Sensorless Fractional Order Control of PMSM Based on Synergetic and Sliding Mode Controllers

The work describes the new architecture of a fixed-point arithmetic unit. It is based on the use of integer arithmetic operations for which the information about the scale of the processed numbers is contained in the binary code of the arithmetic instruction being executed. Therefore, this approach is different from the typical way of implementing fixed-point operations on standard processors. The presented solution is also significantly different from the one used in floating-point arithmetic, as the decision to determine the appropriate scale is made at the stage of compiling the code and not during its execution. As a result, the real-time processing of real numbers is simplified and, therefore, faster. The described method provides a better ratio of the processing efficiency to the complexity of the digital system than other methods. In particular, the advantage of using the described method in FPGA-based embedded control systems should be indicated. Experimental tests on an industrial servo-drive confirm the correctness of the described solution.

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Different Ways Of Algorithms Implementation On Fpgamentioning

confidence: 99%

See 1 more Smart Citation

Fixed-Point Arithmetic Unit with a Scaling Mechanism for FPGA-Based Embedded Systems

Przybył¹

2021

“…Furthermore, sensorless control was granted by a sliding mode observer for the rotor position and the speed estimation. In [22], the SMC method was combined with a fractional order synergetic technique for speed and current control to deal with nonlinearities and uncertainties. Furthermore, a sliding mode observer was used to estimate the rotor position and speed, based on the motor voltages and currents, for sensorless operation.…”

Section: The Special Issuementioning

confidence: 99%

Advanced Control for Electric Drives: Current Challenges and Future Perspectives

Merabet

2020

In the Special Issue “Advanced Control for Electric Drives”, the objective is to address a variety of issues related to advances in control techniques for electric drives, implementation challenges, and applications in emerging fields such as electric vehicles, unmanned aerial vehicles, maglev trains and motion applications. This issue includes 15 selected and peer-reviewed articles discussing a wide range of topics, where intelligent control, estimation and observation schemes were applied to electric drives for various applications. Different drives were studied such as induction motors, permanent magnet synchronous motors and brushless direct current motors.

“…Another characteristic regarding the difficulty of harmonizing these models is that the mathematical models of electromechanical systems are continuous (which can be discretized with the usual methods) while the mathematical models of power electronic systems are hybrid (continuous-discrete). The rapid progress in computing technology and hardware in recent years has enabled the development of several directions for creating PMSM modelling and control strategies, based on predictive controllers [8,9], adaptive controllers [10,11], fuzzy controllers [12,13], or controllers based on artificial neural networks [14,15], but also controllers based on the fractional calculus [16,17] in order to improve the functionality of industrial installations. Moreover, to eliminate some of the transducers and mechanical parts which can decrease the reliability of the system, a series of observers has been developed for the estimation of the PMSM rotor speed and position [17][18][19][20][21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Sensorless Control of PMSM Based on Backstepping-PSO-Type Controller and ESO-Type Observer Using Real-Time Hardware

Nicola

Nicola²,

Selişteanu

2021

Self Cite

In the case of using a Permanent Magnet Synchronous Motor (PMSM) linear model of limited-range parametric variations and of relatively low dynamic of the load torque, the Field Oriented Control (FOC) type strategy ensures good performance of the PMSM control. Therefore, when using a non-linear model of wide-range parametric variations and of high dynamic of the load torque, a backstepping-type controller is proposed, whose tuning parameters are optimized by using a Particle Swarm Optimization (PSO) method. By designing an Extended State Observer (ESO), which provides a good estimate of the PMSM rotor position and speed under uncertainty conditions and with a response time shorter than that of the backstepping-type controller, this observer can be incorporated into the PMSM sensorless control system. The superior performance of the proposed sensorless control system based on the backstepping-PSO-type controller and an ESO-type observer is demonstrated through numerical simulations. Given that the real-time implementation of the control algorithms and observers in an embedded system is a difficult task, consisting of several steps, it is presented after the numerical simulations, which can be assimilated into the Software-in-the-Loop (SIL) step, the Processor-in-the-Loop (PIL) intermediate step, and the Hardware-in-the-Loop (HIL) final step. A comparison between the backstepping-PSO-type controller and the PI-PSO-type controller is presented by means of the real-time implementation of these controllers and demonstrates the superiority of the backstepping-PSO-type controller.