Control strategies for pneumatic servo drives

Moore, Philip; Ssenkungo, F. W.; Weston, Richard; Thatcher, T. W.; Harrison, Robert

doi:10.1080/00207548608919809

Cited by 13 publications

(2 citation statements)

References 4 publications

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“…At Loughborough University of Technology (LUT) the Modular Systems research group have (since 1981) received SERC funding to investigate modular machine architectures. Originally this work centred on deriving single-degree-of-freedom manipulator modules (or machine primitives) and associated motion controllers (Weston et al 1985, Moore et al 1986). This led in 1984(through an industrial collaborator Martonair UK Ltd) to the commercial release of a family of servo-controlled pneumatically actuated machine modules (the first of their type worldwide, Morgan et al 1986).…”

Section: Modular Distributed Manipulator Systemsmentioning

confidence: 99%

Universal machine control system primitives for modular distributed manipulator systems

Weston

Harrison

Booth

et al. 1989

International Journal of Production Research

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The market for programmable machines is still in its infancy, awaiting major changes in machine architectures and functionality. This paper anticipates the evolution of modular distributed manipulator systems and outlines their potential roleas genericreconfigurable manufacturingmachines. The necessary functionality of the control and mechanical primitive elementsof such systems will be described with reference to major SERe-funded research aimed at evolving the primitivesof universal machine control systems.

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Section: Modular Distributed Manipulator Systemsmentioning

confidence: 99%

Universal machine control system primitives for modular distributed manipulator systems

Weston

Harrison

Booth

et al. 1989

International Journal of Production Research

Self Cite

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“…A recently, (Sobczyk et al, 2012) [12] proposed linearized feedback with friction compensation conducted on a pneumatic positioning system. The most common controller in servo pneumatic positioning system is the state feedback controller, called PVA controller and used three feedback signals; position, velocity, and acceleration [13][14][15][16][17]. However, the acceleration feedback signal is difficult to measure and involved much noise when obtains from the derivative of velocity or the second derivative of position.…”

Section: Introductionmentioning

confidence: 99%

Online Identification and Artificial Intelligence Control of a Servo Pneumatic System

Mohamed

Okasha

Abdrabbo³

2018

Scientific Journal of October 6 University

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The aim of this paper is to identify and control a pneumatic servo drive in real-time environment. Obtaining the system's dynamic model accurately can be difficult once the pneumatic servo-system has been assembled since its highly nonlinear in nature, as a result, some difficulties in servo-pneumatic system modeling and control. In order to, overcome the complexity associated with the system nonlinearity, auto-regressive movingaverage (ARMA) model is employed to identify the system's dynamic model in real-time environment. The advantages of this approach include high accuracy in the estimated model, low cost, and time reduction in controller design. The results acquired from the online experimental measured data are used to predict a discrete transfer function of the pneumatic servo system. The fourth-order model with one-step prediction shows the best performance compared with different order estimated model with varying sizes of step. Due to the highly nonlinearity of the system under study, two sophisticated controllers, PID-type fuzzy logic controller and Fractional order PID controller were chosen and designedusingthree optimization algorithms, namely particle swarm optimization (PSO), genetic algorithm (GA), grey wolf optimization (GWO).

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Developing intelligent actuator systems: experimenting with Bitbus and the 8096

Virvalo

Puusaari

1989

Microprocessors and Microsystems

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Control strategies for pneumatic servo drives

Cited by 13 publications

References 4 publications

Universal machine control system primitives for modular distributed manipulator systems

Universal machine control system primitives for modular distributed manipulator systems

Online Identification and Artificial Intelligence Control of a Servo Pneumatic System

Developing intelligent actuator systems: experimenting with Bitbus and the 8096

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