Anti-disturbance observer-based proportional-retarded control design for polytopic uncertain fractional-order systems

Abstract

This study deals with the stabilisation problem of fractional-order time-delay systems with polytopic uncertainties and multiple disturbances with the use of Lyapunov stability theory. Notably, the multiple disturbances comprising both the known and unknown signals, are respectively characterised by the norm-bounded and exogenous system which signifies the harmonic signals with modelling perturbations. The control protocol is configured by the integration of proportional-retarded controller with gain perturbations and the output of an anti-disturbance observer. Precisely, the disturbance observer is taken into account for attenuating the influence of disturbance signals. Moreover, the implementation of a time-delay term in the feedback loop replicates the dynamic features of a derivative action that relies only on position measurements and its time differencing capabilities make it to be minimally sensitive against noise and provide a smoothing effect. By virtue of these circumstances, the asymptotic stability of the considered system is assured. With the aid of a suitable Lyapunov function, a set of robust order-dependent sufficient conditions is derived and then solved through the MATLAB LMI toolbox. As a result, the controller gain matrices can be computed and two numerical examples, including an electrical circuit model with simulation results are presented to certify the inherent potential of the theoretical outcomes.

Keywords:

• Fractional-order time-delay systems
• disturbance observer
• proportional-retarded control
• polytopic uncertainty

Acknowledgments

The work of S. Sweetha was financially supported by Department of Science and Technology, Government of India through DST-INSPIRE Research Fellowship vide sanction No. DST/INSPIRE FELLOWSHIP/2018/IF180599.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Availability of data and material Data sharing not applicable to this article as no datasets were generated or analysed during the current study.