Artificial intelligence in real-time control

Rodd, M.G.; Verbruggen, H.B.; Krijgsman, A.J.

doi:10.1016/0952-1976(92)90010-h

Cited by 45 publications

(7 citation statements)

References 6 publications

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“…In today's complex systems, the application of these procedures alone may not be sufficient to maximise the performance of a manufacturing organisation. Rodd et al (1992) also stated that when examining the nature of the different manufacturing processes, one is faced with many issues which no single unifying mathematicallyprovable theory can cope with. Rodd stated the following problems:…”

Section: Introductionmentioning

confidence: 99%

“…We need also to predict how our system will perform under certain circumstances. In short, we need to be in a position to model our production and control processes as accurately as possible (Rodd et al, 1992).…”

Section: Introductionmentioning

confidence: 99%

“…Rodd (1992) also stated that when examining the nature of the different manufacturing process, one is faced with many issues which no single unifying mathematically-provable theory can cope with. Rodd stated the following problems: (1) Inherent instability of the process; (2) Mixture of continuous and batch operations; (3) Incomplete and/or excessive data; (4) Unidentified processes; (5) changed processes and (6) Temporal problems.…”

Section: Troductiomentioning

confidence: 99%

“…A danger of isolated small-scale efforts is a tendency to compartmentalise the operations area and as a result design systems which aim for local solutions to sub-problems. Rodd (1992) and Kopacek (1999) state that integration will be the main task facing manufacturing systems in the future. Some attempts are made to integrate some components of the manufacturing system.…”

Section: Integration and Intelligent Agentsmentioning

confidence: 99%

“…In short, we need to be in a position to model our production and control processes as accurately as possible (Rodd, 1992). This paper is a review of the use of AI techniques in manufacturing.…”

Section: Troductiomentioning

confidence: 99%

See 4 more Smart Citations

Intelligent systems in manufacturing: current developments and future prospects

Meziane

Vadera

Kobbacy

et al. 2000

Integrated Manufacturing Systems

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Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence (AI) will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of AI techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different AI techniques to be considered and then shows how these AI techniques are used for the components of IMS.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Troductiomentioning

confidence: 99%

Section: Integration and Intelligent Agentsmentioning

confidence: 99%

Section: Troductiomentioning

confidence: 99%

See 3 more Smart Citations

Intelligent systems in manufacturing: current developments and future prospects

Meziane

Vadera

Kobbacy

et al. 2000

Integrated Manufacturing Systems

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The application of artificial intelligence techniques for intelligent control of dynamical physical systems

Kumar

Mani

1994

Adaptive Control & Signal

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There is an increasing concern among the scientific community and industrialists over the safe and reliable operation of control systems in industries. Although several adaptive control techniques have been introduced, they are not robust enough for many real-world problem domains where the degree of uncertainty is high and therefore classical methods of mathematical modelling and control fail. Computer technology has reached a point where machine intelligence can be incorporated in many of the systems that we use daily. Changes in environments, unmeasurable disturbances, changing reference models and performance criteria and component failures are some of the characteristics which necessitate intelligent control. The developments in the field of artificial intelligence have reached a stage which will help to reduce these control complexities by incorporating intelligence into the control systems. In this paper we explain various artificial intelligence techniques that can be used to control dynamical physical systems.

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