Janos L. Grantner

Digital fuzzy logic controller: design and implementation

In this paper, various aspects of digital fuzzy logic controller (FLC) design and implementation are discussed, Classic and improved models of the single-input single-output (SISO), multiple-input single-output (MISC), and multiple-input multiple-output (MIMO) FLCs are analyzed in terms of hardware cost and performance. A set of universal parameters to characterize any hardware realization of digital FLCs is defined. The comparative study of classic and alternative MIMO FLCs is presented as a generalization of other controller configurations. A processing element for the parallel FLC architecture realizing improved inferencing of MIMO system is designed, characterized, and tested. Finally, as a case feasibility study, a direct data stream architecture for complete digital fuzzy controller is shown as an improved solution for high-speed, cost-effective, real-time control applications.

Intelligent Decision Support System

There is a need to develop an automated assessment and training procedure for children with eye-hand coordination problem. Such system is expected to reduce the burden and the associated cost of having a trained professional present at any assessment, or training session for each child. The intelligent decision support system is based upon a fuzzy automaton. By using qualitative (fuzzified) data from the previous test the system will make a decision on the complexity of the next test to be performed. A set of assessment tests, commonly used by occupational therapists, were chosen to implement the various functions using force, inertia and viscosity effects. A test bed has been designed for these tasks that consists of a six-degree-of-freedom force-reflecting haptic interface device called PHANToM along with the GHOST SDK Software, and the Intelligent Decision Support System software.

Synthesis and analysis of fuzzy logic finite state machine models

A common drawback of most linguistic models is that they are essentially static, time is not a parameter in describing the behavior of the process model, or they are unable to respond to a specific sequence of changes at the inputs of the system. Dynamic linguistic models can be implemented by fuzzy automata. Of the feasible solutions, at present, fuzzy logic RISC processors and fuzzy logic finite state machines (ASIC) seem to be most promising. The latter approach is taken into consideration. In this paper the model of the fuzzy-state-fuzzy-output (FSFO) finite state machine (FSM) is discussed in detail. The state membership function (SMF) is introduced and the FSFO FSM implementation by means of crisp-state-fuzzy-output (CSFO) FSM using SMF is proposed. The multivariable model and inference scheme are suggested based on CSFO and FSFO FSM.<<ETX>>

Hybrid fuzzy-Boolean automata for ontological controllers

This paper introduces a hybrid fuzzy-Boolean finite state machine (HFB FSM) model for ontological control. Ontological control is a novel type supervisory control that deals with the problems of error detection and recovery in complex control systems. The HFB FSM is used as a specification method for the problem of recovery when an autonomous control system encounters unexpected changes in its environment. The method allows a controller B (the ontological controller) to trigger a recovery operation on controller A when B has the recovery specification of A. The approach has important potential applications in industry.

Fuzzy automaton for intelligent hybrid control systems

It is a difficult problem to track the status of an event-driven, large hybrid control system. These systems often encounter unexpected events in an uncertain environment. Using a fuzzy automaton offers an effective approximation method to model continuous and discrete signals in a single theoretical framework. The concept of the virtual fuzzy automaton is used to deal with a cluster of relevant states when a decision is made on the next state of a goal path at the supervisory level. The software architecture of an autonomous agent-based industrial control system is outlined, in which the agents utilize a fuzzy automaton that is wrapped in an object.

Hardware implementations of digital fuzzy logic controllers

In this paper, various implementation issues of digital fuzzy logic controllers (FLC) are investigated. Models of the single-input-single-output (SISO) and multiple-input-multiple-output (MIMO) FLCs are analysed in terms of hardware implementation. Classis and alternative implementation of inference engines are presented. Direct Data Stream (DDS) FLC architecture is shown as an improved solution for high-speed, realtime control applications.

Condition Based Maintenance for light trucks

Army ground vehicles often operate in extremely severe environmental and battlefield conditions. There are challenges for the reliability of the military ground vehicle fleet, which need to be addressed. Condition Based Maintenance (CBM) allows maintenance to be performed based on evidence of need provided by reliability modeling and/or other enabling technologies, thus reducing maintenance costs and increasing vehicle availability. The architecture of the Intelligent Vehicle Health Management System (IVHMS) for light trucks is presented. A fuzzy model is developed to diagnose the axle fatigue of the vehicle. The extraction of the fuzzy rules is based upon expert knowledge and a linear damage model. Training data will be used to modify the membership functions and the fuzzy If-Then rules to improve the quality of the fuzzy model for fault diagnostics. The improvement of the fuzzy model will be carried out using re-clustering operation and membership function optimization.

Intelligent Decision Support System for Eye-Hand Coordination Assessment

Our goal is to develop an automated assessment and training procedure for children with eye-hand coordination problem. An automated assessment system is expected to reduce the burden and the associated cost of having a trained professional present at any assessment, or training session. The intelligent decision support system will be based upon a fuzzy automaton. By using qualitative (fuzzified) data from the previous test the system will make a decision on the complexity of the next test to be performed. A set of assessment tests, commonly used by occupational therapists, were chosen to implement the various functions using force, inertia and viscosity effects. A test bed will be used for these tasks that consists of a six-degree-of-freedom force-reflecting haptic interface device called PHANToM along with the GHOST SDK Software, and the Intelligent Decision Support System software

The virtual fuzzy state machine approach-a domain-independent fault detection and recovery method for object-based control systems

The current trend of using object based design for real time control systems has the implication that traditional state based fault detection and recovery methods cannot be used directly. This problem is even more difficult for domain independent fault detection and recovery since most such methods are based on a formal analysis of the global state set. The paper presents a domain independent fault isolation, detection and recovery method for object based control systems based on constraints of the object architecture. Variations of the control behavior from normal cases are detected using a fuzzy state machine approach.

Integration of an Intelligent Decision Support System and a Robotic Haptic Device for Eye-Hand Coordination Therapy

This paper is the continuation of a work presented at ICORR 05, in which the results of single-subjects studied suggested that the haptic robotic therapy proposed improved eye-hand coordination in children diagnosed with this problem, using a robotic mapping from a haptic user interface to a virtual environment. This paper presents the integration of the aforementioned system with an intelligent decision support system (IDSS) based on fuzzy-logic. Our goal is to develop an assessment and training procedure that will result in improving handwriting taking the advantage of the force feedback provided by the haptic device and the intelligence provided by the IDSS. We also incorporate the inertia and viscosity effects to decrease the tremor in the hand as well as to stimulate the muscles involved in the task of holding a pencil (known as facilitation technique in the Occupational Therapy field). The IDSS is based upon a fuzzy automaton. By using qualitative (fuzzified) data from the previous tests executed by the subject, the system will make a decision on the complexity of the next test to be performed. It is expected that this automated system will reduce the burden and the associated cost of having a trained professional present in all assessment/training sessions.