A new conceptual framework for integrating decision-making and control as it pertains to hierarchical discrete-event systems has been formulated. The conceptualized formulation relies upon the definition of a coordinated object that can be recursively employed to describe the desired hierarchy. New object-oriented simulation tools are also being developed to model the coordination hierarchy. To address the unique considerations pertaining to real-time decision making and control, a hierarchical subsystem coordinator has been formulated for inclusion within each coordinated object. The essential mechanisms to coordinate the distributed decision making and control are now being explored.

Using a new object-oriented simulation framework, a distributed software emulator is being developed for the rapid access to manufactured parts (RAMP) flexible manufacturing systems (FMS). This class of FMSs was developed under the U.S. Department of Defense Manufacturing Technology Program to economically manufacture replacement parts in small lot sizes. These FMSs are currently not achieving the desired equipment utilization and production throughput. This effort will attempt to analyze the interactions among the more than 70 controllers that manage the system in order to develop improved control strategies. The project will eventually seek to produce a real-time scheduler for the RAMP FMSs.

This research considers control scheduling and communication/control/sensing issues in the regulation of lateral and longitudinal motion of vehicles participating in high flow density, multilane traffic. The goal is to survey present approaches to the problem and develop control strategies and control schedules to enable lane maneuvers and entrance into/exit from traffic, when traffic in each lane is moving at different target velocities.

The need to continuously operate technical systems in the presence of structural changes in the system, damage to parts of the system, or failures in the control system has long been recognized as an important issue in system design and operational control. The project emphasis is on the development of systematic procedures for the design of fault-tolerant control systems. The focus is on design of reliable control systems using redundant sensors and actuators, on fault assessment methods, reconfiguration procedures and development of controllers based on coarse partitioning of the state space, using methods based on variable structure control, cell-to-cell mapping, and state space partitioning.

Hydrogenerator governors are designed with predetermined rotational inertias and conduit dimensions for maximum acceptable off-speeds (speed deviations from reference). However, this parameter selection may not be favourable for stable operation and satisfactory small signal level performance when governing isolated loads. Poorly governed plants operating in interconnected systems degrade the overall stability. This work develops a graphical method to determine expected performance and stability characteristics based on inertia and conduit sizing decisions. It is directed toward mechanical and civil engineers in volved in the design and associated economics of plant layouts.

A number of published works deal with governor tuning for speed control of hydrogenerators. This work is based on the hypothesis that some system parameters are not known at the design stage. It develops a graph that can be used to predict optimum proportional and integral gains based on four parameters: the time constants of the water column and the rotor inertia and the self-regulation constants of the turbine and the loading grid. The pole cancellation method of design is used and the results are posed in an easy-to-use format not requiring the solution of systems of equations.

This project investigates an identification procedure for a hydrogenerator plant using an adaptive technique. The procedure operates on field data consisting of sampled gates position and electrical frequency. The procedure adapts to ongoing plant changes by continuously updating the identification results. It is shown that the adaptive technique, in this case genetic algorithm based, was capable of identifying the hydrogenerator system and following plant parameter changes while the plant operated under conditions of sufficient frequency excursions. These conditions applied to off-line and isolated network operation where effective control is critical.

Many techniques exist for developing optimal controllers. This work investigates genetic algorithms as a means of finding optimal solutions over a parameter space. In particular, the genetic algorithm is applied to optimal tuning of a governor for a hydrogenerator plant. Analog and digital simulation methods are compared for use in conjunction with the genetic algorithm optimization process. It is shown that analog plant simulation provides advantages in speed over digital plant simulation. This speed advantage makes application of the genetic algorithm in an actual plant environment feasible. Furthermore, the genetic algorithm is shown to possess the ability to reject plant noise and other system anomalies in its search for optimizing solutions.

This research investigates an optimal strategy for controlling the speed response of Kaplan hydrogenerating systems to decreases in load. Typically, primary control gates restrict and redirect water through the turbine to stabilize and transfer the system to operating point demand. The adjustable turbine blade angle is used to return to maximum operating efficiency at the new load level. The overspeed reduction is limited by the conduit's ability to withstand the overpressure caused by the flow restriction at the turbine. A control scheme using gates and blades simultaneously and independently is developed.

We concern ourselves with 11 broad research issues in the modeling, analysis, control, and performance evaluation of Discrete Event Dynamic Systems (DEDS). Research in modeling and analysis concerns the identification of modeling paradigms suitable for supervisory control of DEDS. The control of DEDS concerns the archetypal problem of elimination of deadlocks. The performance analysis of DEDS concerns an approach that will permit a system designer to modify automatically discrete event simulation programs that only estimate performance so as to efficiently obtain the sensitivity of the performance. This sensitivity information can be used toward system optimization using stochastic approximation techniques.