Research Article RobustEstimation-BasedControlStrategiesforInductionMotors FlorinStˆ ıng˘ a, 1 Marius Marian, 2 andDanSelis ¸teanu 1 1 Department of Automatic Control and Electronics, University of Craiova, A.I. Cuza No. 13, Craiova, RO 200585, Romania 2 DepartmentofComputersandInformationTechnology,UniversityofCraiova,A.I.CuzaNo.13,Craiova,RO200585,Romania Correspondence should be addressed to Dan Selis ¸teanu; dansel@automation.ucv.ro Received 18 January 2020; Accepted 26 June 2020; Published 29 July 2020 Academic Editor: Chongyang Liu Copyright©2020FlorinStˆ ıng˘ aetal.isisanopenaccessarticledistributedundertheCreativeCommonsAttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. is work proposes a realistic solution to the control problem of sensorless induction motors. Due to some important aspects related to their construction and reliability, the induction motors are extensively used in many modern industrial applications. Considering that the system is facing the lack of hardware sensors, the proposed complex control strategies are based on the estimation of unavailable system variables and parameters. In order to control the rotor speed, two robust control strategies are proposed: a modified super-twisting adaptive technique and a model predictive technique. e tests performed under several practicalassumptionsshowthattheclosedloopbehaviourofthesystemisadequate,andtheoutputvariablefollowstheimposed time varying reference, despite the considered uncertainties and disturbances acting on the process. 1.Introduction Nowadays, induction motors are facing an interesting challenge from the perspective of modelling and sensorless control. is is mainly caused by some particular, inherited operating conditions. In the last decades, due to the envi- ronmental rules imposed by the international institutions, the induction motors have been proposed to be a reliable solution for the usual drive systems. Regardingthecontroldesignofthesesystems,besidethe classicalscalarcontrolandvectorcontrolstrategies[1–3],in thelastyearsmodernapproacheshavebeenproposed,such as input-output linearization and nonlinear/sliding mode/ nonlinear predictive control strategies [4–6]. Two specific problems are found in practice: first, the modelsareuncertain[7,8]and,second,reliablephysicalsensors for the real-time measurements of process states [9] are un- available. e developed control strategies use the “software sensors” paradigm, as an achievable combination between software estimators/observers and hardware sensors [10–13]. e present work approaches a linked observ- er—estimator used to estimate the unmeasurable state and those parameters that are uncertain or unknown. e proposed reduced-order state observer is designed by using an appropriate linear transformation and provides the reconstruction of rotor fluxes. In what concern the esti- mation of unknown process parameters (e.g., the stator resistance) and of the load torque, acting as an external disturbance on the rotor, a parameter estimator and a disturbance observer were developed. e parameter esti- mator is derived from a typical one used in biotechnology applications[14,15].edisturbancesobserverprovidesan estimation result which can be used within a robust ob- server-based control method [16, 17]. Usingtheestimatesprovidedbytheproposedobservers, two control strategies were proposed: a modified super- twisting algorithm (STA) and a robust model predictive control (RMPC), designed such that the output (i.e., rotor speed) follows a chosen time-varying reference. e main objective of the super-twisting algorithm proposed by Levant in his work [18] is to reduce the chattering effect occurring in classical sliding mode control. Moreover, the algorithm must ensure the convergence and also resolve, in finite time, the tracking problem. In the recent studies, some practical and theoretical modified approaches of the original algorithm were proposed: adaptive gains super-twisting algorithm (AGSTA) used to provide some compensation of the smooth, bounded un- certainties and disturbances of the linear time invariant systems [19], multivariable super-twisting sliding mode Hindawi Complexity Volume 2020, Article ID 9235701, 14 pages https://doi.org/10.1155/2020/9235701