In advanced robot applications, the challenge today is that the robot should perform different successive subtasks to achieve one or more complicated tasks similar to human. Hence, this kind of tasks required to combine different kind of sensors in order to get full information about the work environment. However, from the point of view of control, more sensors mean more possibilities for the structure of the control system. As shown previously, vision and force sensors are the most common external sensors in robot system. As a result, in scientific papers it can be found numerous control algorithms and different structures for vision/force robot control, e.g. shared, traded control etc. The lacks in integration of vision/force robot control could be summarized as follows: • How to define which subspaces should be vision, position or force controlled? • When the controller should switch from one control mode to another one? • How to insure that the visual information could be reliably used? • How to define the most appropriated vision/force control structure? In many previous works, during performing a specified task one kind of vision/force control structure has been used which is pre-defined by the programmer. In addition to that, if the task is modified or changed, it would be much complicated for the user to describe the task and to define the most appropriated vision/force robot control especially if the user is inexperienced. Furthermore, vision and force sensors are used only as simple feedback (e.g. vision sensor is used usually as position estimator) or they are intended to avoid the obstacles. Accordingly, much useful information provided by the sensors which help the robot to perform the task autonomously is missed. In our opinion, these lacks of defining the most appropriate vision/force robot control and the weakness in the utilization from all the information which could be provided by the sensors introduce important limits which prevent the robot to be versatile, autonomous, dependable and user-friendly. For this purpose, helping to increase autonomy, versatility, dependability and user-friendly in certain area of robotics which requires vision/force integration is the scope of this thesis. More concretely: 1. Autonomy: In the term of an automatic decision system which defines the most appropriated vision/force control modes for different kinds of tasks and chooses the best structure of vision/force control depending on the surrounding environments and a priori knowledge. 2. Versatility: By preparing some relevant scenarios for different situations, where both the visual servoing and force control are necessary and indispensable. 3. Dependability: In the term of the robot should depend on its own sensors more than on reprogramming and human intervention. In other words, how the robot system can use all the available information which could be provided by the vision and force sensors, not only for the target object but also for the features extraction of the whole scene. 4. User-friendly: By designing a high level description of the task, the object and the sensor configuration which is suitable also for inexperienced user. If the previous properties are relatively achieved, the proposed robot system can: • Perform different successive and complex tasks. • Grasp/contact and track imprecisely placed objects with different poses. • Decide automatically the most appropriate combination of vision/force feedback for every task and react immediately to the changes from one control cycle to another because of occurrence of some unforeseen events. • Benefit from all the advantages of different vision/force control structures. • Benefit from all the information provided by the sensors. • Reduce the human intervention or reprogramming during the execution of the task. • Facilitate the task description and entering of a priori-knowledge for the user, even if he/she is inexperienced.

In some industrial fields, such as aerospace, electro-hydrostatic actuators (EHAs) are increasingly used to replace conventional standard hydraulic actuators due to their better energy performance. Moreover, implementing different type or technology of actuators in redundant actuation systems working on the same moving part introduced some new challenges. This paper presents a force-tracking controller for an asymmetric electro-hydrostatic actuator that is submitted to an external motion generated by an external source. In this case, the rod displacement is considered as an external disturbance for the hydraulic cylinder, but it is assumed that this disturbance can be easily measured using sensors. The theoretical motivation of this work is discussed along and a variable gain state feedback control based on Linear Parameter Varying control (LPV) theory is proposed to achieve stability, disturbance rejection and tracking performance. The Linear Matrix Inequalities (LMI) framework is used to determine a control law including an augmented state feedback with an integral action that reduces trajectory-tracking errors. Simulation results of the control law are finally given to verify the global performance of this control design.

Die prozessaktuelle Messung von Kräften und Momenten zwischen Werkzeug und Werkstück ist zunehmend Voraussetzung für viele fertigungstechnische Anwendungen. Neben der Verwendung der Daten zur Prozessdiagnose und -überwachung sowie für Qualitätssicherung und -nachweis, werden durch geregelte bzw. adaptive Prozessführung bestimmte Prozesse oder Qualitäten überhaupt erst möglich oder wirtschaftlich. Mit dem erweiterten Bewegungsvermögen moderner Fertigungseinrichtungen wächst dabei auch der Bedarf zur Erfassung räumlicher Kräfte und Momente in bis zu 6 Freiheitsgraden. Großes Potenzial besteht in der Integration mehrerer einachsiger Kraftsensoren direkt in die Maschinenstruktur und der intelligenten Verarbeitung der Messsignale zu räumlichen Kräften und Momenten an der Wirkstelle. Insbesondere für parallele Stabstrukturen und Parallelkinematiken -- und für die Messung mit 6 Freiheitsgraden speziell für Hexapodstrukturen und Hexapoden -- ist der Ansatz aufgrund der nahezu reibungsfreien Messung vielversprechend. Gleichzeitig wirken jedoch prozess- und strukturbedingte Einflüsse auf die Kraftsensoren, die in Abhängigkeit der Sensorposition durch ein Messmodell kompensiert werden müssen. Für dynamische Messungen während der Maschinenbewegung müssen diese Messmodelle zwingend in Echtzeit im Steuerungskern berechnet werden und weiterhin durch ein Verfahren zur Parameteridentifikation schnell und einfach an der betriebsbereiten Maschine aktualisiert werden können. Diese Arbeit erforscht Möglichkeiten und Grenzen integrierter Kraftsensorik in starren Hexapodstrukturen und Hexapodkinematiken zur räumliche Prozesskraftmessung und -regelung an der Wirkstelle sowie die dazu notwendigen Messmodelle und Verfahren zur Parameteridentifikation. Für den Lösungsansatz kommen ausschließlich kostengünstige einachsige Standard-Kraftsensoren zum Einsatz, und die Validierung erfolgt auf Versuchsträgern mit kommerzieller Werkzeugmaschinensteuerung. Es werden systematisch mögliche Konfigurationen und Einbaupositionen identifiziert, die zugehörigen Messmodelle aufgestellt und Verfahren zur Auslegung und Berechnung aussagekräftiger Kenngrößen entwickelt. Anhand definierter Bewertungskriterien werden die Varianten in umfangreichen experimentellen Untersuchungen untereinander verglichen sowie zu den Standardlösungen der 6-Achs-Kraftmessplattform und der Kraftschätzung aus Antriebsströmen eingeordnet. Einen Schwerpunkt bildet die Messung während der Maschinenbewegung, bei der synchron zur Messung und abhängig von der Sensorplatzierung maschinen- und prozessbedingte Einflüsse online kompensiert werden müssen. Auf dieser Basis erfolgt anschließend die Entwicklung von Identifikationsverfahren zur schnellen und einfachen Parametrierung der Messmodelle an der betriebsbereiten Maschine durch automatisierbare Messzyklen. Schließlich werden mit den entwickelten Messsystemvarianten verschiedene Formen der Kraftregelung umgesetzt und die Ansätze so anwendungsnah validiert. Im Ergebnis liegen Methoden und Verfahren zur Aufstellung der Messmodelle, zur Auslegung der Kraftmesssysteme sowie zur Berechnung aussagekräftiger Kenngrößen vor. Zusammen mit der Validierung anhand verschiedener Anwendungsfälle wird ein Beitrag geleistet zur Qualifizierung der Unsicherheiten der räumlichen Kraftmessung mit integrierten Sensoren sowie der Auswirkung der Sensorintegration auf die Maschineneigenschaften. Die zwei entwickelten Verfahren zur Parameteridentifikation erlauben anhand der Kraftsignale aus quasi-statischen und dynamischen Eigenbewegungen der Maschine die schnelle Rekalibrierung der Messmodelle ohne Vorwissen oder Versuchsaufbauten in Bearbeitungspausen. Schließlich zeigen die zwei umgesetzten Varianten der räumlichen Kraftregelung die Eignung der strukturintegrierten Kraftmessung sowohl für das kraftgeregelte Teachen als auch für die Kontaktkraftregelung. / Today, in-process force measurement is required by many manufacturing applications. Beside process monitoring and diagnosis as well as quality assurance and validation, force controlled or adapted process management allows producing higher qualities or even enables new processes. With the extended movability of modern machine tools, such as five-axis kinematics or hexapods, the measurement of spatial forces and moments in up to 6 degrees of freedom is requested in particular. A new promising approach bases on the integration of multiple single-axis force sensors into the machine structure and the smart control-integrated signal transformation to forces and moments at the tool centre point. Especially for bar structures and kinematics, and for a measurement in 6 degrees of freedom for hexapod structures and kinematics, the approach is particularly suitable, as no friction is involved. At the same time, process and dynamic influences affect the force measurements and must be included into a real-time capable measurement model within the control kernel. As the model parameters can change during machine usage, a fast and simple calibration procedure is requested. This contribution explores capabilities and limits of integrated force sensors in rigid hexapod structures and hexapod kinematics for the sake of spatial process force measurement and control at the tool centre point as well as the required measurement models and parameter identification procedures. For practical relevant results, only commercial cost-efficient single-axis standard force sensors are used for this approach, and implementation as well as validation are performed on commercial machine tool controls. At first, possible configurations and sensor placements are evaluated systematically, measurement models are implemented, and methods for framework design as well as the calculation of meaningful criteria are investigated. Next, multiple variants of the new sensor systems are evaluated and classified in extensive experimental studies with regard to the state of the art, which is represented by force/torque sensors at the end-effector and force measurement from drive currents. A focal point is the measurement during machine movement, which requires a synchronous measurement of force and drive values to compensate dynamic influences in real-time. On that basis, different parameter identification procedures are investigated to update the measurement models with fast and simple procedures in an operational machine state by automatable measurement cycles. Finally, multiple variants of force control are implemented that use and validate the developed integrated force measuring systems. In conclusion, methods and procedures to design structure-integrated force sensor systems, to implement the required measurement models, and to calculate meaningful characteristics are available. By the evaluation and validation of the systems regarding to multiple use cases and with respect to the state of the art, this work qualifies capabilities, uncertainties, and limits of spatial structure-integrated force measurement as well as effects upon the machine characteristics. The two developed parameter identification procedures allow a fast and simple recalibration of the measurement models in operational machine state without requiring external knowledge or test setups. Finally, two realised methods of force control prove the capability of structure-integrated force measurement for force-controlled teaching as well as for contact control.

This paper shows an electrohydraulic control system to stabilize the chassis of a mobile machine driving across an off-road ground profile. The active hydraulic suspension system is based on new electronics, SW- and control architectures and the use of state of the art industrial components. The paper shows, that the static and dynamic performance of the system is dominated by the servo valve, which represents the central component of the system.

In advanced robot applications, the challenge today is that the robot should perform different successive subtasks to achieve one or more complicated tasks similar to human. Hence, this kind of tasks required to combine different kind of sensors in order to get full information about the work environment. However, from the point of view of control, more sensors mean more possibilities for the structure of the control system. As shown previously, vision and force sensors are the most common external sensors in robot system. As a result, in scientific papers it can be found numerous control algorithms and different structures for vision/force robot control, e.g. shared, traded control etc. The lacks in integration of vision/force robot control could be summarized as follows: • How to define which subspaces should be vision, position or force controlled? • When the controller should switch from one control mode to another one? • How to insure that the visual information could be reliably used? • How to define the most appropriated vision/force control structure? In many previous works, during performing a specified task one kind of vision/force control structure has been used which is pre-defined by the programmer. In addition to that, if the task is modified or changed, it would be much complicated for the user to describe the task and to define the most appropriated vision/force robot control especially if the user is inexperienced. Furthermore, vision and force sensors are used only as simple feedback (e.g. vision sensor is used usually as position estimator) or they are intended to avoid the obstacles. Accordingly, much useful information provided by the sensors which help the robot to perform the task autonomously is missed. In our opinion, these lacks of defining the most appropriate vision/force robot control and the weakness in the utilization from all the information which could be provided by the sensors introduce important limits which prevent the robot to be versatile, autonomous, dependable and user-friendly. For this purpose, helping to increase autonomy, versatility, dependability and user-friendly in certain area of robotics which requires vision/force integration is the scope of this thesis. More concretely: 1. Autonomy: In the term of an automatic decision system which defines the most appropriated vision/force control modes for different kinds of tasks and chooses the best structure of vision/force control depending on the surrounding environments and a priori knowledge. 2. Versatility: By preparing some relevant scenarios for different situations, where both the visual servoing and force control are necessary and indispensable. 3. Dependability: In the term of the robot should depend on its own sensors more than on reprogramming and human intervention. In other words, how the robot system can use all the available information which could be provided by the vision and force sensors, not only for the target object but also for the features extraction of the whole scene. 4. User-friendly: By designing a high level description of the task, the object and the sensor configuration which is suitable also for inexperienced user. If the previous properties are relatively achieved, the proposed robot system can: • Perform different successive and complex tasks. • Grasp/contact and track imprecisely placed objects with different poses. • Decide automatically the most appropriate combination of vision/force feedback for every task and react immediately to the changes from one control cycle to another because of occurrence of some unforeseen events. • Benefit from all the advantages of different vision/force control structures. • Benefit from all the information provided by the sensors. • Reduce the human intervention or reprogramming during the execution of the task. • Facilitate the task description and entering of a priori-knowledge for the user, even if he/she is inexperienced.