Model predictive control: theory and practice—a survey
Automatica (Journal of IFAC)
Journal of Computational and Applied Mathematics - Special issue on SQP-based direct discretization methods for practical optimal control problems
SIAM Journal on Optimization
A nonsmooth Newton's method for control-state constrained optimal control problems
Mathematics and Computers in Simulation
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Survey Constrained model predictive control: Stability and optimality
Automatica (Journal of IFAC)
Minimizing control variation in nonlinear optimal control
Automatica (Journal of IFAC)
Optimal leader allocation in UAV formation pairs ensuring cooperation
Automatica (Journal of IFAC)
Hi-index | 22.15 |
We consider a class of finite time horizon optimal control problems for continuous time linear systems with a convex cost, convex state constraints and non-convex control constraints. We propose a convex relaxation of the non-convex control constraints, and prove that the optimal solution of the relaxed problem is also an optimal solution for the original problem, which is referred to as the lossless convexification of the optimal control problem. The lossless convexification enables the use of interior point methods of convex optimization to obtain globally optimal solutions of the original non-convex optimal control problem. The solution approach is demonstrated on a number of planetary soft landing optimal control problems.