Showing papers by "Kang-Zhi Liu published in 2021"

A time series model based on hybrid-kernel least-squares support vector machine for short-term wind power forecasting.

Abstract: In this paper, a time series model based on hybrid-kernel least-squares support vector machine (HKLSSVM) with three processes of decomposition, classification, and reconstruction is proposed to predict short-term wind power. Firstly, on the basis of the maximal wavelet decomposition (MWD) and fuzzy C-means algorithm, a decomposition method decomposes wind power time series and classifies the decomposition time series components into three classes according to amplitude–frequency characteristics. Then, time series models on the basis of least-squares support vector machine (LSSVM) with three different kernels are established for these three classes. Non-dominated sorting genetic algorithm II optimizes the parameters of each forecasting model. Finally, outputs of forecasting models are reconstructed to obtain the forecasting power. The proposed model is compared with the empirical-mode-decomposition least-squares support vector machine (EMD-LSSVM) model and wavelet-decomposition least-squares support vector machine (WDLSSVM) model. The results of the comparison show that proposed model performs better than these benchmark models.

A Control Method for IPMSM Based on Active Disturbance Rejection Control and Model Predictive Control

Abstract: In this paper, the speed tracking problem of the interior permanent magnet synchronous motor (IPMSM) of an electric vehicle is studied. A cascade speed control strategy based on active disturbance rejection control (ADRC) and a current control strategy based on improved duty cycle finite control set model predictive control (FCSMPC) are proposed, both of which can reduce torque ripple and current ripple as well as the computational burden. First of all, in the linearization process, some nonlinear terms are added into the control signal for voltage compensation, which can reduce the order of the prediction model. Then, the dq-axis currents are selected by maximum torque per ampere (MTPA). Six virtual vectors are employed to FCSMPC, and a novel way to calculate the duty cycle is adopted. Finally, the simulation results show the validity and superiority of the proposed method.

Position Sensorless Adaptive Positioning Servo System with Simplified Differential Calculation and High-Frequency Voltage Injection Strategy Considering Acoustic Noise Suppression

Abstract: In position sensorless positioning servo systems, the parameter mismatch between interior permanent magnet synchronous motors (IPMSMs) and a position controller and/or a position estimator due to thermal variation and aged deterioration has not been sufficiently investigated. This paper proposes a convolutional integration-based secondorder differential calculation to identify the parameters of IPMSMs for a high-performance positioning servo system in an adaptive scheme. In addition, we propose a high-frequency voltage injection strategy considering the trade-off between acoustic noise suppression and estimation performance. The effectiveness of the proposed second-order differential calculation calculation method, and the high-frequency voltage injection for the acoustic noise suppression is verified experimentally.

Nonlinear decentralized load frequency control of multi‐machine power systems with exponential stability and low L2 gain against load disturbance

Abstract: This paper proposes a novel nonlinear decentralized control method for a class of multi‐machine power systems The aim is to construct a suitable decentralized feedback control law so as t

Stability and robust performance analysis of grid-connected inverter with high-order filter: Resonances beyond the Nyquist frequency

Abstract: Filters are inevitable for grid-connected inverters to attenuate the current harmonics caused by the pulse width modulation which is usually used in power conversion systems. High-order filters have attracted much attention because they attenuate the current harmonics effectively. Nevertheless, the high-order filters have some resonances which cause instability of the system. In addition, the resonance frequencies shift to high as the inductors and capacitors are smaller. It implies that the resonance frequencies may be beyond the Nyquist frequency in downsizing the filter. This complicates the stability and performance analyses of the system. This paper investigates rigorous input–output stability and analyses a robust performance based on the sampled-data control theory regardless of whether the resonance frequencies are beyond the Nyquist frequency or not. Our analysis contributes to downsizing the filter synthesis while the stability and the robustness are guaranteed even if the resonance frequencies are beyond the Nyquist frequency. The effectiveness of the proposed method is verified through simulations and experiments.

A Phase-Shaping Approach to the Control of Parametric Systems and Its Application

Abstract: The robust performance design of parametric systems is a long-standing unsolved problem, even though its analysis has seen significant success. Most existing design methods usually treat the parameter uncertainty as other types, such as norm-bounded uncertainty, and apply the corresponding approach. However, such treatment inevitably broadens the range of uncertainty and brings about design conservatism consequentially. To overcome such difficulty and establish a less conservative performance design method for parametric systems, this article looks back at the passivity theory and put forward a phase-shaping approach. This approach is composed of a generalized Popov transformation and a phase-shaping method for the nominal system. The key idea is to transform an uncertain but positive parameter into a positive real function while shaping the phase of the nominal system via a meta-heuristic method. This design freedom of phase shaping makes it possible to achieve a higher performance. Furthermore, this method is applied to the control design of drivetrain system: a test bed for automobile drivetrains. Its superiority is validated experimentally on an industrial setup.

Identification of Mode Shapes Based on Ambient Signals and the IA-VMD Method

Abstract: The paper presents a multiaspect analysis of multivalues and the broadband nature of system oscillation. By analyzing the ambient signal caused by random small disturbances during the normal operation of interconnected power grids, many system operation characteristics can be obtained. The traditional signal processing method cannot extract the information from ambient signals effectively. Aiming at the problem of broadband oscillation mode superposition and the difficulty of extracting information from ambient signals, an iterative adaptive variational mode decomposition (IA-VMD) method is proposed based on frequency domain analysis and signal energy. Additionally, the IA-VMD method, combined with a bandpass filter and the Prony algorithm, is used to realize the modal identification of broadband oscillation and ambient signals. Simulation experiments show that the IA-VMD method has good adaptability, antinoise characteristics, and a certain significant engineering application value as well.

Active Disturbance Rejection in Repetitive Control Systems

Abstract: As a high-precision control method for periodic signals, repetitive control has been widely investigated from both theoretical and practical sides. Since a repetitive control system contains two completely different actions: continuous control within each repetition period and discrete learning between periods, exploring the best combination of these two actions may provide us with a potential to achieve higher levels of performance. For this reason, we devised a two-dimensional repetitive control method that features preferential adjustment of control and learning actions. On the other hand, there are aperiodic disturbances in a repetitive control system. It is a challenge to reject such kinds of disturbances. To solve this problem, the equivalent-input-disturbance approach is integrated into a two-dimensional repetitive control system to improve disturbance-rejection performance. This section explains the concepts of two-dimensional repetitive control and an equivalent input disturbance and then shows how these two concepts are combined to construct a high-precision control system.