-
[show abstract]
[hide abstract]
ABSTRACT: We present methods to automatically identify and optimize controllers for large-scale complex dynamic systems; in particular, aircraft gas turbine engines. We show how the optimization of different elements within the overall controller can be addressed in an efficient fashion. These elements include local actuator gains, control modifiers, and control schedules. An evolutionary algorithm (EA) is utilized to realize multiobjective optimization on a local as well as a global level, depending on the optimization task at hand. The fitness function comprises performance metrics that incorporate stall margins, exhaust gas temperature, fan-speed tracking error, and local tracking errors. Less attention has been given in the literature to the application of optimization techniques to aircraft engine control systems design, where the controls design and optimization is performed using a full-order engine model and full control systems structures that do not oversimplify the inherent complexities in these highly complex nonlinear dynamic systems. This paper attempts to close that gap.
IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) 12/2005; · 2.01 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: A report is presented on the results of the second benchmark control problem prepared by the Benchmark Working Group of the IEEE Control Systems Society Technical Committee on computer-aided control system design (CACSD). The problem deals with a continuous-time missile autopilot design. The purpose of this benchmark is to provide a useful measure of some of the capabilities of computer-aided control system design packages. The problem requires time simulations, eigenvalue calculations, and frequency-response plots of relatively high-order linear systems. The problem is described, and the results submitted to date are summarized.< >
IEEE Control Systems Magazine 09/1990;
-
[show abstract]
[hide abstract]
ABSTRACT: A survey is presented of the environment, the hardware, and the system, user interface, and applications software that can make engineering workstations effective tools for the analysis and design of control systems. The hardware discussion covers processors, memory, networks, and diskless workstations. Operating systems, distributed file systems, and software for developing user interfaces are highlighted, along with the most widely used applications packages for control system engineering.< >
IEEE Control Systems Magazine 05/1990;
-
[show abstract]
[hide abstract]
ABSTRACT: The GE multidisciplinary expert-aided analysis and design (MEAD)
project, which involves the integration of several computer-aided
control engineering (CACE) packages under a supervisor which coordinates
the execution of these packages with a database manager, an expert
system, and an advanced user interface, is discussed. The principal
components are, in functional terms: a supervisor, which integrates the
underlying CACE packages and coordinates all activity within the GE MEAD
computer program (GMCP); an expert system shell and rule bases for
expert aiding of specific procedures to relieve the user from
unnecessary low-level detail; a database manager for tracking system
models that evolve over time along with associated results; and a user
interface that facilitates access to the CACE package capabilities by
permitting the user to work in several modalities, i.e. menu/forms
style, using GE MEAD commands, the core packages' native commands, or
the GE MEAD macro facility. The operation of the GMCP, including the
user interface, expert system, and database manager, is illustrated by
examples
Computer-Aided Control System Design, 1989., IEEE Control Systems Society Workshop on; 01/1990
-
[show abstract]
[hide abstract]
ABSTRACT: Results submitted for the continuous-time missile autopilot problem that was prepared by P. Hawley and T. Stevens (1986) are reported. The problem was released by the Benchmark Working Group of the IEEE Committee on Computer-Aided Control System Design (CACSD) to the control community at large in October 1987. The problem statement is described and the results submitted to date are summarized. This problem requires time simulations, pole and zero calculations, and frequency response plots for a linear, continuous-time system of relatively high order, specified as an interconnection of first- and second-order blocks. The problem comes in three levels of complexity, involving models having 13, 42, and 74 state variables. Plans for future benchmark problems are included
Aerospace and Electronics Conference, 1988. NAECON 1988., Proceedings of the IEEE 1988 National; 06/1988
-
[show abstract]
[hide abstract]
ABSTRACT: The authors discuss the application of expert systems programming techniques to the design of lead-lag compensators for a linear, single-input/single-output, continuous-time plant. A design method based on first adjusting the high-frequency response with lead and constant-gain compensators followed by adjusting the low-frequency response with lag compensators has been developed. This design heuristic is presented and its ability to achieve specifications for a range of different plants is discussed. The heuristic has been implemented using the production rule knowledge representation; examples of production rules are given and their use is discussed. Inference-engine capabilities and extensions to a conventional analysis and design package, required to implement this automatic control system design method, are also outlined.
Control Theory and Applications, IEE Proceedings D [see also IEE Proceedings-Control Theory and Applications] 06/1987;
-
Artificial Intelligence Applications, CAIA 1985, The Engineering of Knowledge-Based Systems, Proceedings of the Second Conference, Miami Beach, Florida, USA, December 11-13, 1985; 01/1985
-
[show abstract]
[hide abstract]
ABSTRACT: We propose the development of a rule-based expert system to create a third-generation man/machine environment for computer-aided control engineering (CACE). The breadth of the CACE problem is of particular concern, and provides a major motivation for the use of artificial intelligence. This approach promises to provide a high-level design environment that is powerful, supportive, flexible, broad in scope, and readily accessible to nonexpert users. We focus primarily on the high-level requirements for an improved CACE environment, and on the expert system concepts and structures that we have conceived to fulfill these needs. Our chief goal is to determine what artificial intelligence has to contribute to such an environment, and to provide as definite and credible a vision of an expert system for CACE as possible. The main product of this effort is an expert system architecture for CACE.
Proceedings of the IEEE 01/1985; · 6.81 Impact Factor
