All rights reserved.

关键词： Embedded systems

Trajectory tracking for quadrotors with attitude control on S2× S1

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arXiv 2019年

作者： Kooijman, Dave Schoellig, Angela P. Antunes, Duarte J. Control Systems Technology group Mechanical Engineering Eindhoven University of Technology Netherlands Canada

The control of a quadrotor is typically split into two subsequent problems: finding desired accelerations to control its position, and controlling its attitude and the total thrust to track these accelerations and to track a yaw angle reference. While the thrust vector, generating accelerations, and the angle of rotation about the thrust vector, determining the yaw angle, can be controlled independently, most attitude control strategies in the literature, relying on representations in terms of quaternions, rotation matrices or Euler angles, result in an unnecessary coupling between the control of the thrust vector and of the angle about this vector. This leads, for instance, to undesired position tracking errors due to yaw tracking errors. In this paper we propose to tackle the attitude control problem using an attitude representation in the Cartesian product of the 2-sphere and the 1-sphere, denoted by S2× S1. We propose a non-linear tracking control law on S2× S1that decouples the control of the thrust vector and of the angle of rotation about the thrust vector, and guarantees almost global asymptotic stability. Simulation results highlight the advantages of the proposed approach over previous approaches. Copyright © 2019, The Authors. All rights reserved.

关键词： Attitude control

Price-coupling games and the generation expansion planning problem

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arXiv 2019年

作者： Abraham, Mathew P. Kulkarni, Ankur A. Systems and Control Engineering Group Indian Institute of Technology Bombay Mumbai400076 India

In this paper, we introduce and study a class of games called price-coupling games that arise in many scenarios, especially in the electricity industry. In a price-coupling game, there is a part of the objective function of a player which has an identical form for all players and there is coupling in the cost functions of players through a price which is determined uniformly for all players by an independent entity called the price-determining player (e.g. independent system operator (ISO) in an electricity market). This price appears in the objective function only in the part which is identical for all players. We study the existence of equilibria in such games under two broad categories, namely price-anticipative and price-taking formulations. In the price-anticipative formulation, the players anticipate the price and make their decisions while in the price-taking formulation, the players make their decisions considering the price as a given parameter. We model the price-anticipative case as a leader-follower formulation where the players (leaders) conjecture the price (follower's decision) and make their decision. The price-taking formulation is modelled as an N + 1 player game with the additional player as the price-determining player. The existence of an equilibrium in such games are not easy mainly because of the coupled-constraint structure of the game and the non-convexity of the action set. We give conditions for the existence of equilibria in both formulations. We apply our results to analyze the existence of an equilibrium in the generation expansion planning problem using the above results.91A99, 78M50 Copyright © 2019, The Authors. All rights reserved.

关键词： Cost functions

pycombina: An Open-Source Tool for Solving Combinatorial Approximation Problems Arising in Mixed-Integer Optimal control ⁎

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IFAC-PapersOnLine 2020年第2期53卷 6502-6508页

作者： Adrian Bürger Clemens Zeile Mirko Hahn Angelika Altmann-Dieses Sebastian Sager Moritz Diehl Institute of Refrigeration Air-Conditioning and Environmental Engineering Karlsruhe University of Applied Sciences Germany Systems Control and Optimization Laboratory Department of Microsystems Engineering University of Freiburg Germany MathOpt Group Institute for Mathematical Optimization Faculty of Mathematics Otto-von-Guericke University Magdeburg Germany Department of Mathematics University of Freiburg Germany

Application of Model Predictive control (MPC) for nonlinear switched systems often leads via discretization to Mixed-Integer Non-Linear Programs (MINLPs), which in a real-time setting can be solved approximately using a dedicated decomposition approach. One stage within this approach is the solution of a so-called Combinatorial Integral Approximation (CIA) problem, which is a Mixed-Integer Linear Program (MILP) that can be solved either approximately or to global optimality. The applicability of these decomposition methods depends strongly on efficient implementations, while many practical applications also require the consideration of a variety of additional and complex combinatorial constraints. In this work, we provide a comprehensive introduction to the open-source software tool pycombina, which enables users to automatically formulate CIA problems and provides methods for fast and efficient solution of these problems. In a case study, the usage of the tool is exemplified for input data from a real-life MPC application.

关键词： Nonlinear predictive control control of switched systems Numerical methods for optimal control

Correction to: the Ethics of AI in Human Resources

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Ethics and Information Technology 2023年第1期25卷 1-1页

作者： Dennis, Matthew J Aizenberg, Evgeni Department of Industrial Engineering & Innovation Sciences (IE&IS) Philosophy & Ethics Capacity Group TU/e Eindhoven The Netherlands Department of Intelligent Systems Delft University of Technology Delft The Netherlands AiTech Interdisciplinary Research Program on Meaningful Human Control over AI Delft University of Technology Delft The Netherlands

Incorporating Human Driving Data into Simulations and Trajectory Predictions 1

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4. Internationale ATZ-Fachtagung Automatisiertes Fahren, 2018

作者： Schmidt, Manuel Manna, Carlo Nattermann, Till Glander, Karl-Heinz Bertram, Torsten Institute of Control Theory and Systems Engineering TU Dortmund University Dortmund Germany ZF Group – TRW Automotive GmbH Automated Driving and Integral Cognitive Safety Düsseldorf Germany

ISBN: (数字)9783658237516

ISBN: (纸本)9783658237509

The development of algorithms for automated driving is a very challenging task. Recent progress in machine learning suggests that many algorithms will have a hybrid structure composed of deterministic or optimization and learning based elements. To train and validate such algorithms, realistic simulations are required. They need to be interaction based, incorporate intelligent surrounding traffic and the other traffic participants behavior has to be probabilistic. Current simulation environments for automotive systems often focus on vehicle dynamics. There are also microscopic traffic simulations that on the other hand don’t take vehicle dynamics into account. The few simulation software products that combine both elements still have at least one major problem. That is because lane change trajectories disregard human driving dynamics during such maneuvers. Consequently, machine learning algorithms developed and trained in simulations hardly generalize to non-synthetic data and therefore to real-world applications. © Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2019.

关键词： Adversarial machine learning

Stable recovery of entangled weights: Towards robust identification of deep neural networks from minimal samples

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arXiv 2021年

作者： Fiedler, Christian Fornasier, Massimo Klock, Timo Rauchensteiner, Michael Intelligent Control Systems Group Max Planck Institute for Intelligent Systems Heisenbergstr. 3 Stuttgart70569 Germany Institute for Data Science in Mechanical Engineering RWTH-Aachen University Dennewartstraße 27 Aachen50868 Germany Department of Mathematics Bolzmannstraße 3 85748 Garching Germany Department of Numerical Analysis and Scientific Computing Simula Research Laboratory Oslo Norway Department of Mathematics University of San Diego California San Diego United States

In this paper we approach the problem of unique and stable identifiability of generic deep artificial neural networks with pyramidal shape and smooth activation functions from a finite number of input-output samples. More specifically we introduce the so-called entangled weights, which compose weights of successive layers intertwined with suitable diagonal and invertible matrices depending on the activation functions and their shifts. We prove that entangled weights are completely and stably approximated by an efficient and robust algorithm as soon as O(D2 × m) nonadaptive input-output samples of the network are collected, where D is the input dimension and m is the number of neurons of the network. Moreover, we empirically observe that the approach applies to networks with up to O(D × mL) neurons, where mL is the number of output neurons at layer L. Provided knowledge of layer assignments of entangled weights and of remaining scaling and shift parameters, which may be further heuristically obtained by least squares, the entangled weights identify the network completely and uniquely. To highlight the relevance of the theoretical result of stable recovery of entangled weights, we present numerical experiments, which demonstrate that multilayered networks with generic weights can be robustly identified and therefore uniformly approximated by the presented algorithmic pipeline. In contrast backpropagation cannot generalize stably very well in this setting, being always limited by relatively large uniform error. In terms of practical impact, our study shows that we can relate input-output information uniquely and stably to network parameters, providing a form of explainability. Moreover, our method paves the way for compression of overparametrized networks and for the training of minimal complexity *** Codes 65D15, 68T07, 90C26 Copyright © 2021, The Authors. All rights reserved.

关键词： Deep neural networks

H Optimal Estimation for Linear Coupled PDE systems

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H Optimal Estimation for Linear Coupled PDE Systems

58th IEEE Conference on Decision and control, CDC 2019

作者： Das, Amritam Shivakumar, Sachin Weiland, Siep Peet, Matthew M. Eindhoven University of Technology Dept. of Electrical Engineering Control Systems Group Eindhoven5600 MB Netherlands Arizona State University School for Engineering of Matter Transport and Energy TempeAZ85292 United States

ISBN: (纸本)9781728113982

In this work, we present a Linear Matrix Inequality (LMI) based method to synthesize an optimal H estimator for a large class of linear coupled partial differential equations (PDEs) utilizing only finite dimensional measurements. Our approach extends the newly developed framework for representing and analyzing distributed parameter systems using operators on the space of square integrable functions that are equipped with multipliers and kernels of semi-separable class. We show that by redefining the state, the PDEs can be represented using operators that embed the boundary conditions and input-output relations explicitly. The optimal estimator synthesis problem is formulated as a convex optimization subject to LMIs that require no approximation or discretization. © 2019 IEEE.

关键词： Linear matrix inequalities