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

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 (MDO) has been used successfully for the development of many dynamic systems, the established MDO formulations were developed around fundamentally static system models. We still lack general MDO approaches that address the specific needs of dynamic system design. In this article we review the use of MDO for dynamic system design, identify associated challenges, discuss related efforts such as optimal control, and present a vision for fully integrated design approaches. Finally, we lay out a set of exciting new directions that provide an opportunity for fundamental work in MDO.

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This paper gives a bibliographical review of the finite element methods (FEMs) applied to the analysis and simulation of smart materials and structures. The bibliography is an addendum to the Smart materials and structures—a finite-element approach: a bibliography (1986–1997) published in 1998 Modelling Simul. Mater. Sci. Eng. 6 293–334. The added bibliography at the end of this article contains 977 references to papers and conference proceedings on the subject that were published in 1997–2002. The following topics are included: smart materials, smart components/structures, smart sensors and actuators, and controlled structures technology.

Smart materials and structures—a finite element approach—an addendum: a bibliography (1997–2002)

Optimal vibration control and co-design of very flexible actuated structures

A method of motion control as well as shape optimization is proposed for the preliminary design of a suitlike flexible arm, which is composed of some variable-length and fixed-length beams. The large deformation, variable geometry and motion of the flexible structure are calculated by dynamic finite element analysis (FEA) using the step by step time integration method. A neural-networks-inverse-model, which learns nonlinear behaviour of the flexible structure, has been applied for the motion control as an inverse model of the flexible arm. For this geometrically nonlinear structure and time response problem, the optimum shape of the cross-section has been calculated under constraints of stress, stiffness and minimum weight with FEA and sensitivity analysis combined with fuzzy rules. This method has been applied for the design of a flexible arm, which simulates a process of lifting a human body and moving it. The calculated optimum shape has a much higher stiffness with decrease in weight in comparison with the initial shape. Moreover, the calculated motion agrees well with the one aimed for and the flexible arm reduces the impact force.

K. Kawashima

Papers

Motion control and shape optimization of a suitlike flexible arm