Abstract: Connected vehicles are one of the promising technologies for future Intelligent Transportation Systems (ITS). A connected vehicle system is essentially a set of vehicles communicating through a network to exchange their information with each other and the infrastructure. Although this interconnection of the vehicles can be potentially beneficial in creating an efficient, sustainable, and green transportation system, a set of safety and reliability challenges come out with this technology. The first challenge arises from the information loss due to unreliable communication network which affects the control/management system of the individual vehicles and the overall system. Such scenario may lead to degraded or even unsafe operation which could be potentially catastrophic. Secondly, faulty sensors and actuators can affect the individual vehicle’s safe operation and in turn will create a potentially unsafe node in the vehicular network. Further, sending that faulty sensor information to other vehicles and failure in actuators may significantly affect the safe operation of the overall vehicular network. Therefore, it is of utmost importance to take these issues into consideration while designing the control/management algorithms of the individual vehicles as a part of connected vehicle system. In this paper, we consider a connected vehicle system under Co-operative Adaptive Cruise Control (CACC) and propose a fault diagnosis scheme that deals with these aforementioned challenges. Specifically, the conventional CACC algorithm is modified by adding a Kalman filter-based estimation algorithm to suppress the effect of lost information under unreliable network. Further, a sliding mode observer-based algorithm is used to improve the sensor reliability under faults. The effectiveness of the overall diagnostic scheme is verified via simulation studies.
Abstract: This paper addresses the control problem of a class of hyper-redundant arms. In order to avoid discrepancy between the mathematical model and the actual dynamics, the dynamic model with uncertain parameters of this class of manipulators is inferred. A procedure to design a feedback controller which stabilizes the uncertain system has been proposed. A PD boundary control algorithm is used in order to control the desired position of the manipulator. This controller is easy to implement from the point of view of measuring techniques and actuation. Numerical simulations verify the effectiveness of the presented methods. In order to verify the suitability of the control algorithm, a platform with a 3D flexible manipulator has been employed for testing. Experimental tests on this platform illustrate the applications of the techniques developed in the paper.
Abstract: Liquid level control of conical tank system is known to be a great challenge in many industries such as food processing, hydrometallurgical industries and wastewater treatment plant due to its highly nonlinear characteristics. In this research, an adaptive fuzzy PID control scheme is applied to the problem of liquid level control in a nonlinear tank process. A conical tank process is first modeled and primarily simulated. A PID controller is then applied to the plant model as a suitable benchmark for comparison and the dynamic responses of the control system to different step inputs were investigated. It is found that the conventional PID controller is not able to fulfill the controller design criteria such as desired time constant due to highly nonlinear characteristics of the plant model. Consequently, a nonlinear control strategy based on gain-scheduling adaptive control incorporating a fuzzy logic observer is proposed to accurately control the nonlinear tank system. The simulation results clearly demonstrated the superiority of the proposed adaptive fuzzy control method over the conventional PID controller.
Abstract: Designing a controller for stochastic decentralized interconnected large scale systems usually involves a high degree of complexity and computation ability. Noise, observability, and controllability of all system states, connectivity, and channel bandwidth are other constraints to design procedures for distributed large scale systems. The quasi-steady state model investigated in this paper is a reduced order model of the original system using singular perturbation techniques. This paper results in an optimal control synthesis to design an observer based feedback controller by standard stochastic control theory techniques using Linear Quadratic Gaussian (LQG) approach and Kalman filter design with less complexity and computation requirements. Numerical example is given at the end to demonstrate the efficiency of the proposed method.
Abstract: In the SHP, LVDT sensor is for detecting the length
changes of the EHA output, and the thrust of the EHA is controlled by
the pressure sensor. Sensor is possible to cause hardware fault by
internal problem or external disturbance. The EHA of SHP is able to
be uncontrollable due to control by feedback from uncertain
information, on this paper; the sliding mode observer algorithm
estimates the original sensor output information in permanent sensor
fault. The proposed algorithm shows performance to recovery fault of
disconnection and short circuit basically, also the algorithm detect
various of sensor fault mode.
Abstract: In this work, we use the Fault detection and isolation and the Fault tolerant control based on sliding mode observer in order to introduce the well diagnosis of a nonlinear system. The robustness of the proposed observer for the two techniques is tested through a physical example. The results in this paper show the interaction between the Fault tolerant control and the Diagnosis procedure.
Abstract: Digital technologies offer many opportunities in the
design and implementation of brand communication and advertising.
Augmented reality (AR) is an innovative technology in marketing
communication that focuses on the fact that virtual interaction with a
product ad offers additional value to consumers. AR enables
consumers to obtain (almost) real product experiences by the way of
virtual information even before the purchase of a certain product.
Aim of AR applications in relation with advertising is in-depth
examination of product characteristics to enhance product knowledge
as well as brand knowledge. Interactive design of advertising
provides observers with an intense examination of a specific
advertising message and therefore leads to better brand knowledge.
The elaboration likelihood model and the central route to persuasion
strongly support this argumentation. Nevertheless, AR in brand
communication is still in an initial stage and therefore scientific
findings about the impact of AR on information processing and brand
attitude are rare. The aim of this paper is to empirically investigate
the potential of AR applications in combination with traditional print
advertising. To that effect an experimental design with different
levels of interactivity is built to measure the impact of interactivity of
an ad on different variables o advertising effectiveness.
Abstract: This paper presents a speed estimation scheme based
on second-order sliding-mode Super Twisting Algorithm (STA) and
Model Reference Adaptive System (MRAS) estimation theory for
Sensorless control of multiphase induction machine. A stator current
observer is designed based on the STA, which is utilized to take the
place of the reference voltage model of the standard MRAS
algorithm. The observer is insensitive to the variation of rotor
resistance and magnetizing inductance when the states arrive at the
sliding mode. Derivatives of rotor flux are obtained and designed as
the state of MRAS, thus eliminating the integration. Compared with
the first-order sliding-mode speed estimator, the proposed scheme
makes full use of the auxiliary sliding-mode surface, thus alleviating
the chattering behavior without increasing the complexity. Simulation
results show the robustness and effectiveness of the proposed
scheme.
Abstract: Multiphase Induction Machine (IM) is normally
controlled using rotor field oriented vector control. Under phase(s)
loss, the machine currents can be optimally controlled to satisfy
certain optimization criteria. In this paper we discuss the performance
of double manifold sliding mode observer (DM-SMO) in Sensorless
control of multiphase induction machine under unsymmetrical
condition (one phase loss). This observer is developed using the IM
model in the stationary reference frame. DM-SMO is constructed by
adding extra feedback term to conventional single mode sliding mode
observer (SM-SMO) which proposed in many literature. This leads to
a fully convergent observer that also yields an accurate estimate of
the speed and stator currents. It will be shown by the simulation
results that the estimated speed and currents by the method are very
well and error between real and estimated quantities is negligible.
Also parameter sensitivity analysis shows that this method is rather
robust against parameter variation.
Abstract: Purpose: The study aimed to assess the depressant or
antidepressant effects of several Nonsteroidal Anti-Inflammatory
Drugs (NSAIDs) in mice: the selective cyclooxygenase-2 (COX-2)
inhibitor meloxicam, and the non-selective COX-1 and COX-2
inhibitors lornoxicam, sodium metamizole, and ketorolac. The
current literature data regarding such effects of these agents are
scarce.
Materials and methods: The study was carried out on NMRI mice
weighing 20-35 g, kept in a standard laboratory environment. The
study was approved by the Ethics Committee of the University of
Medicine and Pharmacy „Carol Davila”, Bucharest. The study agents
were injected intraperitoneally, 10 mL/kg body weight (bw) 1 hour
before the assessment of the locomotor activity by cage testing (n=10
mice/ group) and 2 hours before the forced swimming tests (n=15).
The study agents were dissolved in normal saline (meloxicam,
sodium metamizole), ethanol 11.8% v/v in normal saline (ketorolac),
or water (lornoxicam), respectively. Negative and positive control
agents were also given (amitryptilline in the forced swimming test).
The cage floor used in the locomotor activity assessment was divided
into 20 equal 10 cm squares. The forced swimming test involved
partial immersion of the mice in cylinders (15/9cm height/diameter)
filled with water (10 cm depth at 28C), where they were left for 6
minutes. The cage endpoint used in the locomotor activity assessment
was the number of treaded squares. Four endpoints were used in the
forced swimming test (immobility latency for the entire 6 minutes,
and immobility, swimming, and climbing scores for the final 4
minutes of the swimming session), recorded by an observer that was
„blinded” to the experimental design. The statistical analysis used the
Levene test for variance homogeneity, ANOVA and post-hoc
analysis as appropriate, Tukey or Tamhane tests.
Results: No statistically significant increase or decrease in the
number of treaded squares was seen in the locomotor activity
assessment of any mice group. In the forced swimming test,
amitryptilline showed an antidepressant effect in each experiment, at
the 10 mg/kg bw dosage. Sodium metamizole was depressant at 100
mg/kg bw (increased the immobility score, p=0.049, Tamhane test),
but not in lower dosages as well (25 and 50 mg/kg bw). Ketorolac
showed an antidepressant effect at the intermediate dosage of 5
mg/kg bw, but not so in the dosages of 2.5 and 10 mg/kg bw,
respectively (increased the swimming score, p=0.012, Tamhane test).
Meloxicam and lornoxicam did not alter the forced swimming
endpoints at any dosage level.
Discussion: 1) Certain NSAIDs caused changes in the forced
swimming patterns without interfering with locomotion. 2) Sodium
metamizole showed a depressant effect, whereas ketorolac proved
antidepressant. Conclusion: NSAID-induced mood changes are not
class effects of these agents and apparently are independent of the
type of inhibited cyclooxygenase (COX-1 or COX-2).
Disclosure: This paper was co-financed from the European Social
Fund, through the Sectorial Operational Programme Human Resources Development 2007-2013, project number POSDRU /159
/1.5 /S /138907 "Excellence in scientific interdisciplinary research,
doctoral and postdoctoral, in the economic, social and medical fields
-EXCELIS", coordinator The Bucharest University of Economic
Studies.
Abstract: In this contribution a structure for high level lateral vehicle tracking control based on the disturbance observer is presented. The structure is characterized by stationary compensating side forces disturbances and guaranteeing a cooperative behavior at the same time. Driver inputs are not compensated by the disturbance observer. Moreover the structure is especially useful as it robustly stabilizes the vehicle. Therefore the parameters are selected using the Parameter Space Approach. The implemented algorithms are tested in real world scenarios.
Abstract: This paper presents a novel integrated hybrid
approach for fault diagnosis (FD) of nonlinear systems. Unlike most
FD techniques, the proposed solution simultaneously accomplishes
fault detection, isolation, and identification (FDII) within a unified
diagnostic module. At the core of this solution is a bank of adaptive
neural parameter estimators (NPE) associated with a set of singleparameter
fault models. The NPEs continuously estimate unknown
fault parameters (FP) that are indicators of faults in the system. Two
NPE structures including series-parallel and parallel are developed
with their exclusive set of desirable attributes. The parallel scheme is
extremely robust to measurement noise and possesses a simpler, yet
more solid, fault isolation logic. On the contrary, the series-parallel
scheme displays short FD delays and is robust to closed-loop system
transients due to changes in control commands. Finally, a fault
tolerant observer (FTO) is designed to extend the capability of the
NPEs to systems with partial-state measurement.
Abstract: Quantification of cardiac function is performed by
calculating blood volume and ejection fraction in routine clinical
practice. However, these works have been performed by manual
contouring, which requires computational costs and varies on the
observer. In this paper, an automatic left ventricle segmentation
algorithm on cardiac magnetic resonance images (MRI) is presented.
Using knowledge on cardiac MRI, a K-mean clustering technique is
applied to segment blood region on a coil-sensitivity corrected image.
Then, a graph searching technique is used to correct segmentation
errors from coil distortion and noises. Finally, blood volume and
ejection fraction are calculated. Using cardiac MRI from 15 subjects,
the presented algorithm is tested and compared with manual
contouring by experts to show outstanding performance.
Abstract: Operations, maintenance and reliability of wind
turbines have received much attention over the years due to the rapid
expansion of wind farms. This paper explores early fault diagnosis
technique for a 5MW wind turbine system subjected to multiple
faults, where genetic optimization algorithm is employed to make the
residual sensitive to the faults, but robust against disturbances. The
proposed technique has a potential to reduce the downtime mostly
caused by the breakdown of components and exploit the productivity
consistency by providing timely fault alarms. Simulation results show
the effectiveness of the robust fault detection methods used under
Matlab/Simulink/Gatool environment.
Abstract: This paper presents a real-time visualization technique
and filtering of classified LiDAR point clouds. The visualization is
capable of displaying filtered information organized in layers by the
classification attribute saved within LiDAR datasets. We explain the
used data structure and data management, which enables real-time
presentation of layered LiDAR data. Real-time visualization is
achieved with LOD optimization based on the distance from the
observer without loss of quality. The filtering process is done in two
steps and is entirely executed on the GPU and implemented using
programmable shaders.
Abstract: The relationship between eigenstructure (eigenvalues
and eigenvectors) and latent structure (latent roots and latent vectors)
is established. In control theory eigenstructure is associated with
the state space description of a dynamic multi-variable system and
a latent structure is associated with its matrix fraction description.
Beginning with block controller and block observer state space forms
and moving on to any general state space form, we develop the
identities that relate eigenvectors and latent vectors in either direction.
Numerical examples illustrate this result. A brief discussion of the
potential of these identities in linear control system design follows.
Additionally, we present a consequent result: a quick and easy
method to solve the polynomial eigenvalue problem for regular matrix
polynomials.
Abstract: The goal of the present paper is to model two classic lines of research in which employees starred, organizational justice and citizenship behavior (OCB), but that have never been studied together when targeting customers. The suggestion is made that a hotel’s fair treatment (in terms of distributive, procedural, and interactional justice) toward customers will be appreciated by the employees, who will reciprocate in kind by favoring the hotel with increased customer-oriented behaviors (COBs). Data were collected from 204 employees at eight upscale hotels in the Canary Islands (Spain). Unlike in the case of perceptions of distributive justice, results of structural equation modeling demonstrate that employees substantively react to interactional and procedural justice toward guests by engaging in customer-oriented behaviors (COBs). The findings offer new reasons why employees decide to engage in COBs, and they highlight potentially beneficial effects of fair treatment toward guests bring to hospitality through promoting COBs.
Abstract: The primary objective of this paper is to elimination of the problem of sensitivity to parameter variation of induction motor drive. The proposed sensorless strategy is based on an algorithm permitting a better simultaneous estimation of the rotor speed and the stator resistance including an adaptive mechanism based on the lyaponov theory. To study the reliability and the robustness of the sensorless technique to abnormal operations, some simulation tests have been performed under several cases.
The proposed sensorless vector control scheme showed a good performance behavior in the transient and steady states, with an excellent disturbance rejection of the load torque.
Abstract: This paper realized the 2-DOF controller structure for first order with time delay systems. The co-prime factorization is used to design observer based controller K(s), representing one degree of freedom. The problem is based on H∞ norm of mixed sensitivity and aims to achieve stability, robustness and disturbance rejection. Then, the other degree of freedom, prefilter F(s), is formulated as fixed structure polynomial controller to meet open loop processing of reference model. This model matching problem is solved by minimizing integral square error between reference model and proposed model. The feedback controller and prefilter designs are posed as optimization problem and solved using Particle Swarm Optimization (PSO). To show the efficiency of the designed approach different variety of processes are taken and compared for analysis.
Abstract: This paper addresses a control system design for a table drive system based on the disturbance observer (DOB)-based
predictive functional critical control (PFCC). To empower the previously developed DOB-based PFC to handle constraints on
controlled outputs, we propose to take a critical control approach. To this end, we derive the transfer function representation of the PFC controller and yield a detailed design procedure. The effectiveness of the proposed method is confirmed through an experimental evaluation.