A current observer based on an internal model control is derived to estimate uncertainties in a permanent magnet synchronous motor (PMSM) caused by parameter variations and disturbances. Specially, a state-spacemodel...
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A current observer based on an internal model control is derived to estimate uncertainties in a permanent magnet synchronous motor (PMSM) caused by parameter variations and disturbances. Specially, a state-spacemodel for current loop is set up as the internal model, and an estimation law is derived by robust Lyapunov functions for the augmented state-space model to improve the observer dynamics and stability index. Superior control performance on suppressing current ripple for PMSM is verified in experiments.
With regards to the characteristics of uncertain long delay of networked control system (NCS), the stochastic time-delay system can be transformed to a deterministic delay system by placing proper quantities of buffer...
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ISBN:
(纸本)9781457720727
With regards to the characteristics of uncertain long delay of networked control system (NCS), the stochastic time-delay system can be transformed to a deterministic delay system by placing proper quantities of buffers at the nodes of the double-end networked control systems. An observer-based control design subject to fixed time delay is proposed to construct the augmented state-space model. Based on the Lyapunov function and linear matrix inequality (LMI) theorem, sufficient and necessary conditions for stability of such systems using static state feedback are given. Simulation result proves its effectiveness.
作者：
Zhou, BinquanWang, ZhuoZhai, YueyangYuan, HengBeihang Univ
Beijing Adv Innovat Ctr Big Data Based Precis Med Minist Ind & Informat Technol Quantum Sensing Tec Sch Instrumentat Sci & Optoelect EngnKey Lab Beijing 100191 Peoples R China
We propose a couple of data-driven analysis methods for the state controllability and state observability of a class of discrete linear time-invariant (LTI) systems with delays, which have unknown parameter matrices. ...
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ISBN:
(纸本)9781538626184
We propose a couple of data-driven analysis methods for the state controllability and state observability of a class of discrete linear time-invariant (LTI) systems with delays, which have unknown parameter matrices. To analyze the state controllability and the state observability, these data-driven methods first transform the system model into an augmented state-space model, and then use the state/output data that were previously measured, to directly build the controllability/observability matrices of this augmentedmodel. Our methods have two main advantages over the traditional model-based characteristics analysis approaches. First, the unknown parameter matrices are not necessary to be identified for verifying the state controllability/observability of the system, but these characteristics can be directly verified according to the measured data, thus our methods have less workload. Second, their computational complexity is lower for the construction of the state controllability/observability matrices.
作者：
Wang, ZhuoYuan, QiBeihang Univ
Sch Res Inst Frontier Sci Beijing 100191 Peoples R China Beihang Univ
Key Lab Minist Ind & Informat Technol Quantum Sensing Tec Beijing 100191 Peoples R China Beihang Univ
Beijing Adv Innovat Ctr Big Data Based Precis Med Beijing 100191 Peoples R China Beijing Acad Quantum Informat Sci
Beijing 100193 Peoples R China Beihang Univ
Sch Instrumentat & Optoelect Engn Beijing 100191 Peoples R China
The state controllability of time-delay systems is important for a wide range of scientific and industrial processes. However, few researches up to now have been carried out for extensive studies on this problem. This...
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ISBN:
(纸本)9781728159225
The state controllability of time-delay systems is important for a wide range of scientific and industrial processes. However, few researches up to now have been carried out for extensive studies on this problem. This paper develops a method for analyzing the state controllability of linear discrete time-varying time-delay systems. By establishing an augmented state-space model of the original system, only a few parameters are needed to complete the determination of the state controllability, which greatly reduces the amount of calculation. Then, a specific example is presented to show the effectiveness of the proposed analysis method.
Wind and wave loads are critical to monopile-supported offshore wind turbines (OWTs) in determining whether OWTs are in safe conditions to generate electricity. However, these random and complex loads vary with time a...
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Wind and wave loads are critical to monopile-supported offshore wind turbines (OWTs) in determining whether OWTs are in safe conditions to generate electricity. However, these random and complex loads vary with time and location, and are difficult to measure directly. Theoretically, the loads can be identified based on structural responses. Nevertheless, it is challenging due to the complexity of external loads and the existence of harmonic loads generated by rotor rotation. This study proposes a new load identification framework using a limited amount of monitoring data to estimate the equivalent wind and wave loads of OWTs simultaneously. Both loads are modeled as Gaussian processes with exponential covariance function and incorporated into the augmented state-space model. Kalman filter is employed to identify the equivalent loads. The effectiveness and accuracy of the proposed method were validated based on a numerical OWT model and a scaled OWT test model. The results demonstrate that the framework can successfully identify equivalent wind and wave loads of OWTs in both parked and operating conditions. The probability distribution of identified load data is consistent with actual load data, with an error of less than 9.1 %. The proposed framework can find vast applications in operational management for OWTs.
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