Barrier Lyapunov function-based adaptive fuzzy control for induction motors with iron losses and full state constraints

Fu, Cheng; Yu, Jinpeng; Zhao, Lin; Yu, Haisheng; Lin, Chong; Ma, Yajie

doi:10.1016/j.neucom.2018.02.020

Cited by 31 publications

(13 citation statements)

References 36 publications

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“…By substituting (15) into (19), the approximate solution U changes exponentially with the load torque of the motor. By substituting (19) into (12), we can obtain the minimum total electrical loss:…”

Section: Influence Of Stator Voltage On the Variation Rate Of Totalmentioning

confidence: 99%

“…and full load ( N L T T  ). Assuming that the load torque fluctuates to a certain extent, the load torque curve of the motor within a certain operating cycle and the optimal voltage regulation curve were calculated using (19) and are shown in Figur 9. Equation (12) can be used to calculate the total electrical losses for 380 and 220 V. Equation 20was used to calculate the total electrical loss of the optimal voltage regulation, as shown in Figure 10.…”

Section: B Analysis Of Optimal Voltage Regulation and Energy-saving mentioning

confidence: 99%

“…The latter is vector control based on a dynamic mathematical model of the motor [15], [16]. Vector control theories and methods mainly include adaptive control [17][18][19][20], inverse dynamics control [21][22][23], fuzzy control [24], [25], back-stepping control [26], and sliding mode control [27][28][29]. However, these energy-saving methods and measures aimed at regulating the motor speed have no significant energysaving effects, and the designs of these controllers are more complex.…”

Section: Introductionmentioning

confidence: 99%

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Principle of Optimal Voltage Regulation and Energy-Saving for Induction Motor With Unknown Constant-Torque Working Condition

Zhong

Ma²,

Hao

2020

IEEE Access

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To achieve optimal voltage regulation and energy savings of an AC induction motor operating under constanttorque and variable-working-load conditions, and consider a motor's T-type and Γ-type equivalent circuit, the copper and iron losses of the stator were regarded as invariable losses that were only related to the stator voltage, and the copper losses of the rotor were regarded as variable losses that varied with the load torque. The total electrical loss formula and the optimal voltage regulation formula for the motor were deduced. The formulas revealed that the total electrical loss of the motor was affected by the stator voltage and the rotor load torque, and the optimal voltage regulation changed exponentially with the load torque of the motor. The calculation results of an engineering example showed that when s = 0.01-0.03 and the motor operated stably, the motor load torque error was not more than 1.8 Nꞏm based on the exact and approximate solutions of the slip s. The total electrical loss showed almost no calculation error when the working voltage of the motor was higher than 230 V. The optimal voltage regulation and its error increased with the increase in the motor load torque, but within the working voltage range of the motor, the optimal voltage regulation error did not exceed 6 V. The total electrical loss with the optimal voltage regulation mode and a variable load torque was less than the total electrical loss of a 380-or 220-V constant driving mode. With the increase in the load rate, the total electrical loss increased. When the motor's load did not exceed the medium load and the motor operated with optimal voltage regulation, the energy-saving effect was significant. In particular, when the motor operated without a load, the total electrical loss was almost 0. INDEX TERMS Induction motor, constant-torque working condition, equivalent circuit, total electrical loss, optimal voltage regulation, energy-saving.

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Section: Influence Of Stator Voltage On the Variation Rate Of Totalmentioning

confidence: 99%

Section: B Analysis Of Optimal Voltage Regulation and Energy-saving mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Principle of Optimal Voltage Regulation and Energy-Saving for Induction Motor With Unknown Constant-Torque Working Condition

Zhong

Ma²,

Hao

2020

IEEE Access

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“…Accordingly, state limitations are indispensable during the PMSM's controllers construct process. Fortunately, many significant achievements have been obtained in the all-state constrained nonlinear control field, such as [15,16] and from these approaches, the barrier Lyapunov functions (BLFs) are normally utilized to hold off the limitation transgressions.…”

Section: Introductionmentioning

confidence: 99%

Command Filtering and Barrier Lyapunov Function‐Based Adaptive Control for PMSMs with Core Losses and All‐State Restrictions

Wang

2021

Complexity

Self Cite

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With the troubles of core losses and all-state confined to certain limitations which are the innate traits of permanent magnet synchronous motors (PMSMs), this article develops a command filtered adaptive backstepping approach to follow the track of PMSM’s desired rotor position. To begin with, the RBF neural network technique is utilized to get close to the uncharted nonlinear terms which existed in PMSM’s mathematical model. Meanwhile, an advanced adaptive command filter control methodology is constructed to avoid the computing explosion during the process of backstepping design. Furthermore, to make sure that all the state variables are confined into certain ranges, we employed the barrier Lyapunov function (BLF) at every step of the controllers construction. In addition, an error compensating mechanism is proposed to neutralize filtering errors and only one adaptive law is required. At last, simulation results bear out the superiority of the aforementioned control scheme.

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“…Vector control theories and methods mainly include adaptive control [23][24][25], back stepping control [26], inverse dynamic control [27], passive control [28], sliding mode control [29,30], and fuzzy logic control [31,32]. Owing to the coupling terms of the state variables in the motor dynamics equations, the torque and excitation components of the motor stator current influence each other, and affect the dynamic performance of the control system.…”

Section: Introductionmentioning

confidence: 99%

Research on the Hoisting Motor Drive System’s Active Disturbance Rejection Control and Energy Consumption for a Crane

Zhong

Ma²,

Hao

et al. 2021

IEEE Access

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To allow the hoisting motor drive system of a crane to track a load torque quickly, a linearization method was used to transform a motor nominal dynamics model into two decoupled linear rotor speed and flux linkage subsystems. The method based on the theory of differential geometry was a precise feedback method. Two active disturbance rejection controllers (ADRCs) with identical structures were designed for the rotor speed and flux linkage subsystems. The extended state observer of the ADRC could estimate the unmodeled dynamics of the motor, the variation of motor parameters due to heating, and the unknown disturbances of the motor system to determine the total disturbances of the system. A closed-loop system with ADRC and an open-loop system were compared. The motor's full-load starting time was reduced by about 50%. When the motor operated smoothly at different load rates and the rated load was suddenly applied, the electromagnetic torque fluctuation range did not exceed 20 N• m. The rotor flux was always stable at the reference value. The motor speed decreased, but the amount of decrease did not exceed 7 rad/s. The closed-loop system had a significant energy-saving effect during the motor's starting process. The power saving rate was about 55%-59% if the motor started with a light load. The power saving rate could reach 71% if the motor started with a heavy load. The ADRC system could accurately estimate the unknown model of the rotor speed and flux linkage subsystems, and adapt to parameter variations of the motor stator and rotor resistance in the range of ±10%. Motor: Te, TL Electromagnetic and load torques. TN Nominal torque. ET Electromagnetic torque tracking error. np Motor's pole logarithm. Je Rotational inertia of the rotor. n Rotor speed. ω Electric angular velocity. ωr Mechanical angular velocity. α, β Static two-phase coordinate axis.

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Barrier Lyapunov function-based adaptive fuzzy control for induction motors with iron losses and full state constraints

Cited by 31 publications

References 36 publications

Principle of Optimal Voltage Regulation and Energy-Saving for Induction Motor With Unknown Constant-Torque Working Condition

Principle of Optimal Voltage Regulation and Energy-Saving for Induction Motor With Unknown Constant-Torque Working Condition

Command Filtering and Barrier Lyapunov Function‐Based Adaptive Control for PMSMs with Core Losses and All‐State Restrictions

Research on the Hoisting Motor Drive System’s Active Disturbance Rejection Control and Energy Consumption for a Crane

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