paper-with-me

Papers

Designing Robust Linear Output Feedback Controller based on CLF-CBF framework via Linear~Programming(LP-CLF-CBF)

2024-03-21 · Mahroo Bahreinian, Mehdi Kermanshah, Roberto Tron

We consider the problem of designing output feedback controllers that use measurements from a set of landmarks to navigate through a cell-decomposable environment using duality, Control Lyapunov and Barrier Functions (CLF, CBF), and Linear Programming. We propose two objectives for navigating in an environment, one to traverse the environment by making loops and one by converging to a stabilization point while smoothing the transition between consecutive cells. We test our algorithms in a simulation environment, evaluating the robustness of the approach to practical conditions, such as bearing-only measurements, and measurements acquired with a camera with a limited field of view.

📄 PDF Abstract BibTeX arXiv:2403.14519

Code (0)

등록된 구현이 없습니다.

Tasks

Navigate

Methods 이 논문이 사용한 방법론

SET Dynamic Sparse Training method where weight mask is updated randomly periodically

Similar Papers 제목 키워드 기반

Policy Gradient Methods for Designing Dynamic Output Feedback Controllers

2022-10-18 · Tomonori Sadamoto, Takumi Hirai

This paper proposes model-based and model-free policy gradient methods (PGMs) for designing dynamic output feedback controllers for discrete-time partially observable systems. To fulfill this objective, we first show tha…

Policy Gradient Methods

A Framework for Output-Feedback Symbolic Control

2020-11-30 · Mahmoud Khaled, Kuize Zhang, Majid Zamani

Symbolic control is an abstraction-based controller synthesis approach that provides, algorithmically, certifiable-by-construction controllers for cyber-physical systems. Symbolic control approaches usually assume that f…

On the Optimization Landscape of Dynamic Output Feedback: A Case Study for Linear Quadratic Regulator

2022-09-12 · Jingliang Duan, Wenhan Cao, Yang Zheng, Lin Zhao

The convergence of policy gradient algorithms in reinforcement learning hinges on the optimization landscape of the underlying optimal control problem. Theoretical insights into these algorithms can often be acquired fro…

Decision MakingPolicy Gradient Methods

Data-driven nonlinear output regulation via data-enforced incremental passivity

2025-06-06 · Yixuan Liu, Meichen Guo

This work proposes a data-driven regulator design that drives the output of a nonlinear system asymptotically to a time-varying reference and rejects time-varying disturbances. The key idea is to design a data-driven fee…

On the design of stabilizing FIR controllers

2024-08-21 · Janis Adamek, Nils Schlüter, Moritz Schulze Darup

Recently, it has been observed that finite impulse response controllers are an excellent basis for encrypted control, where privacy-preserving controller evaluations via special cryptosystems are the main focus. Benefici…

Privacy Preserving