3,765 research outputs found
On the Local Quadratic Stability of T-S Fuzzy Systems in the Vicinity of the Origin
The main goal of this paper is to introduce new local stability conditions
for continuous-time Takagi-Sugeno (T-S) fuzzy systems. These stability
conditions are based on linear matrix inequalities (LMIs) in combination with
quadratic Lyapunov functions. Moreover, they integrate information on the
membership functions at the origin and effectively leverage the linear
structure of the underlying nonlinear system in the vicinity of the origin. As
a result, the proposed conditions are proved to be less conservative compared
to existing methods using fuzzy Lyapunov functions in the literature. Moreover,
we establish that the proposed methods offer necessary and sufficient
conditions for the local exponential stability of T-S fuzzy systems. The paper
also includes discussions on the inherent limitations associated with fuzzy
Lyapunov approaches. To demonstrate the theoretical results, we provide
comprehensive examples that elucidate the core concepts and validate the
efficacy of the proposed conditions
Finite-Time Analysis of Temporal Difference Learning: Discrete-Time Linear System Perspective
TD-learning is a fundamental algorithm in the field of reinforcement learning
(RL), that is employed to evaluate a given policy by estimating the
corresponding value function for a Markov decision process. While significant
progress has been made in the theoretical analysis of TD-learning, recent
research has uncovered guarantees concerning its statistical efficiency by
developing finite-time error bounds. This paper aims to contribute to the
existing body of knowledge by presenting a novel finite-time analysis of
tabular temporal difference (TD) learning, which makes direct and effective use
of discrete-time stochastic linear system models and leverages Schur matrix
properties. The proposed analysis can cover both on-policy and off-policy
settings in a unified manner. By adopting this approach, we hope to offer new
and straightforward templates that not only shed further light on the analysis
of TD-learning and related RL algorithms but also provide valuable insights for
future research in this domain.Comment: arXiv admin note: text overlap with arXiv:2112.1441
New Less Conservative Control Design Conditions for T-S Fuzzy Systems: Relaxed Parameterized Linear Matrix Inequality in the Form of Double Sum
The aim of this study is to investigate less conservative conditions for a
parameterized linear matrix inequality (PLMI) expressed in the form of double
convex sum. This type of PLMI appears frequently in nonlinear T-S fuzzy control
analysis and synthesis problems. In this paper, we derive sufficient linear
matrix inequalities (LMIs) for the PLMI without using any slack variables, by
employing the proposed sum relaxation based on Young's inequality. The derived
LMIs are proven to be less conservative than those presented in [1]. The
proposed technique is applicable to various control design problems for T-S
fuzzy systems represented in PLMIs that take the form of double convex sum.
Furthermore, an example is provided to illustrate the reduced conservatism of
the derived LMIs
An O.D.E. Framework of Distributed TD-Learning for Networked Multi-Agent Markov Decision Processes
The primary objective of this paper is to investigate distributed ordinary
differential equation (ODE) and distributed temporal difference (TD) learning
algorithms for networked multi-agent Markov decision problems (MAMDPs). In our
study, we adopt a distributed multi-agent framework where individual agents
have access only to their own rewards, lacking insights into the rewards of
other agents. Additionally, each agent has the ability to share its parameters
with neighboring agents through a communication network, represented by a
graph. Our contributions can be summarized in two key points: 1) We introduce
novel distributed ODEs, inspired by the averaging consensus method in the
continuous-time domain. The convergence of the ODEs is assessed through control
theory perspectives. 2) Building upon the aforementioned ODEs, we devise new
distributed TD-learning algorithms. A standout feature of one of our proposed
distributed ODEs is its incorporation of two independent dynamic systems, each
with a distinct role. This characteristic sets the stage for a novel
distributed TD-learning strategy, the convergence of which can potentially be
established using Borkar-Meyn theorem
Criterion of vehicle instability in floodwaters: past, present and future
This is an Accepted Manuscript of an article published by Taylor & Francis Group in International Journal of River Basin Management on January 2019, available online at: http://www.tandfonline.com/10.1080/15715124.2019.1566240The stability of vehicles exposed to floodwaters on the roads should not be taken for granted, especially in floodplain areas. When a vehicle in floodwaters becomes unstable, it tends to become buoyant and, eventually, is washed away, putting occupants in extreme danger. Therefore, the characteristics of vehicle instability in floodwaters should be critically understood to prepare safety guidelines. This paper attempts to summarize different vehicle stability studies, which focused on parked vehicles for a range of flood depths, through experimental and theoretical analysis (1967â1993). However, modern vehicle designs mean there are different values for the stability limits under partial or full submergence with different braking conditions, orientations and ground slopes (2010â2017). Since all the reported studies are about static vehicles, this paper attempts to address, for the very first time, vehicles in motion and endangered by floodwaters. As such, the governing effect of incipient velocity for a partially submerged, non-stationary vehicle will be presented, under the consideration of two new parameters, namely rolling friction and driving force.Peer ReviewedPostprint (author's final draft
Curcumin induces stabilization of Nrf2 protein through Keap1 cysteine modification
The present study was aimed to investigate the effects of curcumin, a representative chemopreventive phytochemical with pronounced antioxidant and anti-inflammatory properties, on activation of Nrf2 and expression of its target protein heme oxygenase-1 (HO-1) in mouse skin in vivo and in cultured murine epidermal cells. Treatment of mouse epidermal JB6 cells with curcumin resulted in the induction of HO-1 expression, and this was abrogated in cells transiently transfected with Nrf2 siRNA. While curcumin treatment increased protein expression of Nrf2, it did not alter the steady-state level of the Nrf2 mRNA transcript. Treatment of cells with curcumin stabilized Nrf2 by inhibiting ubiquitination and subsequent 26S proteasomal degradation of this transcription factor. Tetrahydrocurcumin, a non-electrophilic analogue of curcumin that lacks the alpha,beta-unsaturated carbonyl group, failed to induce HO-1 expression as well as nuclear translocation of Nrf2 and its binding to the antioxidant/electrophile response elements. Cells transfected with a mutant Keap1 protein in which cysteine 151 (Cys151) is replaced by serine exhibited marked reduction in curcumin-induced Nrf2 transactivation. Mass spectrometric analysis revealed that curcumin binds to Keap1 Cys151, supporting that this amino acid is a critical target for curcumin modification of Keap1, which facilitates the liberation of Nrf2. Thus, it is likely that the alpha,beta-unsaturated carbonyl moiety of curcumin is essential for its binding to Keap1 and stabilization of Nrf2 by hampering ubiquitination and proteasomal degradation.
Bridge Health Mornitoring using Wireless Sensor Networks
Summary Wireless sensor networks bring new challenges to Bridge monitoring. To monitor a bridge, behavior, including vibration and displacement, must be measured to analyze the health of the structure based on measured and collected data. The collected data can be used to compute modal properties of the bridge. A bridge is moved by external forces, including wind, seismic activity, and traffic. So it is very hard reliance of safety through a preexistence method which uses Data Logger. Dynamic behavior of a bridge is difficult to measure because of costs and installation methods. In this paper, a new method, using a U-Smart Sensor and Sensor Networking to measure the dynamic behavior of the bridge, is suggested. A new wireless MEMS accelerometer sensor (U-Smart Sensor) board is designed to meet the specific hardware and software requirements of structural engineering applications
- âŠ