Author: Publisher:
ISBN:
Category : Automatic control
Languages : en
Pages : 508
Book Description
Fifth NASA/DoD Controls-Structures Interaction Technology Conference
Author: AFHRL-TR.
Author: Air Force Human Resources LaboratoryPublisher:
ISBN:
Category : Aeronautics, Military
Languages : en
Pages : 532
Book Description
Identification in Automatic Control Systems
Author: Scientific and Technical Information Output of the Langley Research Center for Calendar Year 1980
Author: Minimax Approaches to Robust Model Predictive Control
Author: Johan LöfbergPublisher: Linköping University Electronic Press
ISBN: 9173736228
Category : Predictive control
Languages : en
Pages : 212
Book Description
Controlling a system with control and state constraints is one of the most important problems in control theory, but also one of the most challenging. Another important but just as demanding topic is robustness against uncertainties in a controlled system. One of the most successful approaches, both in theory and practice, to control constrained systems is model predictive control (MPC). The basic idea in MPC is to repeatedly solve optimization problems on-line to find an optimal input to the controlled system. In recent years, much effort has been spent to incorporate the robustness problem into this framework. The main part of the thesis revolves around minimax formulations of MPC for uncertain constrained linear discrete-time systems. A minimax strategy in MPC means that worst-case performance with respect to uncertainties is optimized. Unfortunately, many minimax MPC formulations yield intractable optimization problems with exponential complexity. Minimax algorithms for a number of uncertainty models are derived in the thesis. These include systems with bounded external additive disturbances, systems with uncertain gain, and systems described with linear fractional transformations. The central theme in the different algorithms is semidefinite relaxations. This means that the minimax problems are written as uncertain semidefinite programs, and then conservatively approximated using robust optimization theory. The result is an optimization problem with polynomial complexity. The use of semidefinite relaxations enables a framework that allows extensions of the basic algorithms, such as joint minimax control and estimation, and approx- imation of closed-loop minimax MPC using a convex programming framework. Additional topics include development of an efficient optimization algorithm to solve the resulting semidefinite programs and connections between deterministic minimax MPC and stochastic risk-sensitive control. The remaining part of the thesis is devoted to stability issues in MPC for continuous-time nonlinear unconstrained systems. While stability of MPC for un-constrained linear systems essentially is solved with the linear quadratic controller, no such simple solution exists in the nonlinear case. It is shown how tools from modern nonlinear control theory can be used to synthesize finite horizon MPC controllers with guaranteed stability, and more importantly, how some of the tech- nical assumptions in the literature can be dispensed with by using a slightly more complex controller.
Index to Conferences Relating to Nuclear Science
Author: Willie E. ClarkPublisher:
ISBN:
Category : Nuclear physics
Languages : en
Pages : 220
Book Description
Project Independence: Denver, Colorado, Aug. 6-9, 1974
Author: Project Independence Blueprint
Author: United States. Federal Energy AdministrationPublisher:
ISBN:
Category : Energy policy
Languages : en
Pages : 252
Book Description
Applied Mechanics Reviews
Author: Project Independence Blue Print
Author: United States. Federal Energy AdministrationPublisher:
ISBN:
Category : Boston (Mass.)
Languages : en
Pages : 252
Book Description