This project has four main objectives: i) to identify efficient multiplier update implementations for large scale discrete-time control problems with state and control variable constraints, and for finite-difference approximations to analogous continuous-time problems; ii) to extend existing convergence analyses to problems with inequality constraints that have infinite-dimensional range spaces; iii) to develop infinite-dimensional extensions of the Kuhn-Tucker sufficient conditions needed in convergence analyses for the subject algorithms and other constrained minimization methods as well; iv) to investigate quasi-Newton recursions that produce scaling operators which automatically possess well-behaved global and asymptotic properties. The algorithms investigated in this project are related to significant applications in the operation of aircraft and spacecraft, electrical power networks, chemical and nuclear reactors, robot manipulators, and ecosystems.
