8 research outputs found
New insights for applications of Kreisselmeier's structure in robust and fault tolerant control
This paper addresses a two degree of freedom structure discussed by Kreisselmeier for the SISO case in 1999. The discussion herein considers a MIMO setting, and aims at the use of this control topology for robust and fault tolerant control. It is also shown how design barriers can be obtained for robust I/O transfer behavior assignment and robustness evaluation schemes can be devised which allow for the quantitative valuation of I/O transfer behavior degradation in the presence of plant model uncertainty. The concepts and techniques are illustrated and assessed using an in-flight simulation problem
Identification of two-time scaled systems using prefilters.
This paper deals with the identification of two-time scale linear dynamic systems, which are an important class of multiscale systems. Classical identification processes may fail to yield accurate parameters for systems of this class and, for this reason, the authors propose two different techniques to estimate the system parameters. The first technique utilizes two prefilters that are iteratively tuned. The second one considers wavelet filters that are tuned based on the results of the first iterative algorithm. Identification and analysis results for a dynamical aircraft model are shown to demonstrate the algorithm’s performance
Zero Assignment in a Scalar Control System Transfer-Function Exploiting Linear Dynamic Feedback Structures
An algorithm for zero assignment in a scalar control system transfer-function exploiting an already designed generic linear dynamic feedback structure is derived. The algorithm is based on Faddejews method for adjugate matrix determination. The use of the algorithm is illustrated by a simple servomechanism example with a specified dropback value
Robust controllers with guaranteed implementability through multiobjective optimisation-based design
This contribution discusses a novel approach to design of robust controllers explicitly taking into account bandwidth restrictions of onboard computer implemantation. This is achieved by online modal controller reduction during the synthesis-tuning phase in a multiobjective-optimization design environment. This is different to common approaches where implementability issues of high-order controllers are deferred to a separate post-design step. The approach is applied to lateral flight control in the HIRM (High Incidence Research Model) Design Challenge problem defined by GARTEUR
Multiobjective Target Feedback Loop / Loop Transfer Recovery (TFL/LTR) design with application to aircraft lateral control in high incidence regime
Target Feedback Loop / Loop Transfer Recovery (TFL/LTR) synthesis and multiobjective optimization are combined to design robust and well performing controllers in a most general sense. A TFL/LTR synthesis based on quadratic stabilization is used to efficiently synthesize robustly stabilizing controllers. Multiobjective optimization is used to tune synthesis parameters for which the TFL/LTR controller yields good performance in addition to robust stability. The technique is demonstrated in the design of a lateral controller for a high performance aircraft in high incidence regime
Efficient, nearly orthogonal-and-balanced, mixed designs: an effective way to conduct trade-off analyses via simulation
The article of record as published may be located at http://dx.doi.org/10.1057/jos.2013.14SEED Center PaperDesigned experiments are powerful methodologies for gaining insights into the behaviour of complex simulation models. In recent
years, many new designs have been created to address the large number of factors and complex response surfaces that often arise in
simulation studies, but handling discrete-valued or qualitative factors remains problematic. We propose a framework for generating
a design, of speci!ed size, that is nearly orthogonal and nearly balanced for any mix of factor types (categorical, numerical discrete,
and numerical continuous) and mix of factor levels. These new designs allow decision makers structured methods for trade-off
analyses in situations that are not necessarily amenable to other methods for choosing alternatives, such as simulation optimization
or ranking and selection approaches. These new designs also compare well to existing approaches for constructing custom designs
for smaller experiments, and may also be of interest for exploring computer models in domains where fewer factors are involved