LTI
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
Notes on data-driven output-feedback control of linear MIMO systems
Announce Type: replace Abstract: Recent works have approached the data-driven design of dynamic output-feedback controllers for discrete-time LTI systems by constructing non-minimal state vectors composed of past inputs and outputs. Depending on the system's complexity (order $n$, lag $\ell$ and number of outputs $p$), it was observed in several works that such an approach presents significant limitations. In particular, many works require to restrict the class of LTI systems to those...
CART: Context-Anchored Recurrent Transformer -- A Parameter-Efficient Architecture with Learned Stability
arXiv:2606.01495v2 Announce Type: replace Abstract: We present CART (Context-Anchored Recurrent Transformer), a parameter-efficient language model that reuses a single shared core block R times across depth. Unlike prior looped transformers that recompute key-value tensors at every iteration, CART computes K and V once from a multi-layer prelude and has the recurrent core cross-attend to those frozen tensors via multi-head latent attention. A learned Linear Time-Invariant (LTI) gate keeps...
Synthesizing Neural Network Controllers with Closed-Loop Dissipativity Guarantees
arXiv:2404.07373v2 Announce Type: replace Abstract: This paper presents a method to synthesize neural network controllers to maximize reward subject to the hard constraint that the feedback system of plant and controller be dissipative, certifying requirements such as stability and $L_2$ gain bounds. It considers nonlinear and uncertain plants, modeled as the interconnection of a linear time-invariant (LTI) system and an uncertainty block, which incorporates nonlinearities. The uncertainty...
CART: Context-Anchored Recurrent Transformer -- A Parameter-Efficient Architecture with Learned Stability
new Abstract: We present CART (Context-Anchored Recurrent Transformer), a parameter-efficient language model that reuses a single shared core block R times across depth. Unlike prior looped transformers that recompute key-value tensors at every iteration, CART computes K and V once from a multi-layer prelude and has the recurrent core cross-attend to those frozen tensors via multi-head latent attention. A learned Linear Time-Invariant (LTI) gate keeps the recurrence stable: its spectral...
Convergence Analysis of Natural Power Method and Its Applications to Control
arXiv:2512.21469v2 Announce Type: replace-cross Abstract: This paper analyzes the discrete-time natural power method, demonstrating its convergence to the dominant $r$-dimensional subspace corresponding to the $r$ eigenvalues with the largest absolute values. This contrasts with the Oja flow, which targets eigenvalues with the largest real parts. We leverage this property to develop methods for model order reduction and low-rank controller synthesis for discrete-time LTI systems, proving...
Robust and efficient data-driven predictive control
arXiv:2409.18867v2 Announce Type: replace Abstract: We propose a robust and efficient data-driven predictive control (eDDPC) scheme which is more sample efficient (requires less offline data) compared to existing schemes, and is also computationally efficient. This scheme employs a recently proposed data-based representation of linear time-invariant (LTI) systems as a predictor. Such a representation serves as an alternative to Hankel-based predictors obtained from, e.g., the so-called...
State Observers for Linear Systems with Prescribed Residual Bounds
Announce Type: new Abstract: This paper presents a state observer design for continuous linear time-invariant (LTI) systems subject to unknown bounded disturbances, that enforces a prescribed bound on the observer residual. The proposed observer augments a continuous-time Luenberger observer with state resets, triggered when the norm of the residual equals a pre-specified bound. The reset map guarantees contraction of the residual at jump instants while preserving the uniform boundedness...
Branch-Level Energy Localization in Three-Phase Loads: Resolving Indeterminacy in Time-Domain
arXiv:2606.07076v1 Announce Type: cross Abstract: This paper develops a branch-level energy-localization framework for three-phase loads. The instantaneous terminal power of an admissible lumped equivalent is decomposed uniquely as Joule dissipation plus magnetic and electric stored-energy rates, branch by branch. Three formal results are established: a Branch-Level Localization Theorem (uniqueness given an admissible topology); a Topology-Indeterminacy Theorem (multiple admissible...
Autoantibodies Drive Fc Gamma Receptor-Dependent Colon Inflammation During Immune Checkpoint Blockade
Immune-related adverse events (irAEs), particularly colitis, are major limitations of immune checkpoint inhibitor (ICI) therapy, but their mechanisms remain poorly understood. Here we show that endogenous autoantibodies (AAbs) can promote ICI-associated colitis through Fc gamma receptor (FcgR) dependent pathways. IgG from melanoma patients treated with pembrolizumab, nivolumab, or ipilimumab, with or without severe colitis, was transferred into wild-type or humanized FcgR (hFcgR) mice...
Branch-Level Energy Localization in Three-Phase Loads: Resolving Indeterminacy in Time-Domain
Announce Type: replace-cross Abstract: This paper develops a branch-level energy-localization framework for three-phase loads. The instantaneous terminal power of an admissible lumped equivalent is decomposed uniquely as Joule dissipation plus magnetic and electric stored-energy rates, branch by branch. Three formal results are established: a Branch-Level Localization Theorem (uniqueness given an admissible topology); a Topology-Indeterminacy Theorem (multiple admissible topologies reproduce...