Expert system control for airborne radar surveillance

US reconfirms anti-dumping duties on Indian & Chinese carbazole violet

Based on the knowledge rule models and the analysis mathematical models, the two-level real-time expert control system (ECS) was established. With the self-learning ability in expert optimal mode, the expert system (ES) was developed to find the calcining zone's optimal temperature value. To optimize the process, the real-time control system (RTCS) was designed to realize the control of the feeding capacity and negative pressure by self-adjusting algorithm based on CARMA module and least square method. At present, the system was started to work on the stream, and the long-term application shows that it has high reliability and good practicability. Besides, the process and the product quality are developed, and the power is economized.

Knowledge-based expert system for optimal reactive power control in distribution system

Delivered software is often late and over budget, while offering fewer features than requested by the user. Many software developers have difficulties establishing and adhering to a project plan and in delivering what the user wants within the budget and schedule. Developers also have difficulty in obtaining user involvement in the development process. This paper discusses a Web-enabled expert system, Project Management Advisor (PMA), which will provide alerts and corrective actions for some of the common problems that plague software development projects. PMA was developed as a part of a CyberCollaboratory built to facilitate collaborative project work. The development and evaluation of a collaborative generic expert system for identification and analysis of anomalies in project plan data is expected to be useful to many software development teams and managers in a wide variety of organizations PMA is a field prototype and was evaluated rising 11 real world project plans. The preliminary analysis of the findings is presented and discussed.

Ensuring safety while using robots in their interaction with humans is one of the main principles of robotics. An expert control system for a robot would be based on the knowledge about such tools, which could help to solve applied problems in that field, where the robot is supposed to be used by humans. Such a system should also include expert, heuristic knowledge on communicative relations of the «human-robot» type. Those relations affect the selection, made by the robot of such problem-solving tools, which would be safe for humans. Thus, the knowledge on communicative relations determines the knowledge on problem-solving tools. Therefore, the application of an expert system for the purposes of robot control should provide a higher safety than a neural network system based on the procedure of machine learning. The goal of this research is to develop such a component of the expert control system, which would exclude the possibility of a robot causing health and life damage to a human. The method of achieving this goal consists of integrating a phenomenon of self-organization, inherent to a collective control subject within intersubjective «human-robot» relations, into production rules of the robot knowledge base. The knowledge base of the expert robot-control system should include the knowledge about equivalence of communicative relations between humans and robots. The research results in such a concept model of that component in the knowledge base of the expert robot-control system which would enable both the mechanism of feedback between a subject and an object of the control and the safety of managing such a complex intellectual technical system as a robot. The study is interdisciplinary by its nature and unites several approaches from the fields of cybernetics, synergetics, artificial intelligence, the logic of relations and gnosiology. The research concludes that an expert robot-control system, based on self-organization, provides safe cooperation between robots and humans.

Expert-system technology has emerged from beneath the umbrella of Artificial Intelligence and into the mainstream of engineering problem solving. There already are several notable examples of the application of this state-of-the-art technology in the petroleum industry. Clearly, expert systems that run efficiently on standard personal computers are particularly of value. A new expert-system generator that overcomes the speed, memory and mass-storage limitations of XT/AT-class personal computers is presented in this paper. The shell is optimized for the specific characteristics of the target user, knowledge expert and computer. Expert systems developed using this shell currently are being used by our technical personnel for drilling fluid and related applications.

This paper considers the possible enhancement of the capabilities of an expert system tool. Most of the commercial tools currently available are not particularly suitable for developing expert systems that involve routine design calculations. To overcome this drawback for engineering applications, numerical computations may be carried out by conventional computer programs which can be linked to an expert system tool through its external program interface. This type of expert systems is called a "hybrid" or "coupled" expert system. Practicing engineers will, sooner or later, face the need to use hybrid expert systems. This paper presents a case study which shows how the capabilities of a commercial expert system tool can be enhanced by integrating it with a conventional computer program. The hybrid expert system developed by the authors for illustration purpose can be used for the analysis of plane steel trusses and the evaluation of member design forces. It utilizes an in-house program called “Manager” to integrate two commercial software packages: an expert system tool called KES and a structural analysis package named PFRAME. The capabilities of the hybrid system appear to exceed those of the individual software packages. Key words: knowledge based expert systems, expert system building tools, hybrid expert systems, structural analysis, structural design.

Development of a prototype expert system for identification and control of insect pests

Educational aspect of expert control of technological processes

Expert system has the least focus on requirement engineering. In facts, requirement engineering is important to get all the requirements needed for an expert system. If the requirements do not meet the clients' needs, the expert system is considered fail although it works perfectly. Currently, there are a lot of studies proposing and describing the development of expert systems. However, they are focusing in a specific and narrow domain of problems. Also, the major concern of most researchers is the design issues of the expert system. Therefore, we emphasize on the very first step of success expert system development - requirement engineering. Hence, we are focusing in the requirement engineering techniques in order to present the most practical way to facilitate requirement engineering processes. In this paper, we analyze expert system attributes, requirement engineering processes in expert system developments and the possible techniques that can be applied to expert system developments. Next, we propose the most appropriate techniques for the expert system developments based on the analysis. From this paper, a set of techniques for expert system development will be provided.

To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).© (1991) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

A multifunction phased array radar must search and track suspicious targets in its surveillance space in a real-time fashion. With inefficient scheduling implementations in many traditional systems, much radar resource is wasted with a very limited performance gain. This paper targets one of the most important issues in the design of modern phased array radars: real-time dwell scheduling. We formalize the typical workload of a modern phased array radar and propose a rate-based approach to schedule radar dwells in a real-time fashion. We show how to reserve radar resources to guarantee the minimum radar operation without sacrificing the stability of the system. The strength of our approach is verified by a series of simulation experiments based on a real phased array radar for air defense frigates [A. G. Huizing et al. (1996)]. A significant improvement in the performance of phased array radars was shown.

The Gensym real-time expert system G2 integrates dynamic models and rules to combine analytic and heuristic knowledge representation. The inference engine can reason about object connectivity and can use generic forms of knowledge, interpreted for specific instances in the domain. Designed for process control and related applications, G2 allows the process engineer to implement and manage the expert system. A network architecture allows hierarchical or co-operating expert systems in the plant.The first Expert Control System using G2 is described. The Reliable Water Company in Boston has implemented G2 for control and on-line diagnostics for a water purification process. The system was first demonstrated in June 1987, in prototype form, purifying water from the Boston Harbor. Delivery versions are now being deployed.

The control centres of New Zealand's power transmission network arc flooded with alarm messages during a major system outage. A majority of these faults involves the transformer trips. To help the system controllers to restore the transformers Transpower NZ Ltd., New Zealand's power transmission company, has developed a expert control system to perform a real-time analysis of the incoming alarms, identify transformer related events, analyse the faults and provide a real-time restoration advise on transformer restoration. This paper describes the problem tackled by Transpower's system controllers and our expert control system that assists in solving the problem. It discusses the types of knowledge represented, the architecture involved, some implementation details and the performance analysis.

This paper describes experiments designed to test the feasibility of linking discrete-event simulation models with expert systems. Two microcomputer systems are used: one contains the simulation model, while the other contains the expert system. The paper shows that by linking a simulation model with an expert system, it is possible to use the combination for simulation parameter learning, expert system development and expert system control of a simulation model.