Institute of Automatic Control

Transcription

1 Institute of Automatic Control Model-based analysis and design allow for the successful control of complex dynamical systems n The institute is focused on both, the development of methods and their application. In order to allow for an efficient control of technical processes, new techniques are devised in nonlinear control, energy -based modeling and design, model order reduction, as well as adaptive and predictive control. Moreover, a Collaborative Research Centre puts a spotlight on the modeling and analysis of non technical systems. From an application perspective, highly challenging problems include the treatment of vibrations in automobiles, the robust control of multicopters, the control of unstable robots, and the feedback control of industrial processes. Active and Semi-Active Suspension Control developments of our research include the development of a nonlinear feedback control in combination with nonlinear state observation techniques. Thereby, different design objectives can transparently be achieved, while design restrictions like state and input constraints can be taken into account. The so-called hybrid suspension system, developed at our institute, is depicted in the figure; it includes a low-bandwidth actuator F(t) and a high bandwidth variable damper d c (t), together with a sophisticated control system. Prof. Dr.-Ing. habil. Boris Lohmann Contact sekretariat@rt.mw.tum.de Phone Experiments are performed at two quarter car test stands available in the Institute of Automatic Control. Active suspension systems can significantly contribute to the comfort and safety of passenger cars by minimizing vibrations acting on passengers and by reducing dynamic wheel load. Recent Hybrid suspension system controlled by a state estimator and feedback controller Institute of Automatic Control 169

2 Model Order Reduction When a load F(t) moves along an elastic structure, a time-varying high-order model results, which requires reduction before further use in analysis and controller design. The modeling of dynamic systems frequently leads to large sets of differential equations. The goal of model order reduction is to find a much smaller (reduced) model that preserves the most important properties of the original model. Recent research in our group deals with reducing parameter-dependent systems, timevarying systems and systems of differential algebraic equations. The resulting new methods guarantee high approximation accuracy, while being numerically efficient and preserving important system properties like stability or passivity. ISS as an example of a high-order flexible structure. (Photo: NASA) Model Predictive Control for Highly Dynamic Systems Quadrotor the designated controller test platform Within the last decades, immense growth of the available computational power has enabled the embedded implementation of optimization-based control approaches for systems with fast dynamics. The main strength of the model predictive control (MPC) paradigm is the possibility to systematically consider constraints on the input and state variables. Still, the real-world application of nonlinear MPC remains challenging, as non-convex optimization problems have to be solved online with sufficient accuracy in order to obtain desirable closed-loop dynamics. Currently, a novel control concept for multirotor systems using adaptive and predictive components is developed in collaboration with the Institute of Flight System Dynamics. Modeling and Control of Distributed Parameter Systems Visualization of the solution of an undamped wave equation depending on one spatial variable and time Partial differential equations can be used to characterize systems whose parameters depend not only on time but on a spatial variable as well. Such systems include all kinds of transport and diffusion phenomena as they arise for example in the movement of beams or in air flowing through a tube. Firstly, research is dedicated to a new approach for the identification of parameters in linear partial differential equations. Based on the thereupon parameterized model, secondly, model-based control techniques are applied to achieve a desired dynamic behavior of the distributed parameter system. Currently, research interests are focused on a pneumatic line with nonlinear friction. 170 Institute of Automatic Control

3 Energy Based Modeling and Control One focus of research is the design and application of energy-based control approaches to mechatronic systems. Two examples are velocity- and positioncontrol of the mini wheeled inverted pendulum (see section Takagi-Sugeno Systems) and the design of observer-based controllers for linear port-hamiltonian systems using a dual approach. Another main topic is the modeling and control of Feedforward control and simulation of the water level in a channel. The upstream inflow rate is computed to achieve a smooth transient at the downstream. Block diagram with the Dual Observer-Based Compensator (DOBC) systems governed by partial differential equations. A current DFG project deals with the control design based on spatial discretizations that preserve structural properties in terms of energy and conserved quantities. A modular flexible robot is currently under construction as a lab demonstrator for the developed methods. Our scientific exchange with IIT-Bombay, India (DAAD) continues while EU Marie Skłodowska-Curie Actions help to extend our network to France. Takagi-Sugeno Models and Controller Design Most robotic systems exhibit unneglectable nonlinearities in their system dynamics, which are to be considered in the design process of the controller. One approach is to use interpolated linear models, so-called Takagi-Sugeno models, to represent the dynamics of nonlinear systems and to use these models for analysis and control design. Within the collaborative research centre Zyklenmanagement von Innovationsprozessen of the German Research Council (DFG), the modeling and analysis of non-technical dynamical systems is investigated by the use of Takagi-Sugeno models. Ballbot and wheeled inverted pendulum as examples for unstable nonlinear robots Institute of Automatic Control 171

4 Research Focus n Automotive and active vibration control n Model order reduction n Model predictive control n Energy-based modeling and control n Modeling and control of distributed parameter systems n Takagi-Sugeno models and controller design Competence n Mechatronic systems design and control n Feedback control in production systems n Modeling, analysis and control of technical and non-technical processes n Control and optimization n Adaptive and model predictive control Infrastructure n Two quarter-car test stands n Various mechatronic test rigs and robots n Control systems design lab n Electrical and mechanical workshop Courses n Regelungstechnik (Bachelor MW) n Systemtheorie in der Mechatronik (Bachelor MW) n Moderne Methoden der Regelungstechnik 1-3 (Master) n Advanced Control (Master MSPE) n Nonlinear Control (Master MSPE) n Abtastregelung und Computer-Algebra (Master) Management Prof. Dr.-Ing. Boris Lohmann, Director Administrative Staff Regine Markwort Research Scientists Dr.-Ing. Nicole Gehring (Head of the PDE- Group) Dr.-Ing. Paul Kotyczka (Head of the Energy-Based Control Group) Klaus Albert, M.Sc. Alessandro Castagnotto, M.Sc. Maria Cruz Varona, M. Sc. Dipl.-Ing. Sergio Delgado Christian Dengler, M.Sc. Dipl.-Ing. Klaus J. Diepold Dipl.-Ing. Matthias Geuß, M.Sc. Richard Kern, M.Sc. Philipp Niermeyer, M.Sc. Mikhail Pak, M.Sc. Dipl.-Ing. Nils Pletschen Dipl.-Ing. Benjamin Stahl Johannes Strohm, M.Sc. Mei Wang, M.Sc. Technical Staff Thomas Huber Ralf Hübner 172 Institute of Automatic Control

5 Publications 2015 n Pletschen, N.; Barthelmes, S.; Lohmann, B.: Joint State-Parameter Estimation for Active Vehicle Suspensions: A Takagi-Sugeno Kalman Filtering Approach. 54th IEEE Conference on Decision and Control, Osaka, Japan, 2015 n Castagnotto, A.; Cruz Varona, M.; Lohmann, B.: sss & sssmor: Analysis & Reduction of Large-Scale Dynamic Systems with MATLAB. MOR 4 MEMS 2015 Workshop, Karlsruhe, Germany, 2015 n Castagnotto, A.: Salami Slicing & H2-Pseudo-Optimal Model Order Reduction. SIAM Student Chapter at Virginia Tech, Blacksburg (VA), USA, 2015 n Cruz Varona, M.; Lohmann, B.: Model Order Reduction of Linear Time-Varying Systems: Some straightforward approaches. MOR 4 MEMS Workshop, Karlsruhe, 2015 n Cruz Varona, M.; Lohmann, B.: Time-Varying Parametric Model Order Reduction by Matrix Interpolation. MoRePaS 2015 Model Reduction of Parametrized Systems III, Trieste, 2015 n Castagnotto A.; Panzer H. K. F.; Lohmann B.: Stability-Preserving, Adaptive Model Reduction of DAEs by Krylov-Subspace Methods. MoRePaS 2015 Model Reduction of Parametrized Systems III, Trieste, Italy, 2015 n Castagnotto A.; Panzer H. K. F.; Lohmann B.: Modellfunktionen in der H2-Optimalen Modellreduktion von LZI Systemen im Zustandsraum. GMA Fachauschuss 1.30 Modellbildung, Identifikation und Simulation in der Automatisierungstechnik, Anif, Austria, 2015 n Pletschen, N.: Nichtlineare Zustandsrekonstruktion in der vertikalen Fahrwerkregelung: Ein Takagi-Sugeno Kalman-Filter Ansatz. GMA Fachausschuss 1.40 Theoretische Verfahren der Regelungstechnik, Anif, Salzburg, Austria, 2015 n Delgado, S.; Kotyczka, P.: Energy Shaping for the Robust Stabilization of a Wheeled Inverted Pendulum. Proceedings of the 5th IFAC Workshop on Lagrangian and Hamiltonian Methods for Non Linear Control, 2015, n Trivedi, M. V., Banavar, R. N., Kotyczka, P.: Port-Hamiltonian Modelling for Buckling Control of a Vertical Flexible Beam with Actuation at the Bottom. Proceedings of the 5th IFAC Workshop on Lagrangian and Hamiltonian Methods for Nonlinear Control, 2015 n Kotyczka, P., Blancato, A.: Feedforward control of a channel flow based on a discretized port-hamiltonian model. Proceedings of the 5th IFAC Workshop on Lagrangian and Hamiltonian Methods for Nonlinear Control, 2015 n Delgado, S.; Gajbhiye, S.; Banavar R.N.: Reduced equations of motion for a wheeled inverted pendulum. Proceedings of the 8th Vienna International Conference on Mathematical Modelling (MATH- MOD), 2015 n Cruz Varona, M.; Geuß, M.; Lohmann, B.: p(t)mor and Applications for Moving Loads. Proceedings of the 8th Vienna Conference on Mathematical Modeling (MATHMOD), Vienna, Austria (IFAC-PapersOnLine), Elsevier, 2015, n Castagnotto A.; Panzer H. K. F.; Wolf T.; Lohmann B.: Advances on the Adaptive Selection of Both Shifts and Reduced Order in H2-Pseudo-Optimal Model Reduction. In Proceedings of the 8th Vienna Conference on Mathematical Modeling (MATHMOD), Vienna, Austria (IFAC-PapersOnLine), Elsevier, 2015, , Awarded the 2nd prize in the MATHMOD 2015 poster session n Kern, R.; Shastri, Y.: Advanced control with parameter estimation of batch transesterification reactor. Journal of Process Control 33 (0), 2015, n Kotyczka, P., Wang, M.: Dual observer-based compensator design for linear port-hamiltonian systems. Proceedings of the European Control Conference, 2015 n Dietrich, A., Bussmann, K., Petit, F., Kotyczka, P., Ott, C., Lohmann, B., Albu-Schäffer, A.: Whole- Body Impedance Control of Wheeled Mobile Manipulators Stability Analysis and Experiments on the Humanoid Robot Rollin Justin. Autonomous Robots, Special Issue on Whole-Body Control of Contacts and Dynamics for Humanoid Robots, 2015 Institute of Automatic Control 173