Litcius/Paper detail

Fixed-Time-Convergent Generalized Extended State Observer Based Motor Control Subject to Multiple Disturbances

Minnan Piao, Ying Wang, Mingwei Sun, Xinhua Zhang, Zengqiang Chen, Yongyi Yan

2021IEEE Transactions on Industrial Informatics53 citationsDOI

Abstract

Inertia load change, torque disturbance, and sophisticated mechanical nonlinearity impose great challenge on the high-precision control design of motor servo systems. To achieve better tracking and disturbance rejection performance, a practical control scheme, which combines a fixed-time-convergent generalized extended state observer (FGESO) with a fixed-time-convergent state feedback control law, is proposed in this article. First, an FGESO is designed to estimate the lumped disturbance and the fixed-time convergence of the estimation errors can be achieved. In the FGESO, there are three parameters and the correction term is selected as a continuous switching function of the output estimation error, which can facilitate the tuning process and greatly alleviate the chattering problem. Second, a control law based on the bilimit homogeneity technique is provided to regulate the tracking errors within a finite time independent of the initial condition. The fixed-time stability of the closed-loop system can be rigorously proved based on the Lyapunov theory. To facilitate the application of the proposed method, a practical two-step tuning procedure is established. Finally, extensive simulations and experiments are performed on a brushless direct current motor to validate the effectiveness and robustness of the proposed method.

Topics & Concepts

Control theory (sociology)Robustness (evolution)Computer scienceLyapunov functionInertiaConvergence (economics)Nonlinear systemState observerRobust controlTorqueServomechanismControl engineeringControl systemEngineeringControl (management)Artificial intelligenceEconomic growthPhysicsClassical mechanicsEconomicsChemistryElectrical engineeringThermodynamicsGeneBiochemistryQuantum mechanicsAdaptive Control of Nonlinear SystemsIterative Learning Control SystemsControl Systems in Engineering