Neuro-Control Design: Optimization Aspects

1997 ◽  
pp. 259-288 ◽  
Author(s):  
H. Ted Su ◽  
Tariq Samad
Keyword(s):  
Design Optimization ◽  
Control Design

Control, Design and Error Variables in Decomposition of Design Optimization Problems

2002 ◽  
Author(s):  
Jose Martinez Escanaverino ◽  
Jose A. Llamos Soriz ◽  
Alejandra Garcia Toll ◽  
Tania Ortiz Cardenas
Keyword(s):  
Design Optimization ◽  
Design Automation ◽  
Optimization Problems ◽  
Real Life ◽  
Control Design ◽  
Maximum Matching ◽  
Specific Knowledge ◽  
Graph Theoretic ◽  
Domain Specific ◽  
Domain Specific Knowledge

A method for the rational choice of control, design and error variables in optimization problems is devised, based on the reduction of the maximum matching of the problem graph to the Dulmage-Mendelsohn canonical form. The method allows the designer to find with minimum effort appropriate sets of control, design and error variables that lead to an ultimate decomposition in design optimization problems of any dimension. In design automation, this procedure is useful as a rationale to plan manual interventions, where designers guide the process according to domain-specific knowledge. The proposed technique is rigorous and intuitive, thanks to the application of sound graph-theoretic concepts. A real-life example of mechanical engineering design shows the applicability of the method.

Parametric Controllers in Simultaneous Process and Control Design Optimization

2003 ◽  
Vol 42 (20) ◽  
pp. 4545-4563 ◽  
Author(s):  
Vassilis Sakizlis ◽  
John D. Perkins ◽  
Efstratios N. Pistikopoulos
Keyword(s):  
Design Optimization ◽  
Control Design ◽  
Simultaneous Process ◽  
And Control

A Comparative Study of Formulations and Algorithms for Reliability-Based Co-Design Problems

2019 ◽  
Vol 142 (3) ◽  
Author(s):  
Tonghui Cui ◽  
James T. Allison ◽  
Pingfeng Wang
Keyword(s):  
Comparative Study ◽  
Design Optimization ◽  
System Design ◽  
Design Problem ◽  
Control Design ◽  
Engineering System ◽  
Design Strategies ◽  
Parameter Uncertainties ◽  
Horizontal Axis Wind Turbine ◽  
And Control

Abstract While integrated physical and control system co-design has been demonstrated successfully on several engineering system design applications, it has been primarily applied in a deterministic manner without considering uncertainties. An opportunity exists to study non-deterministic co-design strategies, taking into account various uncertainties in an integrated co-design framework. Reliability-based design optimization (RBDO) is one such method that can be used to ensure an optimized system design being obtained that satisfies all reliability constraints considering particular system uncertainties. While significant advancements have been made in co-design and RBDO separately, little is known about methods where reliability-based dynamic system design and control design optimization are considered jointly. In this article, a comparative study of the formulations and algorithms for reliability-based co-design is conducted, where the co-design problem is integrated with the RBDO framework to yield solutions consisting of an optimal system design and the corresponding control trajectory that satisfy all reliability constraints in the presence of parameter uncertainties. The presented study aims to lay the groundwork for the reliability-based co-design problem by providing a comparison of potential design formulations and problem–solving strategies. Specific problem formulations and probability analysis algorithms are compared using two numerical examples. In addition, the practical efficacy of the reliability-based co-design methodology is demonstrated via a horizontal-axis wind turbine structure and control design problem.

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