Annual Review in Automatic Programming最新文献

Fieldbus are used to interconnect devices at the process level. At this level, temporal and spatial consistencies are of prime importance. The communication must provide ways to comply with these requirements.

In this paper, we explain the consistency requirements and show how they are supported in existing fieldbus proposals. This study shows that only FIP takes them into account, although partially, while the other proposals leave it to the application. Finally, we show how these requirements may be satisfied in a simple and efficient manner with minor modification and appropriate use of the FIP mechanisms.

In recent years fuzzy logic is increasingly applied to the lower levels of process automation. To identify applications in which fuzzy systems are useful in contrast to other knowledge based methods, it is necessary to distinguish the advantages from using expert knowledge to specify a system behavior in contrast to a formal description and those which arise from the fuzzy interpretation of knowledge. This paper tries to examine this question under aspects like control results, ease of handiness, and implementation. It uses the well known example of the pole balancer problem.

This paper presents the integration of Artificial Intelligence representation techniques and high level Petri nets in a knowledge based manufacturing modeling and analysis system. By means of Petri nets and its implementation based on rules, a model of the system can be constructed. In order to verify the real behavior, the control system interchanges signals with the plant. When an abnormal situation is detected, the control system must take control decisions to allow the system to work in the new situation. Error management in these cases includes detection, diagnosis and reaction. In this paper the hierarchy of object classes to control the system is enlarged to face with the problems produced by abnormal behavior.

In this paper, Fuzzy Control Systems with consecuent functions are analized using concepts from qualitative theory of nonlinear dynamic systems. Particularly, linear weigthed output fuzzy controllers and weight-output fuzzy controller are considered.The consequent function coefficients of rules around the equilibrium point are related with the stability and robustness indices. Finally, a explanatory example is presented.

RH&H's role in the HINT project was to focus on integration, finishing, utilisation, and marketability of the overall technological result. The other HINT partners were responsible for separate AI techniques and system units, which RH&H integrated to create a commercial product. To identify the industrial requirements of a commercial product, RH&H carried out a survey based on qualitative interviews with experienced, technical managers. We realised that to turn a R&D Project into a commercial product, it is crucial first of all to understand the industrial functional needs and the industry's way to conceptualise the world.

This paper presents differents ways of using artificial neural networks in adaptive control. A classification of architectures for control using neural networks is presented, showing the existing paralelism with Adaptive Control techniques.

Implementation of process control of pulsed laser deposition (PLD) requires actuators, sensors and a “materials and processing” knowledge base. Improvements in quality and reproducibility of material deposits are achieved by using this knowledge base to drive the process toward desired operating regions. The knowledge base includes experimentally determined, empirical relationships describing the complex dynamical interactions of laser parameters. Intelligent control based on this description can be implemented to reduce process disorder and efficiently produce consistent coatings with desired properties.

This paper proposes a performance design method of real time system with use of three variation of Bottleneck Diagnosis Expert Systems (BDES), which generate queueing network models of target systems, identify the network bottlenecks, and suggest the designer how to improve the performance of the networks, with use of qualitative reasoning technique. After input of network topology and parameters, these tools show the designer the bottleneck and how to improve it automatically.

An approach for designing the artificial intelligence part into the human-machine interface is described. Two application domains, namely chemical and cement plants, are considered. Interactive techniques for a better involvement of the end-user in earlier design phases are described. They include task and knowledge analyses, participative rapid prototyping design and usability testing. The logical design of knowledge based functionalities of the human-machine interface is exemplified with tracking interaction and supervising dialogue. The support tools for participative design are also briefly mentioned.

A pilot study is described on the practical application of artificial neural networks. The limit cycle of the attitude control of a satellite is selected as the test case. One of the sources of the limit cycle is a position dependent error in the observed attitude. A Reinforcement Learning method is selected, which is able to adapt a controller such that a cost function is optimised. An estimate of the cost function is learned by a neural ‘critic’. In our approach, the estimated cost function is directly represented as a function of the parameters of a linear controller. The critic is implemented as a CMAC network. Results from simulations show that the method is able to find optimal parameters without unstable behaviour. In particular in the case of large discontinuities in the attitude measurements, the method shows a clear improvement compared to the conventional approach: the RMS attitude error decreases approximately 30%.