By Spyros Tzafestas, Henk Verbruggen (auth.), Professor Spyros G. Tzafestas, Henk B. Verbruggen (eds.)
This booklet is anxious with man made Intelligence (AI) ideas and strategies as utilized to commercial selection making, keep watch over and automation difficulties. the sphere of AI has been multiplied greatly over the last years as a result of that sturdy theoretical and alertness effects have accrued. through the first degree of AI improvement so much staff within the box have been content material with illustrations displaying rules at paintings on basic difficulties. Later, because the box matured, emphasis was once grew to become to demonstrations that confirmed the potential of AI recommendations to deal with difficulties of functional price. Now, we arrived on the degree the place researchers and practitioners are literally construction AI structures that face real-world and business difficulties. This quantity presents a collection of twenty 4 well-selected contributions that care for the applying of AI to such real-life and commercial difficulties. those contributions are grouped and offered in 5 elements as follows: half 1: basic matters half 2: clever platforms half three: Neural Networks in Modelling, keep watch over and Scheduling half four: approach Diagnostics half five: commercial robot, production and Organizational platforms half 1 comprises 4 chapters delivering historical past fabric and working with common concerns similar to the conceptual integration of qualitative and quantitative versions, the therapy of timing difficulties at approach integration, and the research of right reasoning in interactive man-robot systems.
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Extra info for Artificial Intelligence in Industrial Decision Making, Control and Automation
In QR the system at hand is regarded as a series of sub-systems where the state of each subsystem is represented by its associated "state variable" using a qualitative quantitiy space (say +, 0, -). Thus the state Xi of the subsystem i can at any instant of time take one og the values ( + ), (0) or (-). e. Xj+l .. M-plus(Xj) or Xj+l = M-minus(Xi ) In  a two subsystems plant was considered with an M-plus dynamic relationship (Fig. 5). '--__x_l_---'I M-pJus 1. __ X_2_--, Fig. 5. A 2-sub-system plant with M-plus interaction The problem is to determine the change in Xl to cause X 2 to change from ( + ) to « + ),(0),(-» respectively, then from (0) to « + ),(0),(-», and finally from (-) to « +), (0), (-».
For a review of QR methods and their comparison with other AI methodologies the reader is referred to . The above controller was applied in [301 to a two coupled tanks system which has intrisically non-linear characteristics. The control objective was to regulate the level of the liquid in tank 2. We close our discussion on QR by mentioning the work on Order of Magnitude (OM) of Mavrovouniotis and Stephanopoulos [38-39]. The key idea is to extend the relational algebra concept of greater-than, equal or less-than ( +, 0, -) to the 16 Table 1: Control Rules for a Monotonically Increasing Relationship Rule Xl Current X2 Required X2 1 0" + + + + + 2 - + 0 3 - + - 4 + 0 + 5 0 0 0 6 - 0 - 7 + - + 8 + 0 9 0" - - - - - following seven primitives much-smaller than moderately-smaller than slightly-smaller than exactly-equal to slightly-larger than moderately-larger than much larger than The authors discuss the application of the OeM) reasoning to some process engineering and bio-engineering problems.
Automatic dishwashing or automatic serving). Both approaches have relative advan~ages and disadvantages. Our purpose in this chapter is to provide an introductory survey of AI and knowledge-based techniques applied to decision making, control and automation processes. For completeness, the chapter starts with a look at the decision making, control and automation systems themselves. Section 3 discusses three basic AI approaches to decision making, control and automation, namely: reasoning under uncertainty, qualitative reasoning, and neural nets reasoning.