Design and implementation of adaptive fuzzy‐RST digital speed control of PMSM drive

Toumi, Djilali; Youcef, Mihoub; Hassaine, Said; Moreau, Sandrine

doi:10.1002/asjc.2683

Cited by 4 publications

(3 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The DI-FGS presented in Figure 5 is the most employed GS structure by the researchers. 39,40 For a desired mechanical speed ω m * , it uses and processes error e = ω m * − ω m and the derivative of error Δ e information to generate the scheduling variables δ K P and δ K I . However, in real-world applications, implementing the differentiator in the DI-FGS-PI structure is a challenge since it is sensitive to noise.…”

Section: Design Of Fgs Speed Controllersmentioning

confidence: 99%

Designing practical fuzzy gain scheduling controllers for micromobility applications of permanent magnet synchronous machines

Gul,

Kacar,

Aziziaghdam

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part I:

View full text Add to dashboard Cite

In micromobility applications, maintaining satisfactory motor drive performance in the full torque-speed envelope of an outer rotor non-salient permanent magnet synchronous machine is a challenge due to the drastic performance degradation with the increasing non-linearity above the nominal ratings of the motor. In this article, we tackle this challenge via fuzzy gain scheduling proportional–integral speed controllers that have been designed by taking into account practical considerations. On the basis of experimental voltage ripple analyses conducted on the speed control loop with different system characteristics, we develop a single-input fuzzy gain scheduling proportional–integral speed controller and a double-input fuzzy gain scheduling proportional–integral speed controller to reduce the voltage ripples while providing satisfactory dynamical performance. The proposed structures continuously adjust the characteristics of the speed control loop within a specified region to exhibit different dynamical system characteristics against varying conditions. It is verified by the experimental test results that the proposed structures successfully reduced the increasing voltage ripples as the disturbances increase while providing satisfactory dynamical performance. Finally, we provided a discussion on the trade-off between the proposed structures and suggested deploying single-input fuzzy gain scheduling proportional–integral controller for micromobility speed control applications as it is agnostic to noise to a certain degree hence offering better reliability.

show abstract

Section: Design Of Fgs Speed Controllersmentioning

confidence: 99%

Designing practical fuzzy gain scheduling controllers for micromobility applications of permanent magnet synchronous machines

Gul,

Kacar,

Aziziaghdam

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part I:

View full text Add to dashboard Cite

show abstract

“…In [17], an Adaptive Nonlinear Continuous Observer (ANCO) is used to estimate the self-induction coefficient, stator resistance, rotor velocity/position, and load torque by using the current measurements for the PMSM. In [18], adaptive fuzzy RST digital control (AFRSTD), digital control, and fuzzy digital RST control are generated for a PMSM system. In [19], a Sliding Mode focused on an Extended State Observer (SMESO) and Fast Terminal Sliding Mode Control (FTSMC) is recommended to develop disturbance elimination capacity and increase the dynamic performance of PMSM drive systems.…”

Section: Introductionmentioning

confidence: 99%

Observer-Based Suboptimal Controller Design for Permanent Magnet Synchronous Motors: State-Dependent Riccati Equation Controller and Impulsive Observer Approaches

Kalamian,

Soltani,

Bouzari Liavoli

et al. 2024

Computers

View full text Add to dashboard Cite

Permanent Magnet Synchronous Motors (PMSMs) with high energy efficiency, reliable performance, and a relatively simple structure are widely utilised in various applications. In this paper, a suboptimal controller is proposed for PMSMs without sensors based on the state-dependent Riccati equation (SDRE) technique combined with customised impulsive observers (IOs). Here, the SDRE technique facilitates a pseudo-linearised display of the motor with state-dependent coefficients (SDCs) while preserving all its nonlinear features. Considering the risk of non-available/non-measurable states in the motor due to sensor and instrumentation costs, the SDRE is combined with IOs to estimate the PMSM speed and position states. Customised IOs are proven to be capable of obtaining quality, continuous estimates of the motor states despite the discrete format of the output signals. The simulation results in this work illustrate an accurate state estimation and control mechanism for the speed of the PMSM in the presence of load torque disturbances and reference speed changes. It is clearly shown that the SDRE-IO design is superior compared to the most popular existing regulators in the literature for sensorless speed control.

show abstract

“…In order to achieve better control performance and meet the requirement of cutting accuracy, the introduction of intelligent control theory and improved excitation controller are recognised as both reliable and economically efficient methods. In servo control systems, there are various control algorithms such as artificial neural networks, robust, iterative and adaptive control algorithms 8,14 . These control algorithms are widely used in the field of high-precision control.…”

mentioning

confidence: 99%

Optimization of X-axis servo drive performance using PSO fuzzy control technique for double-axis dicing saw

Cao,

Zhang,

et al. 2023

Sci Rep

View full text Add to dashboard Cite

The dicing saw is a critical piece of equipment in IC processing, primarily used to cut wafers. Due to the high spindle speed, even small errors in the cutting process can result in wafer chipping or cracking. Therefore, the dicing saw requires a high degree of accuracy and stability. In this paper, the accuracy of the X-axis servo response was simulated using an Israeli ADT-8230 dual-axis abrasive wheel dicing saw. The study introduces a novel approach by using a fuzzy controller instead of the traditional position loop proportional integral (PI) controller. In addition, a two-input, two-output fuzzy rule is used for on-line correction of the position loop PI parameters. A heuristic algorithm is used to optimise the position loop fuzzy controller parameters. The quantization and proportionality factors are rectified using Particle Swarm Optimisation (PSO) algorithm and Genetic Algorithm (GA) respectively. By comparing the performance of the PSO fuzzy and GA fuzzy controllers, the optimal control method is derived. The proposed method is validated by simulation in the MATLAB/Simulink development environment using real ADT-8230 servo data. Experimental results show that the PSO-fuzzy structured controller reduces the position control error by 11.8%, improves the tracking performance by 26% and reduces the torque pulsation by 23%. Therefore, in future research, more advanced search algorithms should be further combined to improve the servo accuracy of the dicing saw.

show abstract

Design and implementation of adaptive fuzzy‐RST digital speed control of PMSM drive

Cited by 4 publications

References 32 publications

Designing practical fuzzy gain scheduling controllers for micromobility applications of permanent magnet synchronous machines

Designing practical fuzzy gain scheduling controllers for micromobility applications of permanent magnet synchronous machines

Observer-Based Suboptimal Controller Design for Permanent Magnet Synchronous Motors: State-Dependent Riccati Equation Controller and Impulsive Observer Approaches

Optimization of X-axis servo drive performance using PSO fuzzy control technique for double-axis dicing saw

Contact Info

Product

Resources

About