A Survey of Fuzzy Algorithms Used in Multi-Motor Systems Control

Štil, Vedrana Jerković; Varga, Toni; Benšić, Tin; Barukčić, Marinko

doi:10.3390/electronics9111788

Cited by 35 publications

(14 citation statements)

References 38 publications

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“…where e = k e Ω M = k m i a (2) The motor parameters are as follows: P n = 1 kW, U n = 220 V, n n = 3000 rot./min, η = 0.75, p = 2, J = 0.006 kgm 2 , M n = P n /Ω n = 3.2 Nm, Ω n = 2 πn n /60 = 314 rad/s, I n = P n /η/U n = 6 A, I M = I lim = 1.8 I n = 10.8 A, R a = 0.055 U n /I n = 2.01 Ω, L a = 5.6 U n /n n /p/I n = 0.034 H, T a = L a /R a = 0.017 ms, k e = (U n − I n R a )/Ω n = 0.664 Vs, k m = M n /I n = 0.533 Nm/A, k f = 0.08 M n /Ω n = 8.10 −4 Nms. The parameters of the current regulator, those of the power converter and of the current and speed sensors are: K RGi = 0.2, T RGi = T a = 0.017 ms, K EE = 22, T EE = 0.8 ms, K Ti = 1 A −1 , T Ti = 4 ms, K TΩ = 0.1 π/Vs, T TΩ = 10 ms.…”

Section: Control Structurementioning

confidence: 99%

“…The study presented in this paper fits into the broader context of the mathematics of fuzzy controllers, Mamdani structures, and the control of electric drives, as well as the industrial application of fuzzy control systems. Various scientific papers have appeared in the literature for many years, presenting examples of the use of fuzzy logic in regulating the speed of electric drives [1,2]. The paper [3] addresses a variety of issues related to advances in control techniques for electric drives in emerging fields such as electric vehicles, UAVs, trains, and motion control.…”

Section: Introductionmentioning

confidence: 99%

“…Figure 6. The first equivalent control structure.The fuzzy block works on the discourse universe[−1, 1], x t1 ∈ [−2,2]. The family of characteristics di d = f (x t1 ; de) is shown in Figure7.…”

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confidence: 99%

See 2 more Smart Citations

Stability Analysis of Systems with Fuzzy PI Controllers Applied to Electric Drives

Voloşencu

2021

Mathematics

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This paper analyzes the stability of fuzzy control systems with applications for electric drives. Ensuring the stability of these systems is a necessity in practice. The purpose of the study is the analysis of the dynamic characteristics of the speed control systems of electric drives based on fuzzy PI controllers in the context of performing stability analyses, both internal and input–output, finding solutions to stabilize these systems and provide guidance on fuzzy regulator design. The main methods of treatment applied are as follows: framing the control system in the theory of stability of multivariable non-linear systems, application of Lyapunov’s theory, performing an input–output stability analysis, and verification of the stability domain. The article presents the conditions for correcting the fuzzy controller to ensure internal and external stability, determines the limits of the stability sector, and gives indications for choosing the parameters of the controller. The considerations presented can be applied to various structures for regulating the speed of electric drives which use various PI fuzzy controllers.

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Section: Control Structurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Stability Analysis of Systems with Fuzzy PI Controllers Applied to Electric Drives

Voloşencu

2021

Mathematics

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“…By using the fuzzification component, the inputs are converted to the values in the fuzzy domain. Based on the standardization control theory, the fuzzy domain can be set as [−1, 1] [40]. Therefore, K in can be set as the reciprocal of the maximum position error ∆θ max , namely,…”

Section: Design Of Fuzzy Controller 421 Fuzzificationmentioning

confidence: 99%

Intelligent Permanent Magnet Motor-Based Servo Drive System Used for Automated Tuning of Piano

Zhou

2021

Energies

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This paper presents an intelligent permanent magnet synchronous motor-based servo drive system used in automated piano tuning applications. The permanent magnet synchronous motor-based drives are able to improve the accuracy of the piano tuning process in comparison with the traditional direct-current motor-based and step motor-based servo drives. To explain the techniques, firstly, the structure and principles of the automated piano tuning devices with a surface-mounted permanent magnet synchronous motor-based drive system integrated are introduced, illustrating that it is feasible to implement the proposed piano tuning strategy. Secondly, the piano tuning devices have two functions: low-speed rotation and position holding. To ensure that the surface-mounted permanent magnet synchronous motor can rotate stably over the low-speed range with strong anti-interference capacity, a double closed-loop speed-regulation-based control scheme is employed. And to ensure high position control performance, a fuzzy-adaptive triple closed-loop position-regulation-based control scheme is employed. It terms of the control schemes, it deserves to be mentioned that main contributions include, firstly, the parameters of the proportional integral controllers in the double closed-loop speed-regulation structure is tuned relying on both stability and bandwidth analyses. Then, a fuzzy-adaptive proportional integral controller is specially-designed for the triple closed-loop position-regulation to adapt to the piano tuning applications. Simulation is conducted on a 20 rpm three-phase permanent magnet synchronous motor servo drive-based piano tuning system to validate the proposed piano tuning method and to verify the proposed control techniques.

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“…It is also an important embodiment of highspeed and high-precision filling operation. At present, studies on filling multimachine collaborative control technologies usually focus on synchronous control of multimotor systems [1,2]. In the multimotor synchronous control, the synchronous topology and control algorithm are two aspects worthy of attention.…”

Section: Introductionmentioning

confidence: 99%

Collaborative Control of Multimotor Systems for Fixed‐Time Optimisation Based on Virtual Main‐Axis Speed Compensation Structure

Zhang

Ming-jie

et al. 2021

Complexity

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In response to the high-speed and high-precision collaborative control requirements of the multimotor system for filling, a new type of virtual master-axis control structure is proposed and a multimotor fixed-time optimized collaborative control algorithm is designed. Firstly, coupling relationship between virtual and slave motors is effectively established by designing a velocity compensation module for the virtual motor. Secondly, the sliding mode observer (SMO) is used to reconstruct the composite disturbance composed of motor parameter perturbation and load disturbance. Finally, the variable gain terminal sliding mode controller (SMC) is designed to ensure that each slave motor can track the given value within a fixed time. The fast convergence of the system can be proved by the fixed-time convergence theorem and Lyapunov’s stability theorem. The simulation results show that, compared with the traditional virtual main-axis control strategy, the proposed method is more effective for the tracking control of each slave motor in the initial stage.

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A Survey of Fuzzy Algorithms Used in Multi-Motor Systems Control

Cited by 35 publications

References 38 publications

Stability Analysis of Systems with Fuzzy PI Controllers Applied to Electric Drives

Stability Analysis of Systems with Fuzzy PI Controllers Applied to Electric Drives

Intelligent Permanent Magnet Motor-Based Servo Drive System Used for Automated Tuning of Piano

Collaborative Control of Multimotor Systems for Fixed‐Time Optimisation Based on Virtual Main‐Axis Speed Compensation Structure

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