Real-time integrated process supervision

This paper presents the use of a micro-controller-based integrated process supervision (IPS) system as a real-time platform for investigative work in structuring expert control. Two different control approaches, based on classical and artificial intelligence techniques, were integrated within IPS and serve as practical examples of the structured approach to expert control. The IPS is a refinement of the expert control architecture. It allows the integration of several control techniques in a single generic framework. Specifically, the paper presents the extensive experimental results derived from a micro-controller-based implementation of IPS on the real-time control of a typical industrial heat-exchanger process. The classical approach, based on auto-tuning techniques, was implemented under the IPS framework. Three auto-tuning techniques, namely Ziegler–Nichols tuning, amplitude tuning and phase tuning were incorporated. In addition, neural-network-based control techniques using the modified cerebellar model articulation controller (MCMAC) were also seamlessly incorporated within the IPS scheme. The real-time experimental results using the IPS architecture significantly demonstrated the effectiveness of IPS in handling varying operating conditions. Furthermore, the inclusion of both AI and classical control techniques within a common supervisory framework adequately shows the generality of the architecture.     

Neural-network-based blackboard demon subsystems

We propose two neural network architectures involving feedforward and probabilistic neural network models to simulate the blackboard demon subsystem, which is responsible for triggering knowledge sources in accordance with the complex monitoring conditions on the hypotheses in the blackboard. Both architectures involve a preprocessor module to perform the transformation between symbolic hypotheses and numerical ones. They learn and record the triggering relationships between hypotheses and knowledge sources in the network links and perform better blackboard monitoring function than the traditional symbolic demon subsystems. In comparison, the probabilistic neural network-like architecture performs better when there is a possibility of using a centralized knowledge representation and when it only involves one-to-one or one-to-many mapping between hypotheses and triggering patterns. The feedforward architecture may be useful when a distributed knowledge representation is possible and when time requirements for training the architecture to learn the complex mappings are not too strict.     

Realisation of neural network controllers in integrated process supervision

Recent developments in neural network controllers have focused mainly on either primary or adaptive control techniques. To date, there has been little attempt to integrate and schedule them within a common control framework on the basis of the system behaviour. An architecture for integrated process supervision, IPS, has been proposed by Leitch and Quek (IEE Proc.-D, Control Theory and Application, 39(3) (1992) 317-27) as a general meta-level supervisory system which automatically schedules between generic control tasks according to the system performance. The IPS scheme was successfully validated using various classical and adaptive controllers (Leitch and Quek, IEE Proc. 3rd Int. Conf. Control, Vol. 1, March, 1991, pp. 127-33; Ho and Goh, Final Year Dissertation, Nanyang Technological University, 1993). This paper demonstrates how the IPS scheme can be used to integrate and schedule between the neural network primary and adaptive control regimes. The cerebellar model articulation controller (Conforth & Elliman, in Techniques and Applications of Neural Networks, ed. M. Taylor & P. Lisboa. Prentice Hall, UK, 1993, pp. 35–46), CMAC, is chosen for this purpose. Its structure is modified and integrated within the IPS scheme. The modification results in better system performances than the standard PI controllers. Moreover the realisation of the modified CMAC and its associated learning algorithm within the IPS illustrates the generality of the IPS as a generic meta-level supervisory control architecture.     

搅拌设备化工预设计专家系统的黑板系统结构

传统的手工设计混合设备的方法十分耗时且容易出错,因此实现设计的自动化和智能化是非常用意义的开发了搅拌设备化工预设计专家系统系统。详细介绍了专家系统的结构,系统采用两层黑板结构模型和多种知识源相结合的策略,来处理解决复杂的协同问题。知识源包括设计规则库、设计公式库和机械设备标准库,内部黑板主要是为规则库的推理机存储信息服务,而全局黑板系统则是整个系统的数据共享和信息交换中心,并采用层次框架结构进行表达,将人工智能技术与普通设计程序相结合,可以在设计过程为用户提供系统的帮助和指导,来实现搅拌设备设计的自动化和智能化。     

An architecture for a self-improving instructional planner for intelligent tutoring systems

Machine instructional planners use changing and uncertain data to incrementally configure plans and control the execution and dynamic refinement of these plans. Current instructional planners cannot adequately plan, replan, and monitor the delivery of instruction. This is due in part to the fact that current instructional planners are incapable of planning in a global context, developing competing plans in parallel, monitoring their planning behavior, and dynamically adapting their control behavior. In response to these and other deficiencies of instructional planners a generic system architecture based on the blackboard model was implemented. This self-improving instructional planner (SUP) dynamically creates instructional plans, requests execution of these plans, replans, and improves its planning behavior based on a student's responses to tutoring. Global planning was facilitated by explicitly representing decisions about past, current, and future plans on a global data structure called the plan blackboard. Planning in multiple worlds is facilitated by labeling plan decisions by the context in which they were generated. Plan monitoring was implemented as a set of monitoring knowledge sources. The flexible control capability for instructional planner was adapted from the blackboard architecture BB1. The explicit control structure of SUP enabled complex and flexible planning behavior while maintaining a simple planning architecture.     

A knowledge-based framework for automated software synthesis

Automated software synthesis is one of the central techniques used in knowledge-based software engineering to enhance the quality and efficiency of software development. Although many software synthesis systems have been developed, automatic control of these systems remains a difficult problem. Our goal is to reduce user interaction in transformational and schema-based synthesizers by means of significant advances in control mechanisms.This paper describes an approach for synthesis control that integrates a blackboard control architecture with an existing synthesis system. We present a framework language called MetaMorphos that allows explicit representations of control knowledge for use in selecting appropriate synthesis actions. MetaMorphos represents control decisions explicitly in terms of actions, events, and states. It is task-specific and contains knowledge about programming and how to select synthesizing methods based on given features. By employing a blackboard control architecture, our synthesis controller provides adaptability for dynamic control behaviors and flexibility to handle unanticipated situations during software development.Applying MetaMorphos in the domain of software synthesis, we illustrate how we use MetaMorphos to select appropriate transformations, data structure and algorithm schemas during the synthesis. An example shows how MetaMorphos handles the difficult problem of selecting schemas for two very similar problems which, in the best case, require different solutions.     

A blackboard approach to modeling expertise in corporate settlement decisions*

Abstract: The SKADE system models expertise in corporate settlement decisions using the blackboard approach. The full model has four knowledge sources: General Counsel, Attorney, Manager and Insurance Adjuster. The combined expertise from each of these is required to make the settlement decision. A control component in the model coordinates the activities of the various knowledge sources. Based on the latest data entries on the blackboard, the control selects and executes the next knowledge source. The blackboard model reproduces the experts' opportunistic reasoning processes by the interaction between the various knowledge sources. The results of analyses of a hypothetical case through a series of experiments with the SKADE system indicate that the blackboard is an appropriate model for development of multiple cooperative expert systems in the settlement decision domain. Compared to straight rule-based models, this blackboard provides more efficient problem solving. The initial success with the blackboard model suggests that further work needs to be done to see whether more complex models can be built to incorporate a broader range of determinants of settlement decisions.     

Development of an object-oriented blackboard model for stamping process planning in progressive die design

This paper reports preliminary work to investigate the suitability of using a blackboard framework as a problem-solving model for stamping process planning in progressive die design. The model is described at two levels: knowledge level and computational level. The knowledge level describes how the stamping process planning domain is represented in a blackboard architecture. The computational level describes how the blackboard architecture is modeled and implemented using object technology. A software prototype has been developed using CLIPS and C++ interfaced with Solid Edge CAD system. An example is presented to illustrate the feasibility and practicality of the proposed approach.     

基于本体的MAS黑板模型研究

探讨了基于本体的多智能代理黑板知识库系统(OMSBS)的体系结构及OMABS中Agent的模型、组织和交互方式。提出了一种描述混合知识类型的本体知识表达模型。本体在OMSBS中作为领域知识智能代理的知识库，是知识共享和智能代理之间通讯的基础，设计了一类调度智能代理以控制知识源智能代理的行为。OMSBS可以表达混合类型知识及其推理过程，具有良好的适应性和扩展性，呈现出开放结构。     

A blackboard system for the off-line programming of Robots

This paper describes the use of the blackboard architecture for the off-line programming of an IMB 7565 Robot. A blackboard system was implemented in PROLOG and it has been applied successfully for the automatic generation of a control code for the robot to perform the task of block assembly in an environment with an obstacle. The opportunistic type of problem-solving offered by the blackboard architecture has succeeded in obtaining a solution. The user-interface to the system is represented as a knowledge source in the blackboard system, which allows the user to modify the goal specifications during the operation of the blackboard system.     

Goal-driven blackboard control architecture based on extending partially complete general goal trees

A control architecture for goal-driven blackboard systems is introduced. The basic elements of the architecture are goals, policies, strategies, methods and knowledge sources. The basic control loop employs a bidding mechanism to determine the knowledge source to be executed at the current cycle. The architecture employs separate control and domain blackboards, and separate knowledge sources for the control problem and for representing the domain knowledge. The major characteristics of the architecture are that it has a simple and uniform structure, and that its basic control loop is based on a formal basis, namely, extending a partially complete general goal tree. The architecture is implemented in Smalltalk and tested on a multiple-task planning problem.     

面向对象远程监控系统框架研究

针对目前远程监控系统开发成本高、大量冗余局部解决方案的现状 ,提出了可复用远程监控系统框架的通用解决方案 .通过抽取远程监控系统的基本逻辑模型 ,建立了易于扩展、可复用的远程监控系统基本框架 ,从而在大大减少重复劳动、提高劳动生产率的同时 ,促进各方面性能都比较优越的远程监控系统的诞生 .并通过某小型变电站应用实例验证了本方案的可行性以及应用前景     

Intelligent on-line system identification using a blackboard system

Adaptive control systems have been developed and used for a number of decades. However, there are still some problems with their operation, which limit wider industrial adoption. This paper addresses one aspect of adaptive control, namely the on-line system identification of the time-varying process being controlled. The approach adopted is to use a blackboard system to identify the time-varying process model. The blackboard system contains knowledge sources with, algorithmic, fuzzy-logic and evolutionary reasoning. The paper describes the design of a computer simulation of this approach, concentrating on the fuzzy reasoning used to validate the multiple models, and the evolutionary techniques used to reject poor models and introduce better models. The computer simulation is then evaluated, firstly using simulated plant data and then using real plant data from an experimental hot air dryer. It is concluded that the technique is practical, and worthy of further testing on a pilot plant.     

《机械设计》CAI软件中黑板功能的实现研究

提出了CAI软件中黑板功能的概念,在分析课程特点的基础上对《机械设计》课程CAI软件中黑板功能的具体要求,实现思想和结构框架进行了研究,并利用Visual C 6．0编制了一个可行的黑板功能模块。     

Process objects/masked composition: an object-oriented approach formodeling and control of discrete-event systems

An object oriented framework for modeling and supervisory control of discrete-event systems is described. Control and observation masks are encapsulated with process logic to form process objects, and a single type of interconnection operator called masked composition is used to build complex process objects out of simpler component process objects. The approach applies to both deterministic and nondeterministic plant models and supervisory design. In addition to the usual benefits of object-oriented design, such as software reusability, it yields conditions under which the existence of a nondeterministic supervisor implies existence of a deterministic supervisor     

Knowledge decomposition for a product design blackboard expert system

Product design is a complex process, requiring many design factors and knowledge areas to be considered simultaneously. An expert system with a blackboard architecture is appropriate for representing this variety of factors and areas. However, oftentimes it is unclear how to transform the knowledge into the component knowledge bases of a blackboard expert system. The paper describes a non-directed graph decomposition procedure for transforming the knowledge into knowledge bases as part of an approach for developing a product design blackboard expert system. A wood head golf club design example is provided.     

The blackboard model: a survey of its application

The need for co-operation and communication between Knowledge-Based Systems (KBSs) has prompted research into the field of Distributed Artificial Intelligence (DAI). A number of paradigms have been proposed — including the blackboard model.A de facto blackboard model is described which contains three components: the blackboard data structure, knowledge sources and a means for control. To enable comparison between existing applications, a set of attributes has been distilled from the model.Identification of three distinct groupings of current systems has led to the proposal of a taxonomy of blackboard systems. This consists of three generations of development: dedicated systems, generic shells and tool-based architectures.In light of this, an evaluation of the blackboard model is made, with respect to its significance to the field of DAI research.     

基于知识的,集成工具化的汽车锻件模具设计过程的仿真思想

提出了一个基于知识的，集成ＣＡＤ／ＣＡＭ模块，有限元分析模块，Ｍｏｔｉｆ界面制作模块的汽车锻件模具设计的仿真系统，此系统可推广到其它类似的模具设计过程仿真。     

Inter/intra process communications in ISTS

The complexity of maintaining a generic and flexible Intelligent Simulation-Based Training System (ISTS) necessitates a coordinated methodology to handle inter and intra process communications. Several issues must be considered before committing to one form of process communication. Such issues involve system portability, real time interaction, distributed system realization, memory, and multi-process communications. This document examines the application of different communication strategies to ISTS. The advantages and disadvantages of using memory-based InterProcess Communication (IPC) facilities in SunOS operating system versus the use of properties for communication in an X Window environment are described. Furthermore, the use of rule-based blackboard architecture to handle communications between modules within the Tutoring group is presented. This research provides the ground work for a flexible and generic Intelligent Simulation Training System.     

Model-based design of supervisory controllers for baggage handling systems

The complexity of airport baggage handling systems in combination with the required high level of robustness makes designing supervisory controllers for these systems a challenging task.We show how a state of the art, formal, model-based design framework has been successfully used for model-based design of supervisory controllers for an actual industrial baggage handling system, and for a real-time emulation model of an actual international airport.The high level modeling elements of the applied CIF model-based design framework allow the modeler to concentrate on implementing the baggage handling system design requirements, instead of programming PLC code. It also allows a modular and hierarchical design of the supervisory controller, and provides flexibility in adapting and extending the model. Validation of the controller and the uncontrolled plant by means of simulation and visualization made it possible to catch all modeling errors, leading to very short modeling, testing and error correction iteration loops.To the best of our knowledge, this is the first successful employment of formal, model-based design in the context of supervisory control for actual, industrial size baggage handling systems, that covers the entire development process from requirements up to and including validation, real-time PLC code generation and implementation.We give an overview of the model-based design framework, discuss several modeling issues, and analyze the results of the industrial applications. We do not go into full technical detail, due to nondisclosure agreements, but tell the story, and give lessons learned that we consider useful for practitioners.