Publications

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Multi-phase, pseudospectral optimization is employed in a variety of applications, but many of the world-class optimization libraries are closed-source. In this paper we formulate an open-source, object-oriented framework for dynamic optimization using the Pyomo modeling language. This strategy supports the reuse of common code for rapid, error-free model development. Flexibility of our framework is demonstrated on a series of dynamic optimization problems, including multi-phase trajectory optimization using highly accurate pseudospectral methods and controller gain optimization in the presence of stability margin constraints. We employ numerical procedures to improve convergence rates and solution accuracy. We validate our framework using GPOPS-II, a commercial, MATLAB-based optimization program, for a vehicle ascent problem. The trajectory results show close alignment with this state-of-the-art optimization suite.

Pyomo and Dakota are openly available software packages developed by Sandia National Labs. In this tutorial, methods for automating the optimization of controller parameters for a nonlinear cart-pole system are presented. Two approaches are described and demonstrated on the cart-pole example problem for tuning a linear quadratic regulator and also a partial feedback linearization controller. First the problem is formulated as a pseudospectral optimization problem under an open box methodology utilizing Pyomo, where the plant model is fully known to the optimizer. In the next approach, a black-box approach utilizing Dakota in concert with a MATLAB or Simulink plant model is discussed, where the plant model is unknown to the optimizer. A comparison of the two approaches provides the end user the advantages and shortcomings of each method in order to pick the right tool for their problem. We find that complex system models and objectives are easily incorporated in the Dakota-based approach with minimal setup time, while the Pyomo-based approach provides rapid solutions once the system model has been developed.

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This report summarizes the accomplishments of the Laboratory Directed Research and Development (LDRD) project 26546 at Sandia, during the period FY01 through FY03. The project team visited four DoD depots that support extensive aircraft maintenance in order to understand critical needs for automation, and to identify maintenance processes for potential automation or integration opportunities. From the visits, the team identified technology needs and application issues, as well as non-technical drivers that influence the application of automation in depot maintenance of aircraft. Software tools for automation facility design analysis were developed, improved, extended, and integrated to encompass greater breadth for eventual application as a generalized design tool. The design tools for automated path planning and path generation have been enhanced to incorporate those complex robot systems with redundant joint configurations, which are likely candidate designs for a complex aircraft maintenance facility. A prototype force-controlled actively compliant end-effector was designed and developed based on a parallel kinematic mechanism design. This device was developed for demonstration of surface finishing, one of many in-contact operations performed during aircraft maintenance. This end-effector tool was positioned along the workpiece by a robot manipulator, programmed for operation by the automated planning tools integrated for this project. Together, the hardware and software tools demonstrate many of the technologies required for flexible automation in a maintenance facility.