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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,051 papers · 148 categories

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1122 · Jan 202219922001200920182026
15 results for state-feedback

This work refines imitation learning to approximate optimal state-feedback policies for a quadcopter model.

problem Designing optimal control policies for complex systems like quadcopters.
method Supervised imitation learning using deep neural networks trained on optimal trajectories.
result Deep neural networks can approximate optimal state-feedback policies with high accuracy, even with two layers.

Paper shows how to linearize flat systems with two inputs.

problem Linearizing flat nonlinear control systems with two inputs.
method Using prolongations of a control, the system can be made static feedback linearizable.
result A tracking control can be designed without requiring measurements of a generalized Brunovsky state.

The paper explores how ReLU DNNs can represent MPC policies and vice versa.

problem Representing MPC policies as ReLU DNNs and vice versa.
method Developed an approximate method for identifying input-space in ReLU nets resulting in PWA functions over polyhedral regions. Studied inverse multiparametric linear or quadratic programs for reconstruction of constraints and cost functions given a PWA function.
result Identification and representation of MPC policies as ReLU DNNs and vice versa.

The paper solves a complex control problem with stochastic elements and switching conditions.

problem Non-homogeneous stochastic LQ control with regime switching and random coefficients.
method Explicit optimal control and value obtained through two systems of backward stochastic differential equations (BSDEs). Existence and uniqueness of solutions proved using BMO martingales and contraction mapping method.
result Explicit optimal state feedback control and optimal value derived for the problem.

The study sets limits on how well systems can be controlled adaptively.

problem Learning to control unknown linear Gaussian systems with quadratic costs.
method Combining ideas from experiment design, estimation theory, and perturbation bounds of information matrices.
result Regret lower bounds of the order of T\sqrt{T} in the time horizon TT accurately capture control-theoretic parameters.

Wearable devices have the potential to enhance sports performance, yet they are not fulfilling this promise. Our previous studies with 6 professional tennis coaches and 20 players indicate that this could be due the lack of psychological or mental state feedback, which the coaches claim to provide. Towards this end, we…

2018-03-26abs ↗pdf ↗

Develops variational framework for LQG risk-sensitive MFGs with major-minor interactions.

problem Risk-sensitive optimal control in LQG systems with major-minor interactions.
method Variational approach, nonlinear necessary and sufficient condition of optimality, equivalent risk-neutral measure, Markovian closed-loop best-response strategies.
result Derives optimal control strategies for LQG risk-sensitive MFGs with major-minor interactions, establishing Nash and ε\varepsilon-Nash equilibria.