• Journal of Power Electronics
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• v.16 no.3
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• pp.1067-1075
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• 2016

This paper presents an adaptive observer-based approach to estimate voltage parameters, including frequency, amplitude, and phase angle, for single-phase power systems. In contrast to most existing estimation methods of grid voltage parameters, in this study, grid voltage is treated as a dynamic system related to an unknown grid frequency. Based on adaptive observer theory, a full-order adaptive observer is proposed to estimate voltage parameters. A Lyapunov function-based argument is employed to ensure that the proposed estimation method of voltage parameters has zero steady-state error, even when frequency varies or phase angle jumps significantly. Meanwhile, a reduced-order adaptive observer is designed as the simplified version of the proposed full-order observer. Compared with the frequency-adaptive virtual flux estimation, the proposed adaptive observers exhibit better dynamic response to track the actual grid voltage frequency, amplitude, and phase angle. Simulations and experiments have been conducted to validate the effectiveness of the proposed observers.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.4
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• pp.566-574
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• 2013

In this paper, direct power control system for three-phase PFC AC/DC converter without the source voltage sensors is proposed. The sinusoidal input current and unity effective power factor are realised based on the estimated flux in the observer. Both active and reactive power calculated using estimated flux. The estimation of flux is performed based on the reduced-order virtual flux observer using the actual currents and the command control voltage. Moreover, source voltage sensors are replaced by a estimated flux. DC output voltage has been compensated by DC output ripple voltage estimation algorithm. The active and reactive powers estimation are performed based on the estimated flux and Phase angle. The proposed algorithm is verified through simulation and experiment.

• Proceedings of the KIEE Conference
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• 2003.10b
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• pp.83-85
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• 2003

This paper presents a speed control of permanent magnet synchronous motors (PMSM) using an adaptive integral binary observer without speed and position sensors. In view of composition with a main loop regulator and an auxiliary loop regulator, the binary observer has a property of the chattering alleviation in the constant boundary layer. In order to improve the steady state performance of the binary observer, the proposed adaptive integral binary observer is formed by adding extra integral dynamics to the switching hyperplane equation. The effectiveness of the proposed system is conformed by the experimental results.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1159-1161
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• 1997

This paper presents a power system stabilizer(PSS) using the $H_{\infty}$ observer-based sliding mode controller($H_{\infty}$ observer-based SMC) for unmeasurable state variables. The effectiveness of the proposed $H_{\infty}$ observer-based SMPSS for unmeasurable state variables is shown by the simulation result.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1156-1158
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• 1997

This paper presents the proposed full-order observer-based sliding mode power system stabilizer(FOOSMPSS) for finding unmeasurable state variables(torque angle, quadratic-axis transient voltage, exciter output voltage, voltage regulator output voltage and output voltage) by measuring angular velocity. The simulation results is shown by the comparison of the FOOPSS with the proposed FOOSMPSS.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1171-1173
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• 1997

This paper presents the sliding mode observer-model following(SMO-MF) power system stabilizer(PSS) for unmeasurable plant state variables. This SMO-MF PSS can be obtained by combining the sliding mode-model following(SM-MF) including closed-loop feedback(CLF) with the linear foil-order observer(LFOO).

• Journal of Power Electronics
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• v.16 no.3
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• pp.1131-1140
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• 2016

A simple design for a sliding mode observer is proposed for EV lithium battery SOC estimation in this paper. The proposed observer does not have the limiting conditions of existing observers. Compared to the design of previous sliding mode observers, the new observer does not require a solving matrix equation and it does not need many observers for all of the state components. As a result, it is simple in terms of calculations and convenient for engineering applications. The new observer is suitable for both time-variant and time-invariant models of battery SOC estimation, and the robustness of the new observer is proved by Liapunov stability theorem. Battery tests are performed with simulated FUDS cycles. The proposed observer is used for the SOC estimation on both unchanging parameter and changing parameter models. The estimation results show that the new observer is robust and that the estimation precision can be improved base on a more accurate battery model.

• Journal of IKEEE
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• v.27 no.4
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• pp.430-438
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• 2023

The Modular Multilevel Converter (MMC) has emerged as a key component in HVDC systems due to its ability to efficiently transmit large amounts of power over long distances. In such systems, accurate estimation of the MMC capacitor voltage is of utmost importance for ensuring optimal system performance, stability, and reliability. Traditional methods for voltage estimation may face limitations in accuracy and robustness, prompting the need for innovative approaches. In this paper, we propose a novel distributed neural network observer specifically designed for MMC capacitor voltage estimation. Our observer harnesses the power of a multi-layer neural network architecture, which enables the observer to learn and adapt to the complex dynamics of the MMC system. By utilizing a distributed approach, we deploy multiple observers, each with its own set of neural network layers, to collectively estimate the capacitor voltage. This distributed configuration enhances the accuracy and robustness of the voltage estimation process. A crucial aspect of our observer's performance lies in the meticulous initialization of random weights within the neural network. This initialization process ensures that the observer starts with a solid foundation for efficient learning and accurate voltage estimation. The observer iteratively updates its weights based on the observed voltage and current values, continuously improving its estimation accuracy over time. The validity of proposed algorithm is verified by the result of estimated voltage at each observer in capacitor of MMC.

• International Journal of Ocean Engineering and Technology Speciallssue:Selected Papers
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• v.5 no.1
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• pp.46-52
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• 2002

A robust nonlinear observer, utilizing the sliding mode concept, is developed for the dynamic positioning of ships. The observer provides the estimates of linear velocities of the ship and bias from slowly varying environmental loads. It also filters out wave frequency motion to avoid wear of actuators and excessive fuel consumption. The main advantage of the proposed observer is in its robustness. Especially, the observer structure with a saturation function makes the proposed observer robust against neglected nonlinearties, disturbances and uncertainties. Since the mathematical model of DP ships is difficult to obtain and includes uncertainties and disturbances, it is very important for the observer to be robust. A nonlinear output feedback controller is derives based on the developed observer using the observer backstepping technique, and the global stability of the observer and control law is shown by Lyapunov stability theory.. A set of simulation was carried out to investigate the performance of the proposed observer for dynamic positioning of ships.

• Journal of Power System Engineering
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• v.18 no.5
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• pp.129-136
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• 2014

This paper proposes improvement on sensorless vector control performance of a permanent magnet synchronous motor (PMSM) with sliding mode observer. An adaptive observer gain and second order cascade low-pass filter (LPF) were used to improve the estimation accuracy of the rotor position and speed. The adaptive observer gain was applied to suppress the chattering intensity and obtained by using the Lyapunov's stability criterion. The second order cascade LPF was designed for the system to escalate the filtering performance of the back-emf estimation. Furthermore, genetic algorithm was used to optimize the system PI controller's performance. Simulation results showed the effectiveness of the suggested improvement strategy. Moreover, the strategy was useful for the sensorless vector control of PMSM to operate on the low-speed area.