A New Concept for Learning Control Inspired by Brain Theory

The paper explains an unconventional learning control method based on assumptions in the literature about human problem solving and information storage in neuronal networks. The on-line learning comprises two stages: The dynamic input-output behaviour of the process to be controlled is stored stepwise in a neuron-like manner into an associative memory as a predictive process model, the control strategy planned via this model by optimization of a goal oriented performance index is then trained in the same way into a second associative memory. As a general mapping the learned behaviour is in both cases in general nonlinear, and by this such a control design is especially suited for strongly nonlinear processes. Simulations demonstrate the applicability of the new control concept

An Associative Memory Based Learning Control Scheme with PI-Controller for SISO-Nonlinear Processes

The paper discusses the real-time implementation of an associative-memory-based learning control scheme with PI-controllers for nonlinear processes. Starting with a pre-assumed PI-controller which only has to stabilize the process the controller parameters are optimized on-line by a predictive optimization. This optimization uses for prediction the model of the process stored in an associative memory which is also learned on-line. The situation-dependent optimized controller parameters are also stored in an associative memory. The concept is a modification of the LERNAS-system (Ersü,1984), which is also shortly described and compared to the system described here. Some experimental results with a nonlinear pH-control demonstrate the performance of the system

Optical Proximity Sensor Systems for Intelligent Robot Hands

Optical proximity sensors are low-level vision sensors delivering low- and mid-range multidimensional information about the robots end-effector environment. Due to the fast signal processing they can be easily integrated in real-time robot control tasks. The paper presents the basic mechanical, hardware and software design principles of such a sensor, which uses distance measurement via optical triangulation as the basic method. For special robot tasks, special mechanical and hardware arrangements of the basic sensor type are needed. Two examples are shown for demonstration purposes. Possible applications are simple distance sensor devices, two-dimensional orientation sensors and optical robot teach-in units. Accuracy and efficiency of the sensor system are documented by using the sensor for recognizing holes and following arbitrary unknown contours

Konzepte zur Auslegung von Echtzeit-Bildverarbeitungssystemen für die Qualitätssicherung am Beispiel der Inspektion von Texturen

Bildverarbeitungssysteme werden in zunehmendem Maße für Aufgaben der Automatisierungstechnik und im besonderen in der Qualitätssicherung erfolgreich eingesetzt. Zur Lösung komplexer oder zeitkritischer Erkennungsaufgaben, wie z.B. in der Oberflächeninspektion und Texturanalyse, ist der Einsatz rechenintensiver Algorithmik erforderlich, so daß eine Softwarerealisierung nicht oder nur in speziellen Fällen möglich ist. Der vorliegende Beitrag zeigt Ansatzpunkte und Methoden zur Auslegung von Softwaresystemen zur Qualitätssicherung in Echtzeit am Beispiel der Inspektion texturierter Oberflächen auf Es werden merkmalsbasierte Verfahren diskutiert, wobei die ganzheitliche und zielorientierte Berücksichtigung aller Verfahrensschritte wesentlich ist. Zur Unterstützung des Designs von Bildverarbeitungslösungen werden automatische Verfahren der Systemkonfigurierung vorgestellt

A Robot Arithmetic Processor Concept for Cartesian Closed-Loop Control with Prescribed Dynamics

The hardware implementation of a cartesian closed-loop control scheme will be presented which allows to define the dynamic behaviour of each degree of freedom of the cartesian coordinate system in a prescribed sense. The control system at joint level is designed by multivariate design methods with an additional feedforward component using the concept of inverse dynamics. To achieve high accuracy for cartesian motions quasi-continuous control mode with cartesian sampling periods of not greater than 5 ms is aimed at. A special purpose processor for calculation of kinematic and dynamic terns is designed and integrated into a multiprocessor architecture. This implementation concept with Robot Arithmetic Processor provides the necessary computational power and allows real-time cartesian closed-loop control which is also essential for cartesian sensory control tasks

A Real-Time Knowledge Scheme for Sensory-Controlled Robot Assembly Tasks

In the field of assembly automation with industrial robots the research on the application of artificial intelligence techniques is getting increasing importance. This paper describes the hierarchical structure of a knowledge—based sensory-controlled robot assembly system under development which is capable to plan and execute assembly tasks under real—time requirements. The hybrid knowledge representation scheme combining the rule—based and object—oriented approach to represent the assembly domain—specific knowledge is discussed. Furtheron, the knowledge processing concept based upon the representation scheme is explained. A first prototype of the system has been implemented in a real robotic test—bed. Several peg/hole part mating sequences validated the capability of the system to execute assembly tasks in an uncertain environment using sensory information