— Nowadays many robotic tasks require close and compliant tracking of desired positions, paths, or forces. To achieve these goals, model-based control schemes provide a possible solution, allowing to directly consider the nonlinear... more
— Nowadays many robotic tasks require close and compliant tracking of desired positions, paths, or forces. To achieve these goals, model-based control schemes provide a possible solution, allowing to directly consider the nonlinear dynamics. One of the key challenges, however, is the derivation of suitable models, which allow sufficiently fast evaluation, as well as the parameterization of these models based on measurements. In this work we outline and review a structured approach for model-based controller design for robots. In a first step we derive suitable models for multi-link robots. In a second step we review how such models can be parameterized and how optimal identification experiments can be designed. Based on the model we then derive a simple model based controller to experimentally validate the results considering a lightweight robot. The single steps of the derivation and controller design are supported by a newly developed freely available model toolbox for the considered lightweight robot.
Research Interests:
Research Interests:
Networked control systems are systems in which distributed controllers, sensors, actuators and plants are connected via a shared communication network. The use of nondeterministic networks introduces two major issues: communication delays... more
Networked control systems are systems in which distributed controllers, sensors, actuators and plants are connected via a shared communication network. The use of nondeterministic networks introduces two major issues: communication delays and packet dropouts. These problems cannot be avoided and they might lead to a degradation in performance, or, even worse, to instability of the system. Thus, it is important to take network effects directly into account. In this paper, nonlinear continuous time networked control systems are considered and a nonlinear model predictive controller that is able to compensate the network nondeterminism is outlined.
Research Interests:
ABSTRACT Die im Rahmen der Initiative „Industrie 4.0“ geforderte Autonomie auf Zellebene setzt u. a. voraus, komplexe Algorithmen auf speicherprogrammierbaren Steuerungen ausführen zu können. Vor diesem Hintergrund stellt dieser Beitrag... more
ABSTRACT Die im Rahmen der Initiative „Industrie 4.0“ geforderte Autonomie auf Zellebene setzt u. a. voraus, komplexe Algorithmen auf speicherprogrammierbaren Steuerungen ausführen zu können. Vor diesem Hintergrund stellt dieser Beitrag eine Möglichkeit vor, dies auf Basis heute verfügbarer Hardware umzusetzen. Im Kern werden Ansätze vorgestellt, die den Einsatz eines komplexen mathematischen Verfahrens auf dem Laufzeitsystem einer typischen Steuerung realisieren und das notwendige Engineering ermöglichen.
In this paper we investigate the relationship between parameter estimates obtained for a nonlinear discrete-time (DT) approximation of a continuous-time (CT) nonlinear model and the parameters corresponding to the CT model itself.... more
In this paper we investigate the relationship between parameter estimates obtained for a nonlinear discrete-time (DT) approximation of a continuous-time (CT) nonlinear model and the parameters corresponding to the CT model itself. Preliminary results based on a set-based parameter estimation approach are proposed. The focus is thereby directed on formalizing the problem of ensuring that the set of consistent parameters
Research Interests:
ABSTRACT The interpretation of slowly increasing faults in model based condition monitoring is challenging. In this work we propose to derive bounds for parametric fault features to determine if a fault is crucial to a plant or process,... more
ABSTRACT The interpretation of slowly increasing faults in model based condition monitoring is challenging. In this work we propose to derive bounds for parametric fault features to determine if a fault is crucial to a plant or process, looking at performance criteria. Essential information is provided by determination of a faults influence on a certain performance criterion, given by process requirements. For the analysis the sensitivity of parameters is determined via simulation studies. As an example the method is applied to a hydraulic axial piston unit, determining the influence of parametric faults on overall efficiency.
ABSTRACT In this paper we present stability conditions for nonlinear model predictive control with cyclically varying horizons. Starting from a maximum horizon length, the horizon is reduced by one at each sampling time until a minimum... more
ABSTRACT In this paper we present stability conditions for nonlinear model predictive control with cyclically varying horizons. Starting from a maximum horizon length, the horizon is reduced by one at each sampling time until a minimum horizon length is reached, at which the horizon is increased to the maximum length. The approach allows to utilize shapes and structures in the terminal constraints, which can otherwise not be handled. Examples are terminal boxconstraints, where the terminal set cannot be rendered invariant, or quadratic terminal regions and penalties of diagonal structure. Such constraints are for example of advantage for distributed predictive control problems. To underline the applicability, the approach is used to control a four tank system.
Research Interests:
ABSTRACT The design of decentralized controllers for physically coupled interconnected systems is a challenging task, especially if constraints on the states and inputs must be satisfied. In this work we focus on the design of... more
ABSTRACT The design of decentralized controllers for physically coupled interconnected systems is a challenging task, especially if constraints on the states and inputs must be satisfied. In this work we focus on the design of decentralized controllers for interconnected linear systems subject to nonlinear, homogeneous physical couplings. For the design and the characterization of controlled invariant regions we exploit the concept of positively invariant family of sets. Basically we utilize in the analysis and design a dynamically varying upper bound for the interconnections between the subsystems. This allows to overcome some conservatism related to existing design approaches. As shown, the controller synthesis can be formulated as loosely coupled LMI feasibility problems. This conceptually allows us to decompose the design into as series of smaller subproblems, which are computationally attractive. We obtain for the coupled nonlinear systems suitable decentralized linear control laws, as well as a family of ellipsoidal sets for which satisfaction of the state and input constraints, as well as positive invariance can be guaranteed. The application of the approach is validated considering the decentralized control of two systems that are interconnected with nonlinear functions.
Research Interests:
Research Interests:
Research Interests:
ABSTRACT
ABSTRACT In this paper we present stability conditions for nonlinear model predictive control with cyclically varying horizons. Starting from a maximum horizon length, the horizon is reduced by one at each sampling time until a minimum... more
ABSTRACT In this paper we present stability conditions for nonlinear model predictive control with cyclically varying horizons. Starting from a maximum horizon length, the horizon is reduced by one at each sampling time until a minimum horizon length is reached, at which the horizon is increased to the maximum length. The approach allows to utilize shapes and structures in the terminal constraints, which can otherwise not be handled. Examples are terminal boxconstraints, where the terminal set cannot be rendered invariant, or quadratic terminal regions and penalties of diagonal structure. Such constraints are for example of advantage for distributed predictive control problems. To underline the applicability, the approach is used to control a four tank system.
Research Interests:
ABSTRACT The interpretation of slowly increasing faults in model based condition monitoring is challenging. In this work we propose to derive bounds for parametric fault features to determine if a fault is crucial to a plant or process,... more
ABSTRACT The interpretation of slowly increasing faults in model based condition monitoring is challenging. In this work we propose to derive bounds for parametric fault features to determine if a fault is crucial to a plant or process, looking at performance criteria. Essential information is provided by determination of a faults influence on a certain performance criterion, given by process requirements. For the analysis the sensitivity of parameters is determined via simulation studies. As an example the method is applied to a hydraulic axial piston unit, determining the influence of parametric faults on overall efficiency.