Robust control of interval plants: A time domain method

Zhang, Y.M.; Kovacevic, Radovan

doi:10.1049/ip-cta:19971170

Cited by 23 publications

(12 citation statements)

References 11 publications

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“…Based on the impulse response model, adaptive interval model control [40] was used to achieve both speed and stability when the targeted range of manufacturing conditions was wide. The experiments under varied manufacturing conditions verified the effectiveness of the developed control system for weld pool surface depth during gas tungsten arc welding, thus verified the effectiveness of its fundamental elements including the proposed durable non-transferred plasma charge sensor, the proposed online reference surface tracking, and the proposed adaptive interval model control method [33].…”

Section: Gtaw Processmentioning

confidence: 99%

Three-dimensional vision applications in GTAW process modeling and control

Wang

2015

Int J Adv Manuf Technol

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In gas tungsten arc welding (GTAW), the weld pool is the major source of information that can be used to assure the production of the desired weld penetration-the most critical factor determining the weld integrity. To meet this challenge, various sensing technologies, modeling methods, and control strategies have been studied, and artificial intelligence technologies were applied to improve system intelligence. The GTAW process analysis is given first. Then, a short introduction on weld pool sensing technologies is presented, where three-dimensional (3D) vision sensing is a very active orientation. Furthermore, weld pool description model and characteristic parameter model are also discussed, where intelligent algorithms were used generally. Besides, dynamic modeling and penetration control strategies, especially intelligent control strategies are presented. At last, the discussion about development of the GTAW penetration control product is analyzed briefly.

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Section: Gtaw Processmentioning

confidence: 99%

Three-dimensional vision applications in GTAW process modeling and control

Wang

2015

Int J Adv Manuf Technol

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“…The specific algorithm used in this study to control the PAW process is the interval model predictive control algorithm originally proposed by [22], Unlike most model predictive control algorithms where nominal models are used, the interval model predictive control algorithm uses a finite impulse response (FIR) model whose parameters are not specified by nominal values but the lower and upper bounds for each of them. The control algo rithm guarantees the stability and desired tracking performance (i.e., the output approaches the set-point) as long as all the param eters of the actual process being controlled are within their corre sponding bounds used in the control algorithm and the sign of the static gain (also an interval) is certain [22].…”

Section: Model Predictive Controlmentioning

confidence: 99%

“…However, there was a constant term in this model. By calculating the impulse response of model (21), the process FIR model is expressed in below equation n yk = Yl hU)vk-j (22) In order to get rid of the constant term, an auxiliary variable v* is introduced and can be expressed with process input uk by Eq.…”

Section: Plasma Arc Welding Process Modelmentioning

confidence: 99%

Predictive Control for Manual Plasma Arc Pipe Welding

Zhang

2014

Journal of Manufacturing Science and Engineering

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A d a p tiv e In te llig e n t S ystem s LLC , L e x in g to n , KY 40511 e -m a il: x ia n g ro n g .li@ o u tlo o k .c o m Y u M in g ZhangA d a ptive In te llig e n t S ystem s LLC , L e x in g to n , KY 4 0 5 1 1 ;In s titu te fo r S u sta in a b le M a n u fa c tu rin g andDepartm ent o f Electrical and C om puter Engineering, Plasma arc welding (PAW) has several advantages over traditional gas tungsten arc welding (GTAW) process. However, due to its sensitivity to welding parameters, this pro cess has not been widely used in industry, especially fo r manual welding applications where variations in welding parameters are substantial. This paper introduces and imple ments a model predictive control (MPC) method to adjust welding current in order to compensate the effects from these variations during manual plasma welding operation. A linear model with adequate accuracy has been selected fo r the design o f control system. Closed-loop control experiments verified the effectiveness o f developed control system.

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“…Indeed, in control engineering [245,52] and in signal processing [297], the impulse response plays an important role. As shown in [553], the interval impulse response could be effectively used for robust controller design. However for all these works, if there exist model uncertainties in a system's state-space model, the uncertain ranges of the impulse response should be carefully estimated.…”

Section: Power Of An Interval Matrixmentioning

confidence: 99%