Characteristic Model Based All-Coefficient Adaptive Control on Flexible Rotor Supported by Active Magnetic Bearings

Long, Di

doi:10.18130/v3z07n

Cited by 3 publications

(4 citation statements)

References 14 publications

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“…Rather than dropping information as in the reducedorder modelling, it compresses all the information of the highorder model into several characteristic coefficients. Among the many applications, the highlight is that this methodology has been applied to successful rendezvous and docking of Shenzhou-8 spacecraft [9] as well as the control of active magnetic bearings suspending a flexible rotor in Virgina Tech [10], [11].…”

Section: Introductionmentioning

confidence: 99%

Characteristic modelling of complex networks

Chen

Sun

2016

2016 IEEE International Conference on Industrial Technology (ICIT)

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This paper proposes a data-based characteristic model of complex networks that is suitable for control design and analysis. A compression method called characteristic modelling is used to reduce the complexity of dynamic networks and the model with topology-structure preservation is proposed to describe the networks in a concise and explicit way. Based on the controllability and observability of complex networks, the minimal dimensional characteristic model is constructed for control design, which captures the major information of the networks. This modelling method also has the advantage of modelling changeable networks and finding the optimal driver nodes to control the networks. The application to complex networks show the effectiveness and easy implement of the characteristic modelling method.

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Section: Introductionmentioning

confidence: 99%

Characteristic modelling of complex networks

Chen

Sun

2016

2016 IEEE International Conference on Industrial Technology (ICIT)

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“…In recent years, its potential in hypersonic vehicle control was revealed during both the cruising phase [7,12] and the climbing phase [13]. Besides, this method has also been successfully applied to the control of active magnetic bearings suspending a exible rotor in Virginia Tech, see [14].…”

Section: Introductionmentioning

confidence: 99%

Robustness of the characteristic model-based golden-section adaptive control

Huang¹

2015

2015 34th Chinese Control Conference (CCC)

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The characteristic model-based golden-section adaptive control law (CM-GSAC) has been developed for over 20 years in China with a broad range of applications in various elds. This paper discusses the optimization of the control coef cients l 1 and l 2 such that the closed-loop system can tolerate the largest parameter estimation error. The Vinnicombe distance is introduced as a metric to evaluate the distance between the true CM and the estimated CM. According to the simulation results, system with CM-GSAC shows better tracking performance than that of the well known model-reference adaptive control and the multiple model adaptive control.

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“…Over the past 20 years, this control scheme has already been applied to more than 400 systems belonging to 10 kinds of engineering plants in the fields of astronautics (such as in the successful rendezvous and docking of Shenzhou-8 spacecraft [9], and the Fourier transform spectrometer platform [10]) and industry [2,11] in China. Besides, this method has also been successfully applied to the control of active magnetic bearings suspending a flexible rotor in Virginia Tech; see [14]. Besides, this method has also been successfully applied to the control of active magnetic bearings suspending a flexible rotor in Virginia Tech; see [14].…”

Section: Introductionmentioning

confidence: 99%

“…Second, efforts are made to improve the robustness in the presence of parameter estimation errors, which provide another choice when designing the adaptive controller. Besides, this method has also been successfully applied to the control of active magnetic bearings suspending a flexible rotor in Virginia Tech; see [14].However, like most of the adaptive control methods, some of the generic problems are also inherited in the CM-GSAC, such as the suddenly unstable closed loops and the unexpected large parameter changes. In order to relax the constraints on the parameter bounds of the CM, the GSAC is further extended to multiple CMs, which shows more satisfying tracking performance than that of the traditional multiple model adaptive control method.…”

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confidence: 99%

Multiple characteristic model‐based golden‐section adaptive control: Stability and optimization

Huang

2014

Adaptive Control & Signal

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The characteristic model-based golden-section adaptive control (CM-GSAC) law has been developed for over 20 years in China with a broad range of applications in various fields. However, quite a few theoretical problems remain open despite its satisfying performance in practice. This paper revisits the stability of the CM-GSAC from its very beginning and explores the underlying implications of the so-called golden-section parameter l 2 0:618. The closed-loop system, which consists of the CM and the GSAC, is a discrete time-varying system, and its stability is discussed from three perspectives. First, attentions have been paid to select the optimal controller coefficients such that the closed-loop system exhibits the best transient performance in the worst case. Second, efforts are made to improve the robustness in the presence of parameter estimation errors, which provide another choice when designing the adaptive controller. Finally, by measuring the slowly time-varying nature in an explicit inequality form, a bridge is built between the instantaneous stability and the time-varying stability. In order to relax the constraints on the parameter bounds of the CM, the GSAC is further extended to multiple CMs, which shows more satisfying tracking performance than that of the traditional multiple model adaptive control method. 878H. HUANG INTRODUCTIONAs being mentioned in [1], 'It is always better to use an accurate model than not to do so: if there is time delay present and it is neglected, or if there are high frequency dynamics present and they are neglected, an algorithm is more likely to fall over'. However, in practical applications such as the attitude control of hypersonic vehicles that are characterized by strongly coupled multiple states, nonlinearity, high order, and, most importantly, the lack of ground test facilities, it would be rather complicated to develop controllers based on the accurate dynamical model that is highly nonlinear with various uncertainties. Meanwhile, the dynamic performance during controller design is usually unknown when dealing with the nonlinear dynamics directly. A common way is to use the linearization technique at several preselected operation points, for example, the trim conditions of hypersonic vehicles, so as to develop linear controllers. This would be time consuming because of a tremendous amount of points if the vehicle maneuvers frequently and flies in a rapidly changing environment. Meanwhile, controller design based on the linearized model generally lacks adaptability and flexibility. The characteristic model (CM)-based adaptive control thus appears so as to build a bridge between the model complexity and the adaptability.The CM was proposed by Hongxin Wu in the 1990s and has further been developed for more than 20 years [2,3]. The essence of the CM is to use a low-order discrete time-varying system to approach a high-order nonlinear/linear system based on the main features of the plant and the control demands. Rather than dropping information as in the reduced-order m...

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Characteristic Model Based All-Coefficient Adaptive Control on Flexible Rotor Supported by Active Magnetic Bearings

Cited by 3 publications

References 14 publications

Characteristic modelling of complex networks

Characteristic modelling of complex networks

Robustness of the characteristic model-based golden-section adaptive control

Multiple characteristic model‐based golden‐section adaptive control: Stability and optimization

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