Statistical Optimal Controller for AGV’s to achieve High Index of Performance (IP)
Sangeeta Jana1, Malay K. Pandit2, Asim K. Jana3
1Sangeeta Jana, Assistant Professor, Department of Instrumentation and Control Engineering, Haldia Institute of Technology Haldia, West Bengal, India..
2Dr. Malay K. Pandit, Department of electronics and Communication Engineering Haldia Institute of Technology, Haldia, India.
3Asim K. Jana, Department of electronics and Communication Engineering Haldia Institute of Technology, Haldia, India.
Manuscript received on March 02, 2012. | Revised Manuscript received on March 31, 2012. | Manuscript published on April 30, 2012. | PP: 237-241 | Volume-1 Issue-4, April 2012 | Retrieval Number: D0305041412/2012©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper exhibits a new optimal control two simultaneous processes: velocity and speed control in an embedded controller for an AGV (autonomous guided vehicle) in uncertain situations. This technique has been used to fuse information from internal and external sensors to navigate the AGV in an unmapped environment or in case of uncertainty. Uncertainty, the lack of certainty, A state of having limited knowledge where it is impossible to exactly describe existing state or future outcome, more than one possible outcomes. We have optimized speed and position error that contribute to the motion control problems of an AGV. During the movement of an AGV, whether straight or arc create position and orientation errors. The main concern is to achieve the real time and robustness performance to precisely control the AGV movements. We report here for the first time a novel optimization method based on Markov chain.
Keywords: Uncertainty, Robust, system index performance, probability of system error.