Identification and position control of a servo pneumatic cylinder

Shih, Ming‐Chang; Tseng, Shy-I

doi:10.1016/0967-0661(95)00127-g

Cited by 45 publications

(15 citation statements)

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“…Their results showed that an RLS algorithm based on ARMA models provides a reasonably accurate transfer function of the systems under study. Assuming most parameters in pneumatic servo system do not change during operation, Shih and Tseng [14] performed the identification offline and adjusted servo-control before the operation accordingly. Furthermore, they investigated the impact of different parameters (sampling time, order model, different supply pressures, etc.)…”

Section: Robuste Identifikation Von Pneumatischen Servo-aktuatoren Inmentioning

confidence: 99%

Robust identification of pneumatic servo actuators in the real situations

Filipović

Nedić

Stojanović

2011

Forsch Ingenieurwes

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Intensive research in the field of mathematical modelling of the pneumatic cylinder has shown that its mathematical model is nonlinear and that a lot of important details cannot be included in the model. Selection of the model and the identification method have been conditioned by the following facts:(a) The nonlinear model of the system can be approximated by a linear model with time-variant parameters. (b) There is the influence of the combination of heat coefficient, unknown discharge coefficient and change of temperature on the pneumatic cylinder model. Therefore it is assumed that the parameters of the pneumatic cylinder are random (stochastic parameters). (c) In practical conditions, observations have a non-Gaussian distribution.Due to the abovementioned reasons, it is assumed that the pneumatic cylinder model is a linear stochastic model with variable parameters. The Masreliez-Martin filter (robust Kalman filter) was used for identification of parameters of the model. For the purpose of increasing the practical value of the filter, the following two heuristic modifications were performed:(1) It was adopted that T (k) = 1 holds for the scalar transformation of residuals. (2) Fisher information was approximated by a derivative of the Huber's function.The proposed modifications were confirmed through intensive simulations. In order to provide persistent excitation, V. Filipovic · N. Nedic · V. Stojanovic ( ) the autocovariance function "1/f " of the signal was used.The behaviour of the new approach to identification of the pneumatic cylinder is illustrated by simulations. Robuste Identifikation von pneumatischen Servo-Aktuatoren in der realen SituationenZusammenfassung Intensive Forschung auf dem Gebiet der mathematischen Modellierung des pneumatischen Zylinders hat gezeigt, dass sein mathematisches Modell nichtlinear ist und dass viele wichtige Details nicht in das Modell einbezogen werden können. Die Auswahl des Modells und die Art der Identifikation werden durch folgende Tatsachen bedingt: (a) Das nichtlineare Modell des Systems kann durch ein lineares Modell mit zeitvarianten Parametern angenähert werden. (b) Es besteht ein Einfluss der Kombination von Wärme-durchgangs-Koeffizient, unbekanntem Durchflusskoeffizienten und Änderungen der Temperatur auf das pneumatischen Zylinder-Modell. Es wird daher angenommen, dass die Parameter des pneumatischen Zylinders zufälligen Charakters sind. (c) Unter praktischen Bedingungen haben die Beobachtungsergebnisse eine nicht-Gaußsche Verteilung. Aufgrund der vorgenannten Gründe wird davon ausgegangen, dass das Pneumatikzylinder Modell ein lineares, stochastisches Modell mit variablen Parametern sein muss. Der Masreliez-Martin-Filter (robust Kalman-Filter) wurde für die Identifizierung von Parametern des Modells verwendet. Zur Erhöhung des praktischen Werts des Filters, wurden die beiden folgenden heuristischen Modifikationen durchgeführt: 184 Forsch Ingenieurwes (2011) 75:183-196 (1) Es wird angenommen, dass T (k) = 1 für das skalare Transformation der Residuen hält. (2...

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Section: Robuste Identifikation Von Pneumatischen Servo-aktuatoren Inmentioning

confidence: 99%

Robust identification of pneumatic servo actuators in the real situations

Filipović

Nedić

Stojanović

2011

Forsch Ingenieurwes

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“…Because of these problems, the system identification is an alternative approach, which ensures obtaining the mathematical models of servo drives based on input/output measurements of drives. For a system description, linear models with constant parameters are used [8]. In the mentioned reference, the system was modeled as an autoregressive with exogenous input model.…”

Section: Introductionmentioning

confidence: 99%

Identification of time‐varying OE models in presence of non‐Gaussian noise: Application to pneumatic servo drives

Stojanović

Nedić

2016

Intl J Robust & Nonlinear

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Intensive research in the field of mathematical modeling of pneumatic servo drives has shown that their mathematical models are nonlinear in which many important details cannot be included in the model. Owing the influence of the combination of heat coefficient, unknown discharge coefficient, and change of temperature, it was supposed that parameters of the pneumatic cylinder are random (stochastic parameters). On the other side, it has been well known that the nonlinear model can be approximated by a linear model with time-varying parameters. Due to the aforementioned reasons, it can be assumed that the pneumatic cylinder model is a linear stochastic model with variable parameters. In practical conditions, in measurements, there are rare, inconsistent observations with the largest part of population of observations (outliers). Therefore, synthesis of robust algorithms is of primary interest. In this paper, the robust recursive algorithm for output error models with time-varying parameters is proposed. The convergence property of the proposed robust algorithm is analyzed using the methodology of an associated ordinary differential equation system. Because ad hoc selection of model orders leads to overparameterization or parsimony problem, the robust Akaike's criterion is proposed to overcome these problems. By determining the least favorable probability density for a given class of probability distribution represents a base for design of the robust version of Akaike's criterion. The behavior of the proposed robust identification algorithm is considered through intensive simulations that demonstrate the superiority of the robust algorithm in relation to the linear algorithms (derived under an assumption that the stochastic disturbance has a Gaussian distribution). The good practical values of the proposed robust algorithm to identification of the pneumatic cylinder are illustrated by experimental results.Recent research has shown that the nonlinear model of the system can be approximated, with great accuracy, by a time-varying linear system [10]. On the other hand, due to difficult quantification of phenomena described in (ii), one way to present them is the introduction of stochastic processes. Taking into account the previous considerations, it is assumed that the pneumatic cylinder is described by a linear stochastic output error (OE) model with variable parameters. It should be noted that the OE methods are maximum likelihood estimators as well as the equation error methods. The equation error method is used when the output contains both measurement noise and the disturbance (process noise), while the OE method is used when the output contains only the measurement noise [11].Description of stochastic disturbances by Gaussian process is not justified. Namely, in the population of observations, there are rare, large observations that are inconsistent with the majority of the population. Sometimes, complex phenomena are occurred in the system because of atypical changes of the process behavior, output noise, or s...

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“…Modelos caixa branca de robôs manipuladores são não lineares [5,10], enquanto que a identificação caixa preta, gera modelos lineares e não lineares [1], que podem ser usados para projeto e implementação de controladores adaptativos. Os modelos caixa branca, exigem elevado esforço computacional [8,11]. Na utilização de modelos caixa preta, suas estruturas são definidas a priori, e com isto, a escolha de modelos de primeira ou segunda ordem, que representam bem os sistemas reais, e que requerem baixo esforço computacional, 1 riul@ct.ufpb.br 2…”

Section: Introductionunclassified

Modelamento não Linear de Dois Elos de um Robô Eletromecânico de Cinco Graus de Liberdade

Riul¹,

Montenegro²

2015

Proceeding Series of the Brazilian Society of Computational and Applied Mathematics

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Resumo. O objetivo do presente trabalho é o modelamento não linear de dois elos de um robô manipulador eletromecânico de cinco graus de liberdade (5 GDL). O robô manipulador é composto por cinco juntas rotacionais, por quatro elos e por uma garra. Cinco motores de corrente contínua são utilizados para o acionamento do robô e a transmissão do movimento dos motores para as juntas é realizada através de trens de engrenagens. As medidas das posições angulares das juntas são realizadas por potenciômetros. Modelos de robôs manipuladores são obtidos usando equações de Newton -Euler ou de Lagrange; e são acoplados e não lineares. Neste trabalho, um modelo não linear é obtido, usando a série de Volterra em tempo discreto; e os parâmetros do robô manipulador são identificados, através do algoritmo Least Mean Squares (LMS), com base nas excitações e respostas dos elos do robô. Finalizando, são apresentados resultados obtidos através do modelo gerado. Palavras-chave. Sistema não linear, Robótica, Identificação IntroduçãoO presente trabalho tem como objetivo o modelamento não linear de dois elos de um robô manipulador eletromecânico de cinco graus de liberdade (5 GDL). Os elos 1 e 2 a serem controlados são mostrados na Fig. 1. O modelo matemático de um sistema pode ser obtido através de leis físicas, conhecido como modelo caixa branca ou por técnica de identificação paramétrica, conhecida como modelo caixa preta, que depende de dados reais do sistema. Modelos caixa branca de robôs manipuladores são não lineares [5,10], enquanto que a identificação caixa preta, gera modelos lineares e não lineares [1], que podem ser usados para projeto e implementação de controladores adaptativos. Os modelos caixa branca, exigem elevado esforço computacional [8,11]. Na utilização de modelos caixa preta, suas estruturas são definidas a priori, e com isto, a escolha de modelos de primeira ou segunda ordem, que representam bem os sistemas reais, e que requerem baixo esforço computacional, 1 riul@ct.ufpb.br 2

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Identification and position control of a servo pneumatic cylinder

Cited by 45 publications

References 1 publication

Robust identification of pneumatic servo actuators in the real situations

Robust identification of pneumatic servo actuators in the real situations

Identification of time‐varying OE models in presence of non‐Gaussian noise: Application to pneumatic servo drives

Modelamento não Linear de Dois Elos de um Robô Eletromecânico de Cinco Graus de Liberdade

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