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The problem of trajectory tracking control in mobile robots under uncertainties is addressed in this paper. Following the results of mobile robots trajectory tracking reported in ( Scaglia et al., 2010 ), the problem of model errors is focused and the zero convergence of tracking errors under polynomial uncertainties is demonstrated. A simple scheme is obtained, which can be easily implemented. Simulation and experimental results are presented and discussed, showing the good performance of the controller. [ABSTRACT FROM AUTHOR]

Abstract: In advanced industry manufacturing involving robotic operations, the required tasks can be frequently formulated in terms of a path or trajectory tracking. In this paper, an approach based on sliding mode conditioning of a path parametrization is proposed to achieve the greatest tracking speed which is compatible with the robot input constraints (joint speeds). Some distinctive features of the proposal are that: (1) it is completely independent of the robot parameters, and it does not require a priori knowledge of the desired path either, (2) it avoids on-line computations necessary for conventional analytical methodologies, and (3) it can be easily added as a supervisory block to pre-existing path tracking schemes. A sufficient condition (lower bound on desired tracking speed) for the sliding mode regulation to be activated is derived, while a chattering amplitude estimation is obtained in terms of the sampling period and a tunable first-order filter bandwidth. The algorithm is evaluated on the freely accessible 6R robot model PUMA-560, for which a path passing through a wrist singularity is considered to show the effectiveness of the proposal under hard tracking conditions. [Copyright &y& Elsevier]

This paper is concerned with the event-triggered output regulation problem for a class of linear networked switched systems (NSSs). A mode-dependent alternate event-triggered mechanism (AETM) is integrated into the NSSs with transmission delays and packet losses for the first time based on continuous detection and periodic sampling, and a joint-designed switching signal with the triggering information is presented. Under transmission delays and packet losses, a series of resultant error feedback controllers are synthesized in four cases based on the relationships between switching instants and event-triggered instants. Then, a criterion ensuring asynchronous output regulation performance is formed with transmission delays by the input delay method. With the presence of packet losses, a set of sufficient conditions is also dedicated to the proposed control issue by adding the restraint in the number of successive packet losses associated with a modified AETM. Eventually, a comparison and an F-18 aircraft model reveal the effectiveness of the obtained results in the simulation. [ABSTRACT FROM AUTHOR]

In this article, the event-triggered output regulation problem (EORP) under the denial-of-service (DoS) attacks is considered for networked switched systems (NSSs) with unstable switching dynamics (USDs). The USDs here refer to the unsolvable output regulation of each subsystem and the destabilization at partial switching instants, which indicates that the Lyapunov function does not decrease monotonically in activation intervals of each subsystem and increases at partial switching instants. First, long-duration DoS attacks (LDDAs) are considered, where LDDAs imply that their duration may be longer than the total dwell time (DT) of several adjacent activated subsystems. By imposing constraints at switching instants, consecutive asynchronous subsystem switching caused by LDDAs and USDs is allowed, that is, the subsystem switches several times but the controller switching is blocked by LDDAs and controllers fail to switch correspondingly. Second, mixed event-triggered mechanisms (ETMs), combining event-triggered conditions and periodic sampling conditions, are designed to reduce network burden under LDDAs and improve system performance subject to destabilizing switching. Then, an improved DT for switching signal permits irregular arrangement of destabilizing and stabilizing switching and is more suitable for NSSs subject to LDDAs. Moreover, sufficient conditions ensure the solvability of EORP for NSSs with USDs under LDDAs, network-induced delays, random packet losses, and packet disorders. Finally, a switched RLC circuit shows the feasibility of the proposed method.

Air pollution is one of the greatest challenges cities are facing today and improving air quality is a pressing need to reduce negative health impacts. In order to efficiently evaluate which are the most appropriate policies to reduce the impact of urban pollution sources (such as road traffic), it is essential to conduct rigorous population exposure assessments. One of the main limitations associated with those studies is the lack of information about population distribution in the city along the day (population dynamics). The pervasive use of mobile devices in our daily lives opens new opportunities to gather large amounts of anonymized and passively collected geolocation data allowing the analysis of population activity and mobility patterns. This study presents a novel methodology to estimate population dynamics from mobile phone data based on a user-centric mobility model approach. The methodology was tested in the city of Madrid (Spain) to evaluate population exposure to NO 2 . A comparison with traditional census-based methods shows relevant discrepancies at disaggregated levels and highlights the need to incorporate mobility patterns into population exposure assessments.