Everything about Optimal control
Mathematical way of attaining a desired output from a dynamic system
Optimal control theory is a branch of control theory that deals with finding a control for a dynamical system over a period of time such that an objective function is optimized. It has numerous applications in science, engineering and operations research. For example, the dynamical system might be a spacecraft with controls corresponding to rocket thrusters, and the objective might be to reach the Moon with minimum fuel expenditure. Or the dynamical system could be a nation's economy, with the objective to minimize unemployment; the controls in this case could be fiscal and monetary policy. A dynamical system may also be introduced to embed operations research problems within the framework of optimal control theory. Wikipedia →
🧠Start here: a 6-step reading path
- Read the overview: Optimal controlA 5-minute orientation
- Skim a recent paper: Quantum optimal control in quantum technologies. Strategic report on current status, visions and goals for research in EuropeInfluential work since 2022
- Pick up a classic book: Nonlinear Approaches In Engineering ApplicationsThe most-reprinted book on the subject
- Read the landmark paper: Constrained model predictive control: Stability and optimalityCited 7,500 times
- Go sideways: Hamiltonian (control theory)A closely related topic
- Go sideways: Linear–quadratic regulatorA closely related topic
đź“– Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Constrained model predictive control: Stability and optimality
Linear Optimal Control
Optimal Control of Boolean Control Networks
Approximation Methods in Optimal Control I. Sub-optimal Controlâ€
Optimal control
Optimal, near-optimal, and robust epidemic control
Optimal stochastic control
Fuzzy optimal control
🆕 Influential since 2022
đź“š Books worth reading
Nonlinear Approaches In Engineering ApplicationsLiming Dai · 2011
Combinatorial OptimizationBernhard Korte, Jens Vygen · 2005
Optimal controlFrank L. Lewis · 1986
Loopshaping Robust ControlPhilippe Feyel · 2013
Optimal control of ODEs and DAEsMatthias Gerdts · 2011
Representation and control of infinite dimensional systemsAlain Bensoussan, Giuseppe Da Prato · 1992
Deterministic and Stochastic Optimal ControlWendell H. Fleming, Raymond W. Rishel · 1975
The optimistic childMartin Elias Pete Seligman · 1995
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
đź”— Related topics
- Hamiltonian (control theory) The Hamiltonian is a function used to solve a problem of optimal control for a dynamical system. It can be understood as an instantaneous increment of…
- Linear–quadratic regulator The theory of optimal control is concerned with operating a dynamic system at minimum cost. The case where the system dynamics are described by a set of…
- Broyden–Fletcher–Goldfarb–Shanno algorithm In numerical optimization, the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm is an iterative method for solving unconstrained nonlinear optimization…
- Levenberg–Marquardt algorithm In mathematics and computing, the Levenberg–Marquardt algorithm (LMA or just LM), also known as the damped least-squares (DLS) method, is used to solve…
- Fictitious domain method In numerical analysis, the fictitious domain method (FD) is a numerical technique designed to solve partial differential equations on complex geometries…
- Karush–Kuhn–Tucker conditions In mathematical optimization, the Karush–Kuhn–Tucker (KKT) conditions, also known as the Kuhn–Tucker conditions, are first derivative tests (sometimes…
- Crank–Nicolson method In numerical analysis, the Crank–Nicolson method is a finite difference method used for numerically solving the heat equation and similar partial differential…
- Sequential quadratic programming Sequential quadratic programming (SQP) is an iterative method for constrained nonlinear optimization, also known as Lagrange-Newton method. SQP methods…