DESIGN OF THE CONTROL SYSTEM BY MOVEMENT OF ROBOTS MOBILE GROUP IN CONDITIONS OF UNCERTAINTY
| Autor: | Anatoliy Gaiduk, I. A. Kalyaev, Sergey Kapustyan, I. O. Shapovalov |
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| Rok vydání: | 2018 |
| Předmět: | |
| Zdroj: | Proceedings of the Southwest State University. 22:112-122 |
| ISSN: | 2686-6757 2223-1560 |
| Popis: | Many controlled plants, in particular mobile robots, solve various tasks in a priori uncertain conditions. In this connection their mathematical models necessary for creation of qualitative control systems are unknown. Therefore development of design methods of adaptive control systems is actuality. The big uncertainty of this control problem makes application of adaptive systems with identification by the most expedient. In article the new analytical design method of adaptive control systems by movement of mobile robots group in the uncertainty conditions is offered. This method is focused on the decision of a task of identification of the current mathematical models of robots with the subsequent design of a control system by movement of each robot. The suggested method can be realized automatically as required. It is developed on a basis of the markov method of identification, the method of analytical design of systems with control on output and impacts, and also the standard normalized transfer functions are used. As a whole this method allows to design of the adaptive control systems with desirable qualitative properties. Trial step functions of the small intensity and the original method of digital processing of the information are used at identification. Property of system invariancy of the markov parameters and their direct connection with factors of the discrete dynamic systems transfer functions are a basis of the method of digital processing of the information. It is supposed, that the mobile robots are full or can be stabilized at all possible values of their order and parameters. The suggested method can be used for creation of control systems by the various technical plants functioning in conditions of uncertainty. |
| Databáze: | OpenAIRE |
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