Computer Controlled Pneumatic Servo Drives

Weston, Richard; Moore, Philip; Thatcher, T. W.; Morgan, Gareth J.

doi:10.1243/pime_proc_1984_198_079_02

Cited by 16 publications

(7 citation statements)

References 6 publications

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“…If choked flow occurs at the entry port, equation (5) can be simplified, leading to the pressure relationship This ratio consists of only ratio terms relating to asymmetry, discharge coefficients and spool displacements.…”

Section: 2mentioning

confidence: 99%

Steady State Analysis of Pneumatic Servo Drives

Weston

1990

Proceedings of the Institution of Mechanical Engineers, Part C:

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This paper introduces new approaches and design models aimed at determining the steady state behaviour of pneumatic servo drives. Relationships characterizing actuator velocity and chamber pressure with respect to valve displacement are established. Certain pmameter ratios are defined and a novel analytical solution is offered, which may provide the basis of a better and more useful design methodology than conventional graphical methods. The observations and analysis are applicable to both linear (symmetric and asymmetric) and rotary drives controlled by either a singlefive-port servo valve or two independent three-port servo valves.

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Section: 2mentioning

confidence: 99%

Steady State Analysis of Pneumatic Servo Drives

Weston

1990

Proceedings of the Institution of Mechanical Engineers, Part C:

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“…In phase 3 a conventional control algorithm is applied, which may include proportional error control with minor-loop compensation and involve position loop gain scheduling. 3 The first and second control phases can be considered to be "front-end" control phases. 5 Learning loops (e.g.…”

Section: Reducing Positioning Timementioning

confidence: 99%

A new generation of pneumatic servos for industrial robots

Weston

1989

Robotica

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This paper reports on a continuation of research activities at the Loughborough University of Technology (LUT) which are aimed at evolving second generation pneumatic drives and provides an introduction to various aspects which must be considered in the design and use of industrial pneumatic servo-driven robots. The paper illustrates how a new generation of fast and accurate pneumatic servo drives, demonstrating excellent performance/cost characteristics, will become available and will rival electric and hydraulic counterparts in many areas of industrial control.

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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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Computer Controlled Pneumatic Servo Drives

Cited by 16 publications

References 6 publications

Steady State Analysis of Pneumatic Servo Drives

Steady State Analysis of Pneumatic Servo Drives

A new generation of pneumatic servos for industrial robots

Online Identification and Artificial Intelligence Control of a Servo Pneumatic System

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