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 (1967–1993). 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 (2010–2017). 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