Chair Of Mechatronics Research Articles

Cable Robotic 3D-printing: additive manufacturing on the construction site

This paper outlines an important step in characterizing a novel field of robotic construction research where a cable-driven parallel robot is used to extrude cementitious material in three-dimensional space, and thus offering a comprehensive new approach to computational design and construction, and to robotic fabrication at larger scales. Developed by the Faculty of Art and Design at Bauhaus-University Weimar (Germany), the faculty of Architecture at the University of Applied Sciences Dortmund (Germany) and the Chair of Mechatronics at the University of Duisburg-Essen (Germany), this approach offers unique advantages over existing additive manufacturing methods: the system is easily transportable and scalable, it does not require additional formwork or scaffolding, and it offers digital integration and informational oversight across the entire design and building process. This paper considers 1) key research components of cable robotic 3D-printing (such as computational design, material exploration, and robotic control), and 2) the integration of these parameters into a unified design and building process. The demonstration of the approach at full-scale is of particular concern.

Application Study of Newton-Raphson-Type Nonlinear MPC for Hydrostatic Transmissions Under Disturbance and System Uncertainty

Model predictive control is well established and has a huge practical relevance in many industrial applications, especially for chemical or thermal plants. This paper presents the design and the implementation of a nonlinear model predictive control aiming at an accurate tracking control of desired output trajectories under disturbances and uncertainties for a nonlinear hydrostatic transmission system with multiple control inputs, which represents a fast mechatronic system. The benefit of this solution is that it can be easily adapted to either velocity tracking control or torque tracking control -- which is not the case with alternative model-based approaches. The control design is based on a numerical optimization within a moving horizon using the Newton-Raphson method in combination with the optimization-over-some variables technique. The unmeasurable system state variables as well as the system disturbances are reconstructed by an unscented Kalman filter which is well suited for nonlineaer systems subject to process and measurement noise. The proposed control scheme is investigated by simulations and experimentally validated on a test rig at the Chair of Mechatronics, University of Rostock. The results indicates the robustness of the proposed control structure by a high tracking accuracy despite system disturbances and uncertainties.

From Verified Parameter Identification to the Design of Interval Observers and Cooperativity-Preserving Controllers

One of the most important advantages of interval observers is their capability to provide estimates for a given dynamic system model in terms of guaranteed state bounds which are compatible with measured data that are subject to bounded uncertainty. However, the inevitable requirement for being able to produce such verified bounds is the knowledge about a dynamic system model in which possible uncertainties and inaccuracies are themselves represented by guaranteed bounds. For that reason, classical point-valued parameter identification schemes are often not sufficient or should, at least, be handled with sufficient care if safety critical applications are of interest. This paper provides an application-oriented description of the major steps leading from a control-oriented system model with an associated verified parameter identification to a verified design of interval observers which provide the basis for the development and implementation of cooperativity-preserving feedback controllers. The corresponding computational steps are described and visualized for the temperature control of a laboratory-scale test rig available at the Chair of Mechatronics at the University of Rostock.

Kalman Filter-Based Online Identification of the Electric Power Characteristic of Solid Oxide Fuel Cells Aiming at Maximum Power Point Tracking

High-temperature fuel cells are one of the devices currently investigated for an integration into distributed power supply grids. Such distributed grids aim at the simultaneous production of thermal energy and electricity. To maximize the efficiency of fuel cell systems, it is reasonable to track the point of maximum electric power production and to operate the system in close vicinity to this point. However, variations of gas mass flows, especially the concentration of hydrogen contained in the anode gas, as well as variations of the internal temperature distribution in the fuel cell stack module lead to the fact that the maximum power point changes in dependence of the aforementioned phenomena. Therefore, this paper first proposes a real-time capable stochastic filter approach for the local identification of the electric power characteristic of the fuel cell. Second, based on this estimate, a maximum power point tracking procedure is derived. It is based on an iteration procedure under consideration of the estimation accuracy of the stochastic filter and adjusts the fuel cell’s electric current so that optimal operating points are guaranteed. Numerical simulations, based on real measured data gathered at a test rig available at the Chair of Mechatronics at the University of Rostock, Germany, conclude this paper.

Discrete-Time State-Dependent Proportional-Integral Control for Torque Tracking of Hydrostatic Transmissions

This paper presents both design and implementation of a discrete-time proportional-integral (PI) tracking control for the desired output torque of a nonlinear hydrostatic transmission system affected by disturbances and uncertainties. The control is conceived in a decentralized form, in which the bent-axis angle and the torque of the hydraulic motor are controlled separately. The motor bent-axis angle is adjusted by a pure feedforward control law, whereas the torque of the hydraulic motor is controlled using a PI state feedback from a online-solution of the state-dependent Riccati equation. State variables and external disturbances are reconstructed by a discrete-time nonlinear observer. The stability of the closed-loop system as well as the observer are investigated by linear matrix inequalities. The achieved tracking performance indicates the robustness of the overall control structure in the presence of system disturbances and uncertainties. The proposed control is evaluated by means of simulations and experiments using the dedicated test rig at the Chair of Mechatronics, University of Rostock.

A cable-driven parallel robots application: modelling and simulation of a dynamic cable model in Dymola

Modeling a cable model in multibody dynamics simulation tool which dynamically varies in length, mass and stiffness is a challenging task. Simulation of cable-driven parallel robots (CDPR) for instance requires a cable model that can dynamically change in length for every desired pose of the platform. Thus, in this paper, a detailed procedure for modeling and simulation of a dynamic cable model in Dymola is proposed. The approach is also applicable for other types of Modelica simulation environments. The cable is modeled using standard mechanical elements like mass, spring, damper and joint. The parameters of the cable model are based on the factsheet of the manufacturer and experimental results. Its dynamic ability is tested by applying it on a complete planar CDPR model in which the parameters are based on a prototype named CABLAR, which is developed in Chair of Mechatronics, University of Duisburg-Essen. The prototype has been developed to demonstrate an application of CDPR as a goods storage and retrieval machine. The performance of the cable model during the simulation is analyzed and discussed.

An integrodifferential approach to modeling, control, state estimation and optimization for heat transfer systems

Abstract In this paper, control-oriented modeling approaches are presented for distributed parameter systems. These systems, which are in the focus of this contribution, are assumed to be described by suitable partial differential equations. They arise naturally during the modeling of dynamic heat transfer processes. The presented approaches aim at developing finite-dimensional system descriptions for the design of various open-loop, closed-loop, and optimal control strategies as well as state, disturbance, and parameter estimation techniques. Here, the modeling is based on the method of integrodifferential relations, which can be employed to determine accurate, finite-dimensional sets of state equations by using projection techniques. These lead to a finite element representation of the distributed parameter system. Where applicable, these finite element models are combined with finite volume representations to describe storage variables that are—with good accuracy—homogeneous over sufficiently large space domains. The advantage of this combination is keeping the computational complexity as low as possible. Under these prerequisites, real-time applicable control algorithms are derived and validated via simulation and experiment for a laboratory-scale heat transfer system at the Chair of Mechatronics at the University of Rostock. This benchmark system consists of a metallic rod that is equipped with a finite number of Peltier elements which are used either as distributed control inputs, allowing active cooling and heating, or as spatially distributed disturbance inputs.

Robust Control for a Spatially Three-Dimensional Heat Transfer Process

Reliable modeling and robust control of heat transfer processes are tasks with many applications in engineering. Such tasks are relevant, for example, in control of high-temperature fuel cells, in manufacturing of semiconductor devices, control and modeling of welding processes, and for a reliable description of tube-like gas heater structures. For this reason, control-oriented modeling procedures for spatially distributed heating systems are described in this paper. The resulting models, derived from a spatial semi-discretization employing a finite volume modeling technique, are parameterized by means of experimental identification procedures. These models are then used for the design of robust controllers as well as for state and disturbance observers. An experimental validation on a test rig available at the Chair of Mechatronics at the University of Rostock concludes this paper.

Comparison of Model-Based Approaches to the Compensation of Hysteresis in the Force Characteristic of Pneumatic Muscles

In this paper, a comparison of three different feedforward compensation strategies that counteract hysteresis effects in the nonlinear force characteristic of pneumatic muscles is presented: The generalized Bouc-Wen model is a dynamic hysteresis model and enables a description of the given highly asymmetric hysteresis, and as alternative hysteresis models for the comparison, the quasi-static Maxwell-slip model and the Prandtl-Ishlinskii model are considered. The parameters of all these hysteresis models have been experimentally identified using evolutionary optimization algorithms. Each of the identified hysteresis models is suitable for an additional feedforward control action in an existing nonlinear control structure for a high-speed linear axis that is actuated by pneumatic muscles to further reduce the tracking error. This cascaded nonlinear control structure consists of fast underlying control loops for the internal muscle pressures and an outer adaptive backstepping control loop for both the carriage position and the mean muscle pressure. Here, the adaptive control part counteracts nonlinear friction and the remaining model uncertainty. Comprehensive experimental results from an implementation of the proposed control approach on a test rig at the Chair of Mechatronics, University of Rostock, Rostock, Germany, point out both the benefits and efficiency of the corresponding feedforward hysteresis compensation strategies.

Thermal behavior of high-temperature fuel cells: reliable parameter identification and interval-based sliding mode control

In this contribution, we present interval methods for mathematical modeling, for parameter identification, and for control design of dynamical systems. The corresponding approaches are applied to the thermal subsystem of a high-temperature solid oxide fuel cell (SOFC) which is available as a test rig at the Chair of Mechatronics at the University of Rostock. In practice, most internal parameters of SOFC stack modules cannot be measured directly. Therefore, system characteristics such as heat capacities or internal thermal resistances cannot be identified exactly, but only bounded. For this reason, intervals represent a good first approach to dealing with parameter uncertainty. In the first part of the paper, we present interval methods for the parameter identification aiming at the computation of globally optimal parameterizations. In comparison with classical local optimization procedures, the approximation quality is improved by the presented identification approach. The corresponding bounds for admissible domains are used to design a robust sliding mode control law for arbitrary operating points compensating the impact of disturbances and parameter uncertainties in a reliable way. In the second part of the paper, we show a simple approach to handling non-smoothness appearing in SOFC models based on ordinary differential equations in a verified way. We use a generalized derivative definition for a certain type of non-smooth functions inside the algorithm of the verified solver ValEncIA-IVP to be able to compute solutions to non-smooth initial value problems. The applicability of our method is demonstrated using the designed sliding mode controller.

Verified Stability Analysis for Interval-Based Sliding Mode and Predictive Control Procedures with Applications to High-Temperature Fuel Cell Systems

In previous work, control-oriented models have been derived for solid oxide high-temperature fuel cell systems. In these models, interval variables have been used to describe uncertainty due to a limited knowledge about system parameters and to handle effects of electric load variations on the temperature distribution in the fuel cell stack module as well as bounded measurement uncertainty. To deal with these types of uncertainty both in the design of robust controllers and during their online usage, interval techniques can be employed successfully. These control procedures make use of the basic principles of either sliding mode control or predictive control. The corresponding algorithms and the prerequisites for their real-time capable implementation using software libraries for interval arithmetic and algorithmic differentiation are described in this paper. Experimental results show the efficiency of these control laws for a fuel cell test rig that is available at the Chair of Mechatronics at the University of Rostock.

An Integrodifferential Approach to Adaptive Control Design for Heat Transfer Systems with Uncertainties

AbstractOpen-loop and closed-loop control problems for distributed parameter systems, described by parabolic partial differential equations, are considered in this contribution. The goal of the study is the development of strategies for control and estimation of states, disturbances, and parameters. These strategies are based on the method of integrodifferential relations, a projection approach, and a suitable finite element technique. A real-time applicable control algorithm is proposed and its specific features are discussed. A verification of the control laws derived in this contribution is performed taking into account explicit error estimates resulting directly from the integrodifferential approach. The parameters, geometry, and actuation principles of a heat transfer system available at the Chair of Mechatronics, University of Rostock, are used for the numerical simulation and experimental validation. The test setup consists of a metallic rod equipped with a finite number of Peltier elements which are used as distributed control inputs allowing for active cooling and heating.