Hybrid Dynamical Modeling and Control of Permanent Magnet Synchronous Motors: Hardware-in-the-Loop Verification

The stabilization of a permanent magnet synchronous motor using digital controllers requires the design of both the feedback law and an appropriate sampling frequency. Moreover, the design approach must be robust against existing uncertainties, such as disturbances and parameter variations. In this paper, we develop a stabilizing state feedback nonlinear control scheme for the permanent magnet synchronous motor. Moreover, we consider the case where the feedback signal is transmitted over a digital platform, and we derive the stabilizing sampling frequency, such that the stability of the closed-loop system is maintained. We design the controller by emulation, where the closed-loop stability is first established in continuous time; we then take into account the effect of sampling. The feedback law consists of two parts: feedback linearization and robust linear quadratic regulator for the linearized mode. The robustness is achieved by augmenting the state space model, with additional states representing the tracking errors of the motor speed and the motor current. Then, to cope with sampling, we estimate the maximally allowable sampling interval to reduce the sampling frequency while preserving the closed-loop stability. The overall system is modeled as a hybrid dynamical system, which allows handling both the continuous-time and discrete-time dynamics. The effectiveness of the proposed technique is illustrated by simulation and verified experimentally using a hardware-in-the-loop setup. Upon implementing the proposed approach, the obtained sampling interval was around 91 ms, making it suitable for digital implementation setups

Modified Primary Flux Linkage for Enhancing the Linear Induction Motor Performance Based on Sliding Mode Control and Model Predictive Flux Control

This paper proposes a modified primary flux linkage and an improved weighting less model predictive control for linear induction motors (LIMs) to enhance the drive system in terms of linear speed response, wide speed range, efficiency, and computation time. Sliding mode controller is presented in this work to get quick response instead of the use of the PI controller. A weighting less model predictive flux control (MPFC) is employed to eliminate the weighting factor and reduce the computation time. Furthermore, the optimum value of the primary flux linkage is calculated to guarantee higher efficiency under the operation of maximum thrust per ampere, loss minimization control and wider speed range in the field weakening region. The FCS-MPFC uses only the primary flux in the cost function independent on the weighting factor. Moreover, simplified calculation process can be executed greatly in the $\alpha \beta$ -coordinates without transformation matrix, where the end-effect is fully taken into consideration. In comparison with the PI controller under different conditions, the proposed control method can achieve faster dynamics with lower thrust ripple, computation time, and so on. Comprehensive simulation and experimental results based on one prototype with 3 kW linear induction machine have verified the advantages of the proposed strategy in this work

Evaluation of renewable and energy storage system-based interlinked power system with artificial rabbit optimized PI(FOPD) cascaded controller

This research work addresses automatic generation control of multiple arenas and causes under various system disturbances. Sources within arena-1 comprises thermal, bio-diesel, in arena-2 sources represent thermal elements, in arena-3 sources are thermal and hydro units. An innovative endeavor has been undertaken to employ conglomerate controller with the amalgamation of proportional-integral (PI) (integer-order) in addition fractional order proportional-derivative (FOPD). Various examination manifests the fineness of PI(FOPD) overtop additional integer order controllers from perspective concerning reduced grade of crown overshoot, expanse-of-instabilities, crown undershoot in addition to subsiding period. In determination to attain the controller’s features biologically enthused meta-heuristic artificial rabbit optimization is pragmatic. The minimum cost function value has been achieved as 0.000309 for the artificial rabbit optimization in comparison to various established optimization technique along with the proposed PI(FOPD) controller. It is likewise detected that occurrence of inexhaustible sources like realistic dish-Stirling thermal system in arena-1, geothermal power plant and precise wind turbine system styles the structure meaningfully improved related to origin structure when judged exclusively or all together. Accomplishment in presence of interline power flow controller besides combination of energy stowage elements alike redox flow battery in addition solid oxide fuel cell is as well inspected using PI(FOPD) controller, that offers with notable consequence in dynamic presentation in each cases separately. It has been clearly observed that in presence of all the renewables, in case of frequency deviation crown overshoot, crown undershoot, and subsiding period are 0.0053, 0.0131, and 24.32 respectively. These values are showing improvements in comparison to the individual presence of renewables in each arena. Similarly, with the presence of both SOFC and RFB for tie line power between arena-1 and areana-3, the crown overshoot, crown undershoot, and subsiding period are 0.00018, 0.0013, and 22.63 respectively. These values are showing improvements in comparison to the individual presence of Solid Oxide Fuel Cell without battery energy storage in each arena. Also, PI(FOPD) parameters values at nominal condition are appropriate for random pattern of disturbance needs no optimization, which justified the reliability of the suggested controller.© 2017 Elsevier Inc. All rights reserved

Finite State Model Predictive Thrust Control Based on Reduced Number of Predicted Voltage Vectors for Linear Induction Motor

The computational burden represents a challenge nowadays, especially with the advancement of new control techniques, such as model predictive control. Therefore, this paper presents an improved finite-state model predictive thrust control (FS-MPTC) for linear induction motor (LIM). The proposed FS-MPTC uses in the prediction stage half of the available voltage vectors (VVs), The proposed method combines the conventional direct thrust control (DTC) and the FS-MPTC. Eliminating half of the voltage vectors during the prediction stage leads to a significant reduction in computational burden and hence gives the chance to use another technique to improve the overall drive performance. The behavior of the proposed FS-MPTC is examined through simulation results using the parameter of the actual 3kW arc machine. Comprehensive simulation and experimental results have proved that the proposed FS-MPTC can get same the response with shorter computation time compared to the conventional method