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作者： Harris, Chris J. Wu, Zhi Qiao Gan, Qiang Image Speech/Intelligent Syst. R.G. Department of Electronics University of Southampton Southampton SO17 1BJ United Kingdom

Neurofuzzy algorithms have been extensively developed in recent years for the real time/online identification of nonlinear a priori unknown dynamical processes. As with all rule base paradigms they suffer from the curse of dimensionality, restricting their practical use to low dimensional control problems. This paper shows how adaptive construction algorithms based on additive decomposition techniques can overcome this problem, to produce parsimonious neurofuzzy models which retain their transparency or interpretability. Not only does this approach extend the applicability of neurofuzzy algorithms, it also enables low complexity controllers and estimators to be derived. In this context neurofuzzy state estimators are derived, which automatically parameterise a Kalman filter for a process state estimate reconstruction from any input/output data source. This approach avoids pitfalls of the extended Kalman filter, and is optimal for local models. The paper discusses real world applications of this new theory of modelling and estimation to helicopter guidance, intelligent driver warning system, communication antennas, autonomous underwater vehicles, ship collision avoidance guidance, and an IFAC benchmark problem.

关键词： Neural networks

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Neurofuzzy state estimators and their applications

Neurofuzzy state estimators and their applications

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iee colloquium on Advances in control Technology (Ref. No. 1999/142),

作者： C.J. Harris Z.Q. Wu Q. Gan Image Speech and Intelligent Systems Research Group Department of Electronics and Computer Science University of Southampton Southampton UK

Neurofuzzy algorithms have been extensively developed for the real time/online identification of nonlinear a priori unknown dynamical processes. As with all rule base paradigms they suffer from the curse of dimensionality, restricting their practical use to low dimensional control problems. The paper shows how adaptive construction algorithms based on additive decomposition techniques can overcome this problem, to produce parsimonious neurofuzzy models which retain their transparency or interpretability. Not only does this approach extend the applicability of neurofuzzy algorithms, it also enables low complexity controllers and estimators to be derived. In this context neurofuzzy state estimators are derived, which automatically parameterise a Kalman filter for a process state estimate reconstruction from any input/output data source. This approach avoids pitfalls of the extended Kalman filter, and is optimal for local models. The paper discusses real world applications of this new theory of modelling and estimation to helicopter guidance, intelligent driver warning system, communication antennas, autonomous underwater vehicles, ship collision avoidance guidance, and an IFAC benchmark problem.

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Self-learning fuzzy logic control of anaesthetic drug infusions

Self-learning fuzzy logic control of anaesthetic drug infusi...

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iee colloquium on Intelligent Methods in Healthcare and Medical applications (Digest No. 1998/514)

作者： D.G. Mason D.A. Linkens N.D. Edwards J.J. Ross Depts Automatic Control & Systems Engineering University of Sheffield Sheffield UK Surgical & Anaesthetic Sciences University of Sheffield Sheffield UK

We are researching into clinical applications of self-learning fuzzy logic control, an intelligent form of direct adaptive control which permits online learning of fuzzy control rules. The adaptive mechanism in this method is based on a performance index, an error from a pre-specified desired trajectory, which modifies the consequent of previously online-generated fuzzy control rules. There is a need to account for the transport delay incurred by the time taken by the bloodstream to transport the drug from the infusion site to its action sites, which is about one minute. There is also a need to give the time for the patient measurement to start to respond to the altered drug infusion rate. For most anaesthetic drug infusions, this means that the generated fuzzy control rules are stored for two minutes before they are modified and incorporated into the fuzzy control rule base. We have clinically demonstrated the effectiveness of this intelligent control technique with muscle relaxation during surgery, starting each session with a completely blank rule base and having the controller learn the rules required by each patient online. We are now investigating the application of this technique to a more generally realistic clinical scenario where multiple drug infusions are managed based on multiple patient measurements: haemodynamic support of intensive care patients in septic shock. This application highlights problems with dimensionality as the number of input and output variables increases and thus challenges its general application to complex processes.

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Experiences from a Prolog-based environment for modelling and simulation: An example of the application of logic programming in control engineering

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iee colloquium (Digest) 1996年第78期 varpaging页

作者： Tanyi, E.B. Linkens, D.A. Univ of Yaounde I Yaounde Cameroon

This paper describes the use of Prolog in the implementation of a knowledge-based Environment for Modelling and Simulation (KEMS). The basis of the implementation is the AI frame paradigm which provides a conceptual foundation for the design of the Model base, the Simulation Code Generator and the knowledge Acquisition Module which are the Prolog-based components of KEMS. The experiences derived from KEMS provide a springboard from which the wider applications of Logic programming in control Engineering are discussed. Six application areas are identified, including modelling, the design of from-ends for CAD packages, the design of object-oriented databases, the prototyping of engineering concepts, knowledge-based control and the design of decision-support systems.

关键词： control system synthesis

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Experiences from a Prolog-based environment for modelling and simulation: an example of the application of logic programming in control engineering

Experiences from a Prolog-based environment for modelling an...

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iee colloquium on Symbolic Computation for control (Digest No: 1996/078)

作者： E.B. Tanyi D.A. Linkens Dept. of Electr. Eng. Yaounde Univ. I Cameroon Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK

The paper describes the use of Prolog in the implementation of a knowledge-based Environment for Modelling and Simulation (KEMS). The basis of the implementation is the AI frame paradigm which provides a conceptual foundation for the design of the model base, the simulation code generator and the knowledge acquisition module which are the Prolog-based components of KEMS. The experiences derived from KEMS provide a springboard from which the wider applications of logic programming in control engineering are discussed. Six application areas are identified, including modelling, the design of front-ends for CAD packages, the design of object-oriented databases, the prototyping of engineering concepts, knowledge-based control and the design of decision-support systems.

关键词： Prolog

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Soft-computing in the control of electrical drives

Soft-computing in the control of electrical drives

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iee colloquium on Advances in control Systems for Electric Drives

作者： P.C.K. Luk J.Y.M. Cheung C.K. Lee School of Electronic & Electrical Engineering Robert Gordon University Aberdeen UK School of Engineering Bolton Institute Bolton UK Electronic Engineering Department Hong Kong Polytechnic Hong Kong China

The principal constituents of soft computing are the fuzzy logic (FL), artificial neural networks (NN) and probabilistic reasoning (PR). It is generally regarded that FL primarily deals with imprecision, NN with learning, and PR with uncertainty. They have, however, overlapping boundaries and are known to be complementary rather than competitive to each other in many applications. Here, two control algorithms, one implemented by fuzzy logic and the other by a neural network, are used as the basis to highlight salient features of soft computing. A DC motor servo system with the proposed soft computing based algorithms is discussed. The fuzzy logic control employs the principles of fuzzy logic to calculate an optimal output action based on input conditions, and a knowledge base expressed in linguistic forms, thereby performing a parallel operation to control the output with a high degree of robustness against parameter change. In the neural network control, focus is on how neural networks can overcome deadzone-plus-saturation nonlinearity commonly found in the power driver of a DC servo motor. Simulation results have been performed to establish the validity of these control algorithms.< >

关键词： Adaptive control DC motor drives Fuzzy control Neural networks Optimal control Servomotors Uncertain systems

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Building on HAZOP (hazard and operability) studies to reproduce knowledge-based systems

Building on HAZOP (hazard and operability) studies to reprod...

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Proceedings of the iee colloquium on knowledge-based Systems for Safety Critical applications

作者： Tait, J.I. Univ of Sunderland Sunderland United Kingdom

One of the major problems in constructing knowledge-based systems is so-called verification, i.e. ensuring the system's knowledge is correct in some sense. This problem is felt particularly acutely in safety critical systems, where of course inclusion of incorrect knowledge may threaten life. The safety of a new chemical plant is ensured by an extensive review of its design, control and operability called a Hazard and Operability (HAZOP) Study. This means that design data which has been reviewed through the HAZOP study can be regarded as conforming with the safe operation of the plant. This paper discusses an automatic method of extracting knowledge from the results of the HAZOP study for use in knowledge-based systems. Although additional knowledge (for example more general knowledge of physics or fault diagnosis) may be required to build a complete application, the method in effect provides verification `for free' of a substantial part of the knowledge base.

关键词： knowledge based systems

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Case-based reasoning system for troubleshooting

Case-based reasoning system for troubleshooting

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Computing and control Division Colloqiuim on Case based Reasoning: Prospects for applications

作者： Bub, Rudiger Henderson, William Wrigley, David Wilson, John Univ of Northumbria at Newcastle Newcastle Upon Tyne United Kingdom

This paper describes a project using a Case-based reasoning system for troubleshooting purposes. The problem domain is the production equipment of a battery separator manufacturing site. The aim of the project is to assist the users to diagnose faults thereby reducing down time. Case-based reasoning (CBR) is a new approach using knowledge from past experiences to solve or evaluate new problems. CBR suggests actions to take or makes recommendations by comparing (matching) the current situation with similar previous situations. The paper outlines the development of a CBR Express system at Cookson Entek Limited It explains the problem domain and the type of data acquired. The paper gives some details about the benefits and limitations of this technology. Suggestions are made for further improvements to the software which would increase the performance of the case-base. The paper concludes with an outlook for future work at Cookson Entek.

关键词： knowledge based systems

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Building on HAZOP (hazard and operability) studies to produce knowledge-based systems

Building on HAZOP (hazard and operability) studies to produc...

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iee colloquium on knowledge-based Systems for Safety Critical applications

作者： J.I. Tait School of Computing and Information Systems University of Sunderland Sunderland UK

One of the major problems in constructing knowledge-based systems is so-called verification, i.e. ensuring the system's knowledge is correct in some sense. This problem is felt particularly acutely in safety critical systems, where of course inclusion of incorrect knowledge may threaten life. The safety of a new chemical plant is ensured by an extensive review of its design, control and operability called a Hazard and Operability (HAZOP) Study. This means that design data which has been reviewed through the HAZOP study can be regarded as conforming with the safe operation of the plant. This paper discusses an automatic method of extracting knowledge from the results of the HAZOP study for use in knowledge-based systems. Although additional knowledge (for example more general knowledge of physics or fault diagnosis) may be required to build a complete application, the method in effect provides verification 'for free' of a substantial part of the knowledge base.< >

关键词： knowledge acquisition knowledge engineering Safety Software reliability

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Comparing several implementations of a hardware hasher unit

Comparing several implementations of a hardware hasher unit

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iee colloquium on Field Programmable Gate Arrays - Technology and applications

作者： M.J. Lear E. James S.H. Lavington B. Srisuchinwong T.A. York A.M. Somerville Department of Computer Science University of Essex Colchester UK Department of Electrical Eng. & Electronics University of Manchester Institute of Science and Technology Manchester UK

As part of the design of a knowledge-base server, there arose a requirement for a hardware sub-unit which could perform a general hashing function on variable length tuples. The knowledge-base server uses transputers for its internal control. The hardware hasher unit replaces an OCCAM procedure which took an unacceptably long time to execute (about 10 microseconds). The target time was under 160 nanoseconds. The first implementation of the hardware hasher was carried out using conventional GAL technology. This worked at acceptable speed (order of 40 nanoseconds) but the nine GAL chips took up a relatively large amount of PCB area. Hasher designs have since been implemented in Xilinx 3000 series FPGA technology, Altera MAX series 5000 technology, Actel ACT1 technology, National MAPL technology, AMD MACH technology, and Lattice Semiconductor pLSI technology. This paper compares the speed, cost and PCB area for all seven designs. The authors also comment generally on the suitability of each candidate technology for this type of task, and then draw some conclusions which may help to guide future designs in other applications areas.< >

关键词： File systems File servers knowledge based systems Logic arrays

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