Induction motor (IM) drive systems are pivotal in modern industrial and commercial applications, driving essential processes and systems across various sectors efficiently and reliably. The accurate estimation of IM and load parameters is challenging but vital to guarantee the optimal performance of the entire drive system. The IEEE Standard 112A and existing online methods take hours to estimate only IM parameters after shutting down, disconnecting, estimating, reconnecting, and realigning the motor and its load using specialized tools. Offline techniques assume a known IM manufacturer datasheet, which is often unavailable. Therefore, this article proposes a novel online self-commissioning algorithm that estimates the parameters of an IM and its load in a remarkably swift time frame of just 180 s without disconnecting the IM from the load or using the IM manufacturer datasheet. The proposed method only requires the IM nameplate information and employs a discrete normalized model reference adaptive system. In addition, its computational burden is minimal, making it suitable for practical real-time implementation using the commercial and cost-effective microcontroller for power electronics, i.e., c2000 TMS320F28388D control platform. Comprehensive experimental results for fan-type loads driven by 1.1- and 7.5-kW IMs are discussed to validate the proposal.

Hybrid grid-connected renewable energy systems have gained significant importance in sustainably responding to an increased electrical energy demand. These are time-varying nonlinear dynamical plants, where the value of their parameters depends on changing weather conditions and the alternating grid voltage with randomly fluctuating amplitude. This paper proposes a robust cascade MRAC for nonlinear plants representing a class of these systems, which includes n renewable energy converts and a DC/AC single-phase full bridge inverter. The proposal reduces commissioning time by avoiding linearization and knowledge of the plant parameters. Moreover, it includes specific formulas for tuning the controller parameters that decrease their adjustments based on trial and error. Finally, it uses a direct adaptive method with adaptive laws having $\sigma \theta$ modification and an inner loop at least five times faster than the outer loop. The proposition validation includes the theoretical stability proof based on the Lyapunov stability method and Barbalat’s Lemma. Furthermore, it presents comparative simulation results with quoted cascade PI controllers for a monophasic system, including two renewable energy sources and injection. Both techniques effectively track setpoint changes of the energy sources’ currents and direct current bus voltage, showing the proposal similar or reduced ripple. At the same time, both ensure robustness against decreased photovoltage panels irradiance, increased fuel cells voltage, and grid voltage amplitude random fluctuations. However, the proposal does these things while avoiding prior linearization and unknowing the plant parameters.

The need for industrial and commercial machinery to maintain high torque while accurately following a variable angular speed is increasing. To meet this demand, induction motors (IMs) are commonly used with variable speed drives (VSDs) that employ a field-oriented control (FOC) scheme. Over the last thirty years, IMs have been replacing independent connection direct current motors due to their cost-effectiveness, reduced maintenance needs, and increased efficiency. However, IMs and VSDs exhibit nonlinear behavior, uncertainties, and disturbances. This paper proposes a robust combined adaptive passivity-based control (CAPBC) for this class of nonlinear systems that applies to angular rotor speed and stator current regulation inside an FOC scheme for IMs’ VSDs. It uses general Lyapunov-based design energy functions and adaptive laws with $\sigma$-modification to assure robustness after combining control and monitoring variables. Lyapunov’s second method and the Barbalat Lemma prove that the control and identification error tends to be zero over time. Moreover, comparative experimental results with a standard proportional–integral controller (PIC) and direct APBC show the proposed CAPBC’s effectiveness and robustness under normal and changing conditions.

Variable speed drives (VSDs) employing a V/f control dominate over 60% of industrial and commercial induction motor (IM) applications. This is the simplest VSD adjusted based on the motor nameplate information and obviates the need for complex full-parameter estimates, controller adjustments, or variable observers, which limits it to low starting torque pumping, fans, and air conditioning systems. This article introduces an enhanced V/f control-based VSD for IMs that expands the application range by increasing the starting torque to rated load conditions. Moreover, it significantly reduces the starting stator current, alleviating the electric power system. This is achieved by substituting the boost voltage with a direct current (dc) voltage and incorporating a single stator resistance estimate to consider stator drop voltage. The dc voltage is derived from a novel discrete Taylor series (TS) adaptive control system (ACS), which regulates the rated current during startup. The proposed method was successfully implemented on a VSD utilizing the c2000 TMS320F28388D control platform, requiring no additional hardware but minor algorithm adjustments, with no cost increase. Experimental validation involved two 0.25 kW parallel IMs under a Prony brake setup. A comparative analysis of the results shows significant advantages of the proposed method over some previously enhanced approaches.

The need for industrial and commercial machinery to maintain high torque while accurately following a variable angular speed is increasing. To meet this demand, induction motors (IMs) are commonly used with variable speed drives (VSDs) that employ a field-oriented control (FOC) scheme. Over the last thirty years, IMs have been replacing independent connection direct current motors due to their cost-effectiveness, reduced maintenance needs, and increased efficiency. However, IMs and VSDs exhibit nonlinear behavior, uncertainties, and disturbances. This paper proposes a robust combined adaptive passivity-based control (CAPBC) for this class of nonlinear systems that applies to angular rotor speed and stator current regulation inside an FOC scheme for IMs´ VSDs. It uses general Lyapunov-based design energy functions and adaptive laws with σ-modification to assure robustness after combining control and monitoring variables. Lyapunov’s second method and Barbalat Lemma prove that the control and identification error tends to be zero over time. Moreover, comparative experimental results with standard Proportional Integer controller (PIC) and direct APBC, show the proposed CAPBC effectiveness and robustness under normal and changing conditions