Sliding Mode Control of Energy Storage Systems for Reshaping the Accelerating Power of Synchronous Generators

Tu, Ganggang; Li, Yanjun; Xiang, Ji

doi:10.1109/tpwrs.2022.3170703

Cited by 5 publications

(3 citation statements)

References 39 publications

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“…As apparent from (48), the approximations of rotor current are dependant on the stator currents and voltage measurements. As a result, if R > Q, the current control law u eq (21) is derived from the rotor current approximation (48). Figure ??…”

Section: Sliding Mode Observer Designmentioning

confidence: 99%

“…However, further improvements to the control structure are required to achieve an ideal sliding motion and deliver the desired performance. On the other hand, fractional-order and higher-order SMC approaches have successfully emerged as reliable alternatives with outstanding performance in respect of guaranteed fast finite-time convergence, alleviated chattering, higher control precision, and robust performance against external disturbances and model uncertainties [2,12,[18][19][20][21]. In the sense of converter control of DFIG-driven WTs, an adaptive fractional-order terminal SMC (FTSMC) approach was developed in [22].…”

Section: Introductionmentioning

confidence: 99%

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Observer-Based High-Order Sliding Mode Control of DFIG-Based Wind Energy Conversion Systems Subjected to Sensor Faults

Mousavi,

Bevan,

Kucukdemiral

et al. 2024

IEEE Trans. on Ind. Applicat.

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Recent advances in technology have paved the way for the increased penetration of wind energy conversion systems (WECSs) into the grid, worldwide. However, the existence of model uncertainties and intermittency of wind power can lead to malfunction of the stabilizing controllers and degrade the WECSs' power production performance. In this work, a compound control scheme comprising active fault-tolerant fractional-order nonsingular terminal sliding mode controllers (AFTSMCs) and a sliding mode observer (SMO) is developed to enhance the robustness of doubly-fed induction generator (DFIG) -based WECSs against uncertainties and maintain their desired performance. The developed AFTSMCs alleviate the chattering problem and overcome the compromise between fast response and the undesirable chattering problem. At the same time, it performs the speed trajectory tracking and rotor current regulation tasks. Moreover, under inevitable false fault detections due to unavoidable gradual performance degradations in the current sensors, a tolerance boundary is circumscribed for actual faults occurrence, allowing the developed robust SMO to estimate and reconstruct the rotor current during sensor faults with a high level of reliability. Evaluations of comparative performance are provided and validate the cooperative fault-tolerant method's superior control performance over other advanced approaches.

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Section: Sliding Mode Observer Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Observer-Based High-Order Sliding Mode Control of DFIG-Based Wind Energy Conversion Systems Subjected to Sensor Faults

Mousavi,

Bevan,

Kucukdemiral

et al. 2024

IEEE Trans. on Ind. Applicat.

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“…Te sliding mode observer-based fnite time control scheme is a method for controlling the frequency regulation and economic dispatch in power grids. It uses a sliding mode observer to estimate the states of the system, such as the generator speeds and power outputs, and then applies a fnite time control scheme to adjust the control signals in order to regulate the frequency and optimize the economic dispatch [22,23]. Tis method is efective in handling uncertainties and disturbances in the power grid, as the sliding mode observer is able to adapt to changing conditions and provide accurate state estimates.…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network-Based Experimental Investigations for Sliding Mode Control of an Induction Motor in Power Steering Applications

Parimalasundar,

Senthilkumar,

Kumar

et al. 2023

International Journal of Intelligent Systems

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Sliding mode control (SMC) of induction motor is a new concept in the current scenario, as it seeks to improve torque control accuracy and power steering efficiency through the use of pulse width modulation schemes. Furthermore, artificial neural network-based sliding mode control is applied to a squirrel cage induction motor, which is used in the steering control of automobiles. The artificial neural network (ANN)-based SMC is more popular due to its robustness and good stability in external parameter variation. Additionally, an SMC and an ANN-based SMC are employed to compute the torque and flux, improving performance for power steering applications. The performance of the designed model is validated through MATLAB/Simulink and experimental models with different controllers under various operating conditions. The controller has been embedded into a TMS320F28335 controller, and performances have been evaluated. The performance analyses of induction motor using different controllers are performed. The transient performances of induction motor such as delay time, rise time, settling time, and steady-state error are investigated. The proposed work is analysed by using a mathematical model and implemented in a test-bench model for validation.

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Drive State Analysis Based Electric Drive Control Model for Improved Power Stabilization

Pandey,

Sasmita Dash

2024

E3S Web of Conf.

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The problem of power stabilization in electric drives has been well studied. There exist numbers of approaches around the problem which consider the input power alone and suffer to achieve higher performance in power stabilization. To handle this issue, an efficient Drive State Analysis based Electric Drive Control model (DSA-EDCM) is presented in this article. The model monitors the drive state of electric drive at each duty cycle. According to the drive state and its previous conditions like voltage consumption, voltage leak, rpm and torque required, the method performs drive state analysis. The drive state analysis algorithm computes the power required at different conditions by computing Power Support value (PSV). Based on the PSV value, the method selects specific drive according to the input voltage received. Selected drive has been triggered for the cycle to maintain power stability. The proposed model improves the performance of power stability and maximizes the utilization performance.

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Sliding Mode Control of Energy Storage Systems for Reshaping the Accelerating Power of Synchronous Generators

Cited by 5 publications

References 39 publications

Observer-Based High-Order Sliding Mode Control of DFIG-Based Wind Energy Conversion Systems Subjected to Sensor Faults

Observer-Based High-Order Sliding Mode Control of DFIG-Based Wind Energy Conversion Systems Subjected to Sensor Faults

Artificial Neural Network-Based Experimental Investigations for Sliding Mode Control of an Induction Motor in Power Steering Applications

Drive State Analysis Based Electric Drive Control Model for Improved Power Stabilization

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