다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

An introduction to heat transfer

This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

Adaptive Control

System Identification I

Design of physical systems and associated control systems are coupled tasks; design methods that manage this interaction explicitly can produce system-optimal designs, whereas conventional sequential processes may not. Here we explore a new technique for combined physical system and control design (co-design) based on a simultaneous dynamic optimization approach known as direct transcription, which transforms infinite-dimensional control design problems into finite dimensional nonlinear programming problems. While direct transcription problem dimension is often large, sparse problem structures and fine-grained parallelism (among other advantageous properties) can be exploited to yield computationally efficient implementations. Extension of direct transcription to co-design gives rise to a new problem structures and new challenges. Here we illustrate direct transcription for co-design using a new automotive active suspension design example developed specifically for testing co-design methods. This example builds on prior active suspension problems by incorporating a more realistic physical design component that includes independent design variables and a broad set of physical design constraints, while maintaining linearity of the associated differential equations.© 2011 ASME

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Co-Design of an Active Suspension Using Simultaneous Dynamic Optimization

Dynamic engineering systems are playing an increasingly important role in society, especially as active and autonomous dynamic systems become more mature and prevalent across a variety of domains. Successful design of complex dynamic systems requires multidisciplinary analysis and design techniques. While multidisciplinary design optimization has been used successfully for the development of many dynamic systems, the established multidisciplinary design optimization formulations were developed around fundamentally static system models. General multidisciplinary design optimization approaches that address the specific needs of dynamic system design are still lacking. In this article, the use of multidisciplinary design optimization for dynamic system design is reviewed, associated challenges are identified, related efforts such as optimal control are discussed, and a vision for fully integrated design approaches is presented. Finally, a set of exciting new directions that provide an opportunity for fundame...

Multidisciplinary design optimization of dynamic engineering systems

The solution of complex system design problems using decomposition-based optimization methods requires determination of appropriate problem partitioning and coordination strategies. Previous optimal partitioning techniques have not addressed the coordination issue explicitly. This article presents a formal approach to simultaneous partitioning and coordination strategy decisions that can provide insights on whether a decomposition-based method will be effective for a given problem. Pareto-optimal solutions are generated to quantify tradeoffs between the sizes of subproblems and coordination problems as measures of the computational costs resulting from different partitioning and coordination strategies. Promising preliminary results with small test problems are presented. The approach is illustrated on an electric water pump design problem.

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Optimal Partitioning and Coordination Decisions in Decomposition-Based Design Optimization

Optimal Partitioning and Coordination Decisions in Decomposition-Based Design

1 Abstract The methods of analytical target cascading (ATC) and collaborative optimization (CO) are studied with respect to their intended use and applicability. ATC was initially developed as a product development tool, while CO evolved from eorts to coordinate multidisciplinary analyses using a multidisciplinary design optimization (MDO) formulation. ATC and CO are used typically to solve object-based and discipline-based decomposed system optimization problems, respectively. Their mathematical formulations appear to be similar although they were developed with dierent motivations. The article defines and compares terminologies for each approach and shows that each has unique applicability and solution process. Two new analytical example problems are employed to illustrate the distinctions between ATC and CO. The first example elucidates how each method can be used to solve the same design problem. The second example uses a new optimization formulation, nested ATC-MDO, to illustrate their complementary nature. In this formulation a system is partitioned by object, and objects are partitioned by discipline. ATC coordinates the design of system elements and an MDO method, such as CO, coordinates the multidisciplinary design of an element. The formulation maps well to organizational matrix structures. The overall study demonstrates the benefits of using complementary solution strategies in solving complex system optimization problems.

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James T. Allison

Papers

Co-Design of an Active Suspension Using Simultaneous Dynamic Optimization

Multidisciplinary design optimization of dynamic engineering systems

Optimal Partitioning and Coordination Decisions in Decomposition-Based Design Optimization

Optimal Partitioning and Coordination Decisions in Decomposition-Based Design

On the Use of Analytical Target Cascading and Collaborative Optimization for Complex System Design