Event-triggering robust fusion estimation for a class of multi-rate systems subject to censored observations

2020 ◽  
Author(s):  
Cong Huang ◽  
Peng Mei ◽  
Jun Wang
Keyword(s):  
Event Triggering ◽  
Censored Observations

scholarly journals Zero-inflated-censored Weibull and gamma regression models to estimate wild boar population dispersal distance

2021 ◽  
Author(s):  
Eduardo de Freitas Costa ◽  
Silvana Schneider ◽  
Giulia Bagatini Carlotto ◽  
Tainá Cabalheiro ◽  
Mauro Ribeiro de Oliveira Júnior
Keyword(s):  
Wild Boar ◽  
Regression Models ◽  
Likelihood Function ◽  
Complex Structure ◽  
Dispersal Distance ◽  
Wild Boar Population ◽  
Gamma Distributions ◽  
Excess Of Zeros ◽  
Censored Observations ◽  
Positive Effect

AbstractThe dynamics of the wild boar population has become a pressing issue not only for ecological purposes, but also for agricultural and livestock production. The data related to the wild boar dispersal distance can have a complex structure, including excess of zeros and right-censored observations, thus being challenging for modeling. In this sense, we propose two different zero-inflated-right-censored regression models, assuming Weibull and gamma distributions. First, we present the construction of the likelihood function, and then, we apply both models to simulated datasets, demonstrating that both regression models behave well. The simulation results point to the consistency and asymptotic unbiasedness of the developed methods. Afterwards, we adjusted both models to a simulated dataset of wild boar dispersal, including excess of zeros, right-censored observations, and two covariates: age and sex. We showed that the models were useful to extract inferences about the wild boar dispersal, correctly describing the data mimicking a situation where males disperse more than females, and age has a positive effect on the dispersal of the wild boars. These results are useful to overcome some limitations regarding inferences in zero-inflated-right-censored datasets, especially concerning the wild boar’s population. Users will be provided with an R function to run the proposed models.

scholarly journals An Optimized Triggering Algorithm for Event-Triggered Control of Networked Control Systems

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1262
Author(s):  
Sunil Kumar Mishra ◽  
Amitkumar V. Jha ◽  
Vijay Kumar Verma ◽  
Bhargav Appasani ◽  
Almoataz Y. Abdelaziz ◽  
...  
Keyword(s):  
Control Systems ◽  
Networked Control Systems ◽  
Networked Control ◽  
Pendulum System ◽  
Uniform Sampling ◽  
Inverted Pendulum System ◽  
Event Triggering ◽  
Non Uniform Sampling ◽  
System States ◽  
Event Triggered

This paper presents an optimized algorithm for event-triggered control (ETC) of networked control systems (NCS). Initially, the traditional backstepping controller is designed for a generalized nonlinear plant in strict-feedback form that is subsequently extended to the ETC. In the NCS, the controller and the plant communicate with each other using a communication network. In order to minimize the bandwidth required, the number of samples to be sent over the communication channel should be reduced. This can be achieved using the non-uniform sampling of data. However, the implementation of non-uniform sampling without a proper event triggering rule might lead the closed-loop system towards instability. Therefore, an optimized event triggering algorithm has been designed such that the system states are always forced to remain in stable trajectory. Additionally, the effect of ETC on the stability of backstepping control has been analyzed using the Lyapunov stability theory. Two case studies on an inverted pendulum system and single-link robot system have been carried out to demonstrate the effectiveness of the proposed ETC in terms of system states, control effort and inter-event execution time.

scholarly journals Event-triggering $${H}_{\infty }$$-based observer combined with NN for simultaneous estimation of vehicle sideslip and roll angles with network-induced delays

2021 ◽  
Vol 103 (3) ◽  
pp. 2733-2752
Author(s):  
Maria Jesus L. Boada ◽  
Beatriz L. Boada ◽  
Hui Zhang
Keyword(s):  
Autonomous Vehicles ◽  
Networked Control System ◽  
Observer Design ◽  
Simultaneous Estimation ◽  
Road Accidents ◽  
Sideslip Angle ◽  
Current Series ◽  
Event Triggering ◽  
Communication Scheme ◽  
Proper Design

AbstractNowadays, vehicles are being fitted with systems that improve their maneuverability, stability, and comfort in order to reduce the number of accidents. Improving these aspects is of particular interest thanks to the incorporation of autonomous vehicles onto the roads. The knowledge of vehicle sideslip and roll angles, which are among the main causes of road accidents, is necessary for a proper design of a lateral stability and roll-over controller system. The problem is that these two variables cannot be measured directly through sensors installed in current series production vehicles due to their high costs. For this reason, their estimation is fundamental. In addition, there is a time delay in the relaying of information between the different vehicle systems, such as, sensors, actuators and controllers, among others. This paper presents the design of an $${H}_{\infty }$$ H ∞ -based observer that simultaneously estimates both the sideslip angle and the roll angle of a vehicle for a networked control system, with networked transmission delay based on an event-triggered communication scheme combined with neural networks (NN). To deal with the vehicle nonlinearities, NN and linear-parameter-varying techniques are considered alongside uncertainties in parameters. Both simulation and experimental results are carried out to prove the performance of observer design.

scholarly journals Distributed Attitude Synchronization for Spacecraft Formation Flying via Event-Triggered Control

2021 ◽  
Vol 11 (14) ◽  
pp. 6299
Author(s):  
Xiong Xie ◽  
Tao Sheng ◽  
Liang He
Keyword(s):  
Control System ◽  
Formation Flying ◽  
Spacecraft Formation ◽  
Spacecraft Formation Flying ◽  
Control Scheme ◽  
Event Triggering ◽  
Computational Resources ◽  
Update Frequency ◽  
Attitude Synchronization ◽  
Event Triggered

The distributed attitude synchronization control problem for spacecraft formation flying subject to limited energy and computational resources is addressed based on event-triggered mechanism. Firstly, a distributed event-driven controller is designed to achieve attitude coordination with the limitation of energy and computing resources. Under the proposed control strategy, the controller is only updated at the event triggering instants, which effectively reduces the update frequency. Subsequently, an event-triggered strategy is developed to further decrease energy consumption and the amount of computation. The proposed event-triggered function only requires the latest state information about its neighbors, implying that the trigger threshold does not need to be calculated continuously. It is shown that the triggering interval between two successive events is strictly positive, showing that the control system has no Zeno phenomenon. Moreover, the update frequency of the proposed controller can be reduced by more than 90% compared to the update frequency of the corresponding time-driven controller with an update frequency of 10 Hz by choosing appropriate control parameters and the control system can still achieve high-precision convergence. Finally, the effectiveness of the constructed control scheme is verified by numerical simulations.

scholarly journals Event-Triggering State and Fault Estimation for a Class of Nonlinear Systems Subject to Sensor Saturations

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1242
Author(s):  
Cong Huang ◽  
Bo Shen ◽  
Lei Zou ◽  
Yuxuan Shen
Keyword(s):  
Nonlinear Systems ◽  
Difference Equations ◽  
Estimation Error ◽  
Upper Bounds ◽  
The State ◽  
Fault Estimation ◽  
Triggering Mechanism ◽  
Transmission Frequency ◽  
Current Transmission ◽  
Event Triggering

This paper is concerned with the state and fault estimation issue for nonlinear systems with sensor saturations and fault signals. For the sake of avoiding the communication burden, an event-triggering protocol is utilized to govern the transmission frequency of the measurements from the sensor to its corresponding recursive estimator. Under the event-triggering mechanism (ETM), the current transmission is released only when the relative error of measurements is bigger than a prescribed threshold. The objective of this paper is to design an event-triggering recursive state and fault estimator such that the estimation error covariances for the state and fault are both guaranteed with upper bounds and subsequently derive the gain matrices minimizing such upper bounds, relying on the solutions to a set of difference equations. Finally, two experimental examples are given to validate the effectiveness of the designed algorithm.

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