Issue 2 (192), article 3
Kibern. vyčisl. teh., 2018, Issue 2 (192), pp.
Acting Head of the Department of Intelligent Automatic Systems
International Research and Training Center for Information Technologies
and Systems of the National Academy of Science of Ukraine
and Ministry of Education and Sciences of Ukraine, Kiev, Ukraine,
Acad. Glushkova av., 40, Kiev, 03187, Ukraine
ADAPTIVE STABILIZATION OF SOME MULTIVARIABLE SYSTEMS WITH NONSQUARE GAIN MATRICES OF FULL RANK
Introduction. The paper states and solves a new problem concerning the adaptive stabilization of a specific class of linear multivariable discrete-time memoryless systems with nonsquare gain matrices at their equilibrium states. This class includes the multivariable systems in which the number of outputs exceeds the number of control inputs. It is assumed that the unknown gain matrices have full rank.
The purpose of this paper is to answer the question of how the pseudoinverse model-based adaptive approach might be utilized to deal with the uncertain multivariable memoryless system if the number of control inputs is less than the number of outputs.
Results. It is shown that the parameter estimates generated by the standard adaptive projection recursive procedure converge always to some finite values for any initial values of system’s parameters. Based on these ultimate features, it is proved that the adaptive pseudoinverse model-based control law makes it possible to achieve the equilibrium state of the nonsquare system to be controlled. The asymptotical properties of the adaptive feedback control system derived theoretically are substantiated by a simulation experiment.
Conclusion. It is established that the ultimate behavior of the closed-loop control system utilizing the adaptive pseudoinverse model-based concept is satisfactory.
Keywords: adaptive control, multivariable system, discrete time, feedback, pseudoinversion, stability, uncertainty.
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