γ-passive system and its phase property and synthesis

Sakamoto, Noboru; Suzuki, Masayuki

doi:10.1109/9.506239

Cited by 35 publications

(18 citation statements)

References 15 publications

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“…In this subsection, a notion of γ-positive realness [4] is introduced for the phase specification of G (s), since the notion of γ-positive realness enables us to solve the phase specification as well-known H ∞ control problem. One of the authors has already proposed this design strategy for robust vector control and sensorless control for induction motors [5] [6], and this paper aims to adopt this result to IPMSM sensorless drives.…”

Section: Phase Specification Using γ-Positive Realness and H ∞ Conmentioning

confidence: 99%

“…Therefore, it can be expected to realize the high performance sensorless vector control system of IPMSM drives with assistance of previous works related to SPMSM sensorless drives. Next, this paper proposes a novel design of adaptive flux observer on stator frame for robust estimation of position and for speed adaptation based on the aforementioned flux model, although this adaptive flux observer is constructed in the same manner as the literature [3], its observer gain is designed based on γ−positive real problem [4] [5]. Finally, simulation results show feasibility of the proposed strategy.…”

Section: Introductionmentioning

confidence: 97%

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Adaptive flux observer on stator frame and its design based on /spl gamma/-positive real problem for sensorless IPMSM drives

Hasegawa

Hatta

Matsui

2005

31st Annual Conference of IEEE Industrial Electronics Society, 2005. IECON 2005.

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This paper shows a new expression of IPMSMs, which can be regarded as a linear system, and proposes a novel design of the adaptive flux observer based on a linear model of IPMSMs on stator frame. According to this linear model, IPMSMs can be regarded a SPMSMs theoretically, yielding possibility to apply some techniques related to the adaptive flux observer of SPMSM for IPMSM drives without any approximation. This paper also proposes a design of the adaptive flux observer based on γ−positive real problem for IPMSM sensorless drives, which results in robust position estimation and speed adaptation. Finally, feasibility of the proposed method are shown by some simulation results.

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Section: Phase Specification Using γ-Positive Realness and H ∞ Conmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

Adaptive flux observer on stator frame and its design based on /spl gamma/-positive real problem for sensorless IPMSM drives

Hasegawa

Hatta

Matsui

2005

31st Annual Conference of IEEE Industrial Electronics Society, 2005. IECON 2005.

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“…7. Constraints of pole replacement C.2~y-Positive Realness and Hoo Control To solve directly the aforementioned design problem is difficult, but [5] has also shown that the problem can be solved as Hoo control problem by using Cayley transformation: H(s) =(G(s) -I)(G(s) + I) 1.…”

Section: B Error System Of Speed Identificationmentioning

confidence: 99%

“…i~ds Lkl= 1-(2+(a+e)T)z-+(1+(a+e)T)z-2 (wiqs Lk + Vds Lkl) (5) In this paper, parameters a, e and g are identified based on the above equation.…”

Section: Introductionmentioning

confidence: 99%

“…this subsection, a notion of -y-positive realness[5] is introduced for the phase specification of a transfer function, since the notion of -y-positive realness enables us to solve the phase specification as well known H,, control problem.C.1 Maximum Phase and -y-Positive RealnessGiven a transfer function G(s) in general, G(s) is -y-positive real if and only if there exists some y…”

mentioning

confidence: 99%

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Experimental Evaluation on Parameter Identification of Induction Motor Using Output Inter-Sampling Approach

Hasegawa

Ogawa

Matsui

2005 IEEE International Conference on Industrial Technology

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This paper evaluates parameter identification of speed sensorless vector controlled induction motor using output inter-sampling approach. It is wellknown that the rotor speed and the rotor time constant of induction motors at steady state operation cannot be simultaneously identified. In order to avoid this problem, many researches have already proposed some kinds of strategies such as high frequency signal injection to obtain the parameter knowledge from only stator quantities, which would cause the torque vibration and the degradation of efficiency. Hence, it is desirable to decrease the amplitude of the injected signal. Although M sequence(Maximum-length linear shift register sequence) signal is injected as an exogenous signal for parameter identification in this paper, the method of signal processing is discussed from the viewpoint of M sequence amplitude to achieve accurate parameter identification. To solve this problem, some literatures describe that output inter-sampling approach can result in the improvement of parameter identification accuracy. So, this motivates us to identify d-axis model of induction motors in steady state. In this paper, identification mechanism based on output inter-sampling approach is shown, and accuracy of identified parameters is experimentally evaluated.

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Dissipativity reinforcement in feedback systems and its application to expanding power systems

Urata

Inoue

2017

Intl J Robust & Nonlinear

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This paper focuses on the performance analysis and improvement of interconnected passive systems. We assume that each subsystem has a special passivity property that is characterized by 2 parameters. The parameters are also utilized for evaluating the dissipation performance as the L 2 -gain. Then, the feedback system composed of passive subsystems inherits the parameter-dependent passivity, and the parameter transition is given. In addition, it is shown that the dissipation performance of the feedback system is strictly improved as compared with that of the subsystems, which is called dissipativity reinforcement in this paper. Furthermore, we expand the feedback system to a larger-scale system via the iterative feedback connection of the passive subsystems. Then, the performance of the entire system is gradually reinforced with the increase in the number of subsystems. Subsequently, we extend the class of parameter-dependent passivity to a frequency-dependent one. Finally, dissipativity reinforcement via an iterative feedback connection is applied to a power system that involves a large number of renewable energy generators. In particular, we propose a strategy for designing the power system, such that the dissipation performance of the entire system is gradually reinforced via scale expansion, ie, with the increase in the amount of energy generators installed.

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γ-passive system and its phase property and synthesis

Cited by 35 publications

References 15 publications

Adaptive flux observer on stator frame and its design based on /spl gamma/-positive real problem for sensorless IPMSM drives

Adaptive flux observer on stator frame and its design based on /spl gamma/-positive real problem for sensorless IPMSM drives

Experimental Evaluation on Parameter Identification of Induction Motor Using Output Inter-Sampling Approach

Dissipativity reinforcement in feedback systems and its application to expanding power systems

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