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control Technology and Applications (CCTA),

作者： Artemi Makarow Jan Braun Christoph Rösmann Georg Schoppel Ingo Glowatzky Torsten Bertram Institute of Control Theory and Systems Engineering TU Dortmund University Germany Bosch Rexroth AG Lohr am Main Germany

During a model-based system optimization of a proportional directional control valve, the system performance is simulated for a wide range of different design parameter sets. The behavior of the model, which is used to evaluate the system performance, changes whenever the optimization algorithm provides new parameter values. The closed-loop control response of a proportional valve is used as the metric of the system performance. Thus, to avoid evaluating the robustness of the valve controller, a new controller design is required whenever a variation of the plant parameters is carried out. The native controller of a proportional directional control valve is a nonlinear PID controller with numerous coupled parameters. This controller design requires a complex evolutionary multi-objective parameter optimization. This contribution introduces the model predictive control (MPC) in the context of a fully automated model-based system optimization of a proportional directional control valve. Since the plant is known exactly for every design variation, the plant model becomes a part of the control concept. By updating the prediction model, the controller exhibits a design adaptive characteristic. Due to the inherent system knowledge of the MPC setup within the model-based system optimization, the number of free controller parameters decreases significantly. These additional free parameters, like the weights of the user-defined objective function, can be included easily into the design optimization vector enabling a single holistic system optimization procedure.

关键词： Optimization Valves Numerical models Predictive models Finite element analysis Adaptation models

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A resonant speed controller for injection of a sinusoidal speed excitation in frequency response analysis of variable speed pump drives

A resonant speed controller for injection of a sinusoidal sp...

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International Conference on System theory, control, and Computing (ICSTCC)

作者： David Graurock Benedikt Meier Martin Oettmeier Jens O. Fiedler Torsten Bertram Research and Development Wilo SE Dortmund Germany Institute of Control Theory and Systems Engineering TU Dortmund University Dortmund Germany

In this paper an approach for adapting a speed controller in order to perform a superposition of the speed of a circulating pump with a sinusoidal excitation is presented. In various applications the injection of a sinusoidal signal can be used for frequency response analysis. In this case the speed control of a circulating pump is adapted in order to perform a speed excitation which can be used for the identification of the pipeline network the pump is embedded in. As the original speed control was implemented with a PI-controller in order to control the operating point of the pump, the control is adapted by adding a resonant controller in parallel to the PI-controller in order to maintain a transfer function similar to the original one while providing an improved behaviour regarding the injection of the speed excitation.

关键词： Torque Hydraulic systems Resonant frequency Velocity control Frequency control Transfer functions Mathematical model

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Online learning with stability guarantees: A memory-based real-time model predictive controller∗

arXiv

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arXiv 2018年

作者： Schwenkel, Lukas Gharbi, Meriem Trimpe, Sebastian Ebenbauer, Christian Institute for Systems Theory and Automatic Control University of Stuttgart Germany Institute for Data Science in Mechanical Engineering RWTH Aachen University Germany Intelligent Control Systems Group Max Planck Institute for Intelligent Systems Stuttgart Germany

We propose and analyze a real-time model predictive control (MPC) scheme that utilizes stored data to improve its performance by learning the value function online with stability guarantees. For linear and nonlinear systems, a learning method is presented that makes use of basic analytic properties of the cost function and is proven to learn the MPC control law and the value function on the limit set of the closed-loop state trajectory. The main idea is to generate a smart warm start based on historical data that improves future data points and thus future warm starts. We show that these warm starts are asymptotically exact and converge to the solution of the MPC optimization problem. Thereby, the suboptimality of the applied control input resulting from the real-time requirements vanishes over time. Numerical show that existing real-time MPC schemes can be improved by storing optimizatising the proposed ng scheme. Copyright © 2018, The Authors. All rights reserved.

关键词： Model predictive control

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Distributed H2-optimized Output Feedback controller Design using the ADMM

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IFAC-PapersOnLine 2017年第1期50卷 10389-10394页

作者： Eilbrecht J. Jilg M. Stursberg O. Institute of Control and System Theory Department of Electrical Engineering and Computer Science University of Kassel Kassel 34121 Germany

This paper addresses the design of sparse, H2-optimized dynamic output feedback controllers for distributed systems. These systems consist of several physically remote subsystems, which are assumed to be controlled via local controllers. Depending on the topology of a communication network, subsets of these controllers may exchange information. In this setting, a trade-off between control performance and communication costs exists: while a network which connects more controllers increases control performance, establishing communication links also causes higher costs. In the past, the Alternating Direction Method of Multipliers (ADMM) has been applied to the design of state feedback controllers that optimize this trade-off. Due to the practical relevance of output feedback, this paper provides extensions necessary for application of the ADMM to the output feedback case. Motivated by deeper insights into the non-convex, non-smooth nature of the problem, the HANSO optimization package is applied to the controller performance optimization subproblem of the ADMM. The devised procedure is successfully applied to two example systems. © 2017

关键词： ADMM Decentralized control Distributed control Dynamic Output Feedback Optimal control

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On approximation and implementation of transformation based feedback laws for distributed parameter systems

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IFAC-PapersOnLine 2017年第1期50卷 6786-6792页

作者： Woittennek F. Riesmeier M. Ecklebe S. Institute of Automation and Control Engineering University of Health Sciences Medical Informatics and Technology Hall in Tirol 6060 Austria Institute of Control Theory Technische Universität Dresden Dresden 01069 Germany

This paper presents an approach for the efficient numerical implementation of transformation based state feedback laws for linear distributed parameter systems. The control laws considered may originate from backstepping or flatness-based design methods. They are, therefore, directly based on the underlying distributed parameter systems. In general, they are given as unbounded functionals on the infinite-dimensional state-space. By approximating a carefully chosen bounded part, the implementation of these feedback-operators can be considerably simplified. This is achieved by approximating the state in appropriate finite-dimensional sub-spaces of the state-space. The choice of these sub-spaces as well as the controller implementation are discussed for both, a particular motivating example specific and the general case. For the implementation and validation of the obtained approximated controllers the python-based software toolbox PyInduct is introduced. © 2017

关键词： backstepping distributed parameter system feedback control flatness hyperbolic system late lumping parabolic system state feedback

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Adaptive Model Predictive control with Robust Constraint Satisfaction

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IFAC-PapersOnLine 2017年第1期50卷 3313-3318页

作者： Lorenzen M. Allgöwer F. Cannon M. Institute for Systems Theory and Automatic Control University of Stuttgart Germany Department of Engineering Science University of Oxford United Kingdom

Adaptive control for constrained, linear systems is addressed and a solution based on Model Predictive control (MPC) and set-membership system identification is presented. The paper introduces a computationally tractable solution which uses observations of past state and input trajectories to update the model and improve control performance while maintaining guaranteed constraint satisfaction and recursive feasibility. The developed approach is applied to a stabilizing MPC scheme and practical stability under persistent, additive disturbance is proved. A numerical example and brief comparison with non-adaptive MPC is provided. © 2017

关键词： Adaptive control Constraint Satisfaction Problems Model Predictive control System Identification Uncertain Linear Systems

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Semantic Mapping with Omnidirectional Vision

Semantic Mapping with Omnidirectional Vision

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IEEE International Conference on Robotics and Automation

作者： Luis Felipe Posada Alejandro Velasquez-Lopez Frank Hoffmann Torsten Bertram Design Engineering Research Group (GRID) Universidad EAFIT Medellin Colombia Institute of Control Theory and Systems Engineering Technische Universität Dortmund Dortmund Germany

This paper presents a purely visual semantic mapping framework using omnidirectional images. The approach rests upon the robust segmentation of the robot's local free space, replacing conventional range sensors for the generation of occupancy grid maps. The perceptions are mapped into a bird's eye view allowing an inverse sensor model directly by removing the non-linear distortions of the omnidirectional camera mirror. The system relies on a place category classifier to label the navigation relevant categories: room, corridor, doorway, and open room. Each place class maintains a separated grid map that are fused with the range-based occupancy grid for building a dense semantic map.

关键词： Semantics Sensors Cameras Robots Buildings Mirrors Visualization

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Local Refinement of l-complete Approximations for Supervisory control of Hybrid Systems

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IFAC-PapersOnLine 2018年第7期51卷 472-479页

作者： Yang, Jung–Min Moor, Thomas Raisch, Jörg School of Electronics Engineering Kyungpook National University 80 Daehakro Bukgu Daegu41566 Korea Republic of Lehrstuhl für Regelungstechnik at Friedrich-Alexander Universität Erlangen-Nürnberg ErlangenD-91058 Germany Fachgebiet Regelungssysteme Technische Universitaet Berlin Berlin10587 Germany Systems and Control Theory Group Max Planck Institute for Dynamics of Complex Technical Systems MagdeburgD-39106 Germany

l-complete approximation is a discrete abstraction method for a specific class of hybrid control problems involving purely discrete specifications. It allows for global refinement if the subsequent synthesis of supervisory control should fail for the currently selected abstraction level. In this paper, we present a methodology of local refinement for l-complete approximations. If the strongest l-complete approximation of a given hybrid system does not guarantee the existence of a suitable supervisor for a given specification, the proposed scheme refines the abstract model only in a local set of states that violate a controllability condition. Compared to the standard unfocused and global refinement procedure, this may significantly reduce the computational burden both in the abstraction step and the subsequent controller synthesis step. © 2018

关键词： Hybrid systems Abstracting controllability Discrete event simulation Discrete time control systems Specifications Abstract modeling Computational burden controllability condition controller synthesis Discrete abstraction l complete approximations Local refinement Supervisory control

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An Improved Output Feedback MPC scheme for Constrained Linear Systems

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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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A numerical solution to the two-dimensional nonlinear degenerate heat conduction equation with a source

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AIP Conference Proceedings 2020年第1期2315卷

作者： A. L. Kazakov L. F. Spevak O. A. Nefedova 1Institute of Engineering Science Ural Branch of the Russian Academy of Sciences 34 Komsomolskaya St. Ekaterinburg 620049 Russia 2Matrosov Institute for System Dynamics and Control Theory Siberian Branch of the Russian Academy of Sciences 134 lermontov St. Irkutsk 664033 Russia

The paper develops an algorithm for solving the two-dimensional nonlinear degenerate parabolic heat conduction equation with a source depending on required function, with a specified law of heat wave front motion. The algorithm based on the boundary element method is implemented in the form of a program. To verify it, we use exact solutions the construction of which is reducible to solving a Cauchy problem for ordinary differential equations with a singularity before the highest derivative. The solutions to the Cauchy problem are constructed in the form of power series with recurrently computed coefficients (with a proof of the statement providing its convergence) and by the boundary element method.

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