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고석조,이민철,홍창우 한국공작기계학회 2002 한국공작기계학회 춘계학술대회논문집 Vol.2002 No.-
In the previous study, a polishing robot system was developed to automate the polishing process and to cope with the shortage of skilled workers. This polishing robot system has several advantages: reduced time for setting polishing work, decreased labor costs, effective operation, continuous polishing work without an operator, improved machine accuracy, and the ability to polish a free curved surface die. However, still the problem remains that a worker must stay to monitor the polishing process in the poor working conditions for a long time. Nowadays some advanced manufacturing companies need to find a way to check the performance of their production equipments and plants from remote sites. Thus, this study constructed the communication network and developed the monitoring programs (a servo program and a client program) to operate the polishing robot from remote sites. Using these programs, workers are able to monitor and control the polishing robot on the web page, in any place where internet service is possible. To guarantee a stable operation in spite of a variable computer operating environment, the monitoring system is implemented in Java. The experimental results showed that the developed monitoring programs provided a stable communication.
Fuzzy-Sliding Mode Control of a Polishing Robot Based on Genetic Algorithm
Go, Seok-Jo,Lee, Min-Cheol,Park, Min-Kyu The Korean Society of Mechanical Engineers 2001 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.15 No.5
This paper proposes a fuzzy-sliding mode control which is designed by a self tuning fuzzy inference method based on a genetic algorithm. Using the method, the number of inference rules and the shape of the membership functions of the proposed fuzzy-sliding mode control are optimized without the aid of an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. It is further guaranteed that the selected solution becomes the global optimal solution by optimizing Akaikes information criterion expressing the quality of the inference rules. In order to evaluate the learning performance of the proposed fuzzy-sliding mode control based on a genetic algorithm, a trajectory tracking simulation of the polishing robot is carried out. Simulation results show that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the trajectory control result is similar to the result of the fuzzy-sliding mode control which is selected through trial error by an expert. Therefore, a designer who does not have expert knowledge of robot systems can design the fuzzy-sliding mode controller using the proposed self tuning fuzzy inference method based on the genetic algorithm.
Design of a Fuzzy-Sliding Mode Controller for a SCARA Robot to Reduce Chattering
Go, Seok-Jo,Lee, Min-Cheol The Korean Society of Mechanical Engineers 2001 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.15 No.3
To overcome problems in tracking error related to the unmodeled dynamics in the high speed operation of industrial robots, many researchers have used sliding mode control, which is robust against parameter variations and payload changes. However, these algorithms cannot reduce the inherent chattering which is caused by excessive switching inputs around the sliding surface. This study proposes a fuzzy-sliding mode control algorithm to reduce the chattering of the sliding mode control by fuzzy rules within a pre-determined dead zone. Trajectory tracking simulations and experiments show that chattering can be reduced prominently by the fuzzy-sliding mode control algorithm compared to a sliding mode control with two dead zones, and the proposed control algorithm is robust to changes in payload. The proposed control algorithm is implemented to the SCARA (selected compliance articulated robot assembly) robot using a DSP (digital signal processor) for high speed calculations.