Fuzzy parameter tuning in the stabilization of an RFPT-based adaptive control for an underactuated system

Várkonyi, Teréz A.; Tar, József K.; Rudas, Imre J.

doi:10.1109/cinti.2011.6108473

Cited by 9 publications

(4 citation statements)

References 5 publications

(4 reference statements)

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“…), can be beneficial for retrospective, as well as perspective data analyses [17]. Using traditional knowledge forms of knowledge discovery on safety, reliability and efficiency, may assist in the discovery of an experimental model of the system and enhance the system control, using resulting rules and models.…”

Section: A Background and Problem Field Descriptionmentioning

confidence: 99%

On scientific research information system

Gaspar

Madarasz

Andoga

et al. 2013

2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)

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The presented paper proposes a design of a scientific research information system (SRIS), intended for real world use according to existing requirements and processes in the Laboratory of Intelligent Control Systems of Aircraft Engines. The novelty of the proposed SRIS lies in universal and narrow scope of the system and digitalization of existing manual processes, with the addition of algorithms and methods for research efficiency evaluation. The key idea is the possibility to design own quantitative key performance indicators (KPIs) for the efficiency evaluation. It is possible to generalize the presented approach for any research environment, either for technical, financial, time related or information efficiency evaluation. In case of a complex technical systems, the SRIS can also be considered a decision support system (DSS), when using various data mining algorithms e.g.

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Section: A Background and Problem Field Descriptionmentioning

confidence: 99%

On scientific research information system

Gaspar

Madarasz

Andoga

et al. 2013

2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)

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“…The other advantage, researches showed, that the improvement achieved by this function can be increased by applying small modifcations to this function during the controlling process [14].…”

Section: Introductionmentioning

confidence: 99%

VS-type stabilization of MRAC controllers using robust fixed point transformations

Várkonyi

Tar

Rudas

et al. 2012

2012 7th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)

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Nowadays, control of dynamical systems with uncer tainties is a common problem. Many sulutions can be found in the literature, one of these methods is the family of Robust Fixed Point Transformations (RFPT) with local basin of attraction.The method is based on the idea that if someone has to use an approximate model in a control task, there is a function which, locally converging to the right solution, can reduce the disadvantages of the approximation. In this paper, authors show that though RFPT can loose its local convergensity, it can still improve a simple controller's results and this improvement makes the controller's behavior very similar to that of a sliding mode controller. The similarity includes the so called chattering effect, but a simple smoothing algorithm is also introuced to minimize the fluctuation of the control signal. I. INTRODUC TIONIn the 19th century stability of dynamical systems was a problematic subject for the scientists. It was sometimes very elaborate to determine whether a system was stable or not and only a few results were at hand to answer these questions. One of the first breakthroughs was made by Aleksandr Lyapunov in 1892. In his PhD dissertation [1] he introduced an approach, called Lyapunov's "direct" method, in which on the basis of relatively simple estimations, stability (either global or local, common, exponential, or asymptotic) could be determined without obtaining and studying the solutions of the equations of motion. (It is well known that the most of the practically occurring problems do not have analytical solutions in closed form, while the numerical solutions are normally valid only for the limited time-span of investigations and without deeper mathematical background their results cannot be extrapolated.) Lyapunov's work was translated to English approximately 75 years later, in the 20th century [2] and since that it has become the possibly most significant mathematical tool for designing stable controllers for linear and nonlinear systems (for some examples [3]-[11]).The advantage of the Sliding Mode Control (SMC) is its simplicity, characterized by robustness which makes the con troller able to handle dynamical systems with heavy uncertain conditions. In sliding mode, SMC does not just behave as a reduced order system with respect to the original system, but is insensitive to uncertainities and disturbances. On the contrary it has a main disadvantage, the so-called chattering effect, which demands the system to fluctuate so quick that it might get damaged in short time because of the stress [12].Robust Fixed Point Transformation is a method based on an idea that if someone has to use an approximate model in a control task, there is a function which, locally converging to the right solution, can reduce the disadvantages of the approximation. As included in its name, RFPT is characterized by robustness and it has the ability to handle rough approxima tions also, without increasing the performance of the controller considerably. These properties make RFPT very si...

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“…For guaranteeing the stability of the controller in certain applications tuning only one of the adaptive parameters may be necessary that can simply be realized [21]. According to simulations the suggested method was found to be useful for adaptive control of underactuated CMS [22], freeway traffic [23], etc. The simplicity of the design method was demonstrated by the use of strongly system (two coupled nonlinear springs) in [24].…”

Section: Introductionmentioning

confidence: 99%

Adaptive controllability of the brusselator model with input coupling

Tar

Rudas

Nádai

et al. 2012

2012 4th IEEE International Symposium on Logistics and Industrial Informatics

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For replacing Lyapunov's ingenious but complicated "2nd method" in designing adaptive controllers for nonlinear systems the use of "Robust Fixed Point Transformations (RFPT)" was extensively studied in the past few years mainly for "Classical Mechanical Systems (CMS)". In spite of the strongly nonlinear coupling that is typical in the Euler-Lagrange equations of motion CMS are simple in the sense that their state variables (i.e. the generalized coordinates and their time-derivatives), driving force or torque components, as well as the tracking error signals are physically well interpreted both in the positive and the negative domains. Furthermore, the time-derivatives of the control forces do not occur in the equations of motion. Therefore simple PIDtype controllers with great feedback gains as well as RFPT-based adaptive ones of smaller feedback gains but of the aptitude for introducing strong nonlinear transient fluctuations after their switching on can successfully deal with such systems. In contrast to CMS "Chemical Systems (CS)", besides their multiplication and power-type terms in the reaction equations also have further strong nonlinearities due to phenomenological restrictions. Neither negative concentrations, nor negative ingress rates of pure reagents can occur in the case of "Continuous Stirring Tank Reactors (CSTR)". Such effects were recently investigated by assuming the ingress of very concentrated reagents in the control that do not considerably dilute the other reagents in the CTRS. In this paper the far reaching consequences of this mutual diluting effect are studied. It is shown that the RFPT-based adaptive controller still can be useful but the control strategy has to take far more complicated form.

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Fuzzy parameter tuning in the stabilization of an RFPT-based adaptive control for an underactuated system

Cited by 9 publications

References 5 publications

On scientific research information system

On scientific research information system

VS-type stabilization of MRAC controllers using robust fixed point transformations

Adaptive controllability of the brusselator model with input coupling

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