Approximative Models in Dynamic Control of Robotic Systems

Intelligent robotic systems are becoming essential for inspections and measurements in harsh environments. This article presents the design of an omnidirectional robotic platform for tunnel inspection with spatial limitations. This robot was born from the need to automate the surveillance process of the Super Proton Synchrotron (SPS) accelerator of the European Organization for Nuclear Research (CERN), where there is remaining radiation. The accelerator is located within a tunnel that is divided by small doors of 400 × 200 mm dimensions, through which the robot has to cross. The designed robot brings a robotic arm, and the needed devices to carry out the inspection. Thanks to this design, the robot application may vary by replacing certain devices and tools. In addition, this paper presents the kinematic and dynamic control models for the robotic platform.

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Dynamic control of distributed autonomous robotic systems with underlying three-index assignments

2000 26th Annual Conference of the IEEE Industrial Electronics Society. IECON 2000. 2000 IEEE International Conference on Industrial Electronics, Control and Instrumentation. 21st Century Technologies and Industrial Opportunities (Cat. No.00CH37141) ◽

10.1109/iecon.2000.972599 ◽

2002 ◽

Cited By ~ 1

Author(s):

J. Starke ◽

P. Molnar

Keyword(s):

Dynamic Control ◽

Robotic Systems ◽

Autonomous Robotic Systems

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KNOWLEDGE BASED ROBOTIC CONTROL AGAINST SATURATION OF ACTUATORS OWING TO FUZZY RULES

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001408006107 ◽

2008 ◽

Vol 22 (01) ◽

pp. 183-194 ◽

Cited By ~ 3

Author(s):

JIN-ZHUANG XIAO ◽

HONG-RUI WANG ◽

HONG-BIN WANG

Keyword(s):

Fault Tolerant ◽

Dynamic Control ◽

Control Process ◽

Robotic Manipulators ◽

Fuzzy Rules ◽

Robotic Systems ◽

Robotic Control ◽

Knowledge Based ◽

High Level ◽

The Given

Considering the decreasing performance of robotic systems under the constraints of actuators, this paper concludes the rules of dynamic control process and extracts the knowledge of optimizing the output of robotic controller based on the analysis of a Lyapunov function. Then fuzzy rules are used to express the knowledge and embedded in the controller to direct the dynamic control process. Under this controller, the systemic requirement of high-level outputs of the actuators is limited to a great extent, at the same time the convergent performance is optimized by a fuzzy-sets method from which the saturated fault tolerant control is realized in robotic manipulators. Simulating results on a 2-DOF robot validate the effectiveness of the given controller.

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