The evaluation and application of chemically regenerative atmospheric control systems.

" Report ; no. TDR-269 (4560-50)-2)."

The air quality and economic implications of supplementary control systems in Illinois /

Bibliography: p. 90-92.

Organizational maintenance manual for cab, armament, sighting, and fire control, elevating and traversing systems and associated components : howitzer, medium, self-propelled, 155mm, M109A2 (2350-01-031-0586), M109A3 (2350-01-031-8851).

"June 1986."

Organizational maintenance manual for cab, armament, sighting, and fire control, elevating and traversing systems and associated components : howitzer, medium, self-propelled, 155mm, M109A2 (2350-01-031-0586), M109A3 (2350-01-031-8851).

"30 June 1986."

Unit maintenance repair parts and special tools list for cab, armament, sighting and fire control, elevating and traversing systems, and associated components, howitzer, medium, self-propelled, 155mm, M109A2 (NSN 2350-01-031-0586), M109A3 (NSN 2350-01-031-8851) ...

"November 1989."

Direct support and general support maintenance repair parts and special tools list ... for cab, armament, sighting and fire control, elevating and traversing systems, and associated components, howitzer, medium, self-propelled, 155mm, M109A2 (NSN 2350-01-031-0586), M109A3 (NSN 2350-01-031-8851) ...

"December 1989."

Diversion and corridor control systems in Western Europe /

Preprint of IRF report, issued June 1977.

Control of aircraft and missile powerplants; an introduction to the analysis and design of engine control systems

Mode of access: Internet.

A novel approach to modelling and exploiting uncertainty in stochastic control systems

We consider an inversion-based neurocontroller for solving control problems of uncertain nonlinear systems. Classical approaches do not use uncertainty information in the neural network models. In this paper we show how we can exploit knowledge of this uncertainty to our advantage by developing a novel robust inverse control method. Simulations on a nonlinear uncertain second order system illustrate the approach.

Conditional distribution modeling for estimating and exploiting uncertainty in control systems

This paper presents a general methodology for estimating and incorporating uncertainty in the controller and forward models for noisy nonlinear control problems. Conditional distribution modeling in a neural network context is used to estimate uncertainty around the prediction of neural network outputs. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localize the possible control solutions to consider. A nonlinear multivariable system with different delays between the input-output pairs is used to demonstrate the successful application of the developed control algorithm. The proposed method is suitable for redundant control systems and allows us to model strongly non Gaussian distributions of control signal as well as processes with hysteresis.

A methodology for analysis and control of discrete event dynamic systems

The rapid developments in computer technology have resulted in a widespread use of discrete event dynamic systems (DEDSs). This type of system is complex because it exhibits properties such as concurrency, conflict and non-determinism. It is therefore important to model and analyse such systems before implementation to ensure safe, deadlock free and optimal operation. This thesis investigates current modelling techniques and describes Petri net theory in more detail. It reviews top down, bottom up and hybrid Petri net synthesis techniques that are used to model large systems and introduces on object oriented methodology to enable modelling of larger and more complex systems. Designs obtained by this methodology are modular, easy to understand and allow re-use of designs. Control is the next logical step in the design process. This thesis reviews recent developments in control DEDSs and investigates the use of Petri nets in the design of supervisory controllers. The scheduling of exclusive use of resources is investigated and an efficient Petri net based scheduling algorithm is designed and a re-configurable controller is proposed. To enable the analysis and control of large and complex DEDSs, an object oriented C++ software tool kit was developed and used to implement a Petri net analysis tool, Petri net scheduling and control algorithms. Finally, the methodology was applied to two industrial DEDSs: a prototype can sorting machine developed by Eurotherm Controls Ltd., and a semiconductor testing plant belonging to SGS Thomson Microelectronics Ltd.