Field-oriented control based on parallel proportional–integral controllers of induction motor drive

In the chemical industry, a reactor is an absolutely necessary container. The fact that its dynamic qualities are nonlinear and unknown, however, is what causes the temperature to deviate from the value that was specified. As a result, the typical PID control cannot fulfill the prerequisites of the production process. A new nonlinear function is presented to replace the function that was previously used, and a temperature controller that is based on better fractional order active disturbance rejection is devised. On the basis of a new fractional order temperature detector (FOTD), a new fractional order equilibrium state observer (FOESO), and nonlinear function, an improved fractional order active disturbance rejection controller has been developed. A model of the reactor was created, and the dynamic properties of temperature control were investigated. By simulation and experimentation, it was demonstrated that the strategy has a number of benefits and is effective. In this approach, the information provided by the model is exploited to its maximum potential, and the temperature of the inlet cooling water is employed as the temperature control disturbance for feedforward compensation. Over the entirety of the process, this guarantees that the desired temperature will be preserved. When compared to FADRC, PID, and ADRC, the rising time is increased by 5 s, and the overshoot is raised by 25%. It has been established that the fraction-order active disturbance rejection controller has a quicker response speed, a higher capacity for anti-interference, and a quicker speed of stabilization.

/pdf/reactor-temperature-control-based-on-improved-fractional-2j4wavgi.pdf

Reactor Temperature Control Based on Improved Fractional Order Self-Anti-Disturbance

The skin effect in modeling an induction motor can be described by fractional differential equations. The existing methods for identifying the parameters of an induction motor with a rotor skin effect suggest the presence of errors only in the output. The presence of errors in measuring currents and voltages leads to errors in both input and output signals. Applying standard methods, such as the ordinary least squares method, leads to biased estimates in these types of problems. The study proposes a new method for identifying the parameters of an induction motor in the presence of a skin effect. Estimates of parameters were determined based on generalized total least squares. The simulation results obtained showed the high accuracy of the obtained estimates. The results of this research can be applied in the development of predictive diagnostic systems. This study shows that ordinary least squares parameter estimates can lead to incorrect operation of the fault diagnosis system.

/pdf/identification-of-fractional-models-of-an-induction-motor-1fr045wb.pdf

Identification of Fractional Models of an Induction Motor with Errors in Variables

Control strategies for grid-connected hybrid renewable energy systems: Integrating modified direct torque control based doubly fed induction generator and ANFIS based maximum power point tracking for solar PV generation

The article introduces a new model of a Reference Signal Tracking (RST) controller for the fractional order quantities. The controller is applied to an indirect field‐oriented control (IFOC) system used for the speed control of an asynchronous motor powered by a photovoltaic (PV) generator with a maximum power point tracking (MPPT) algorithm. This model utilizes two fractional order controllers: the fractional order proportional‐integral (FOPI) regulator and the fractional‐order integral‐proportional (FOIP) regulator. These controllers are used with the generalized predictive control (GPC) technique. The first step in the approach is to derive the equivalent digital RST controller's model from the FOPI and FOIP controller's transfer functions. The GPC technique converts the continuous‐time FOPI (and FOIP) controller into a discrete‐time version. This conversion ensures a fast response and effective disturbance rejection. Simulation tests are conducted to analyze the rotor speed and stator current ripples to evaluate the performance of the proposed method. The results demonstrate the effectiveness of the introduced scheme in achieving improved control performance in terms of response speed and disturbance rejection. The article presents a modified RST controller model based on the fractional order approach applied to an IFOC system for motor speed control driven by a photovoltaic generator. Using FOPI, FOIP controllers, and GPC contributes to enhanced control performance, as evidenced by the simulation results.

Driving an asynchronous motor powered by PV‐MPPT using equivalent RST controller of fractional order PI and IP, based on generalized predictive control

Agriculture activities are completely dependent upon energy production worldwide. This research presents sensorless speed control of a three-phase induction motor aided with an extended Kalman filter (EKF). Although a proportional integral (PI) controller can ensure tracking of the rotor speed, a considerable magnitude of ripples is present in the torque generated by a motor. Adding a simple derivative to have a proportional integral derivative (PID) action can cause a further increase in ripple magnitude, as it allows the addition of high-frequency noise in the system. Therefore, a fractional-order-based PID control is presented. The proposed control scheme is applied in a closed loop with the system, and simulation results are compared with the PID controller. It is evident from the results that the fractional order control not only ensures 20 times faster tracking, but ripple magnitude in torque was also reduced by a factor of 50% compared to that while using PID and ensures the effectiveness of the proposed strategy.

https://www.mdpi.com/1996-1073/16/4/1901/pdf?version=1676454850

A Fractional Order Controller for Sensorless Speed Control of an Induction Motor

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A Fractional Order Controller for Sensorless Speed Control of an Induction Motor