This study deals with the design of a robust fault estimation and fault-tolerant control for vehicle lateral dynamics subject to external disturbance and unknown sensor faults. Firstly, a descriptor ...state and fault observer is designed to achieve the system state and sensor fault estimates simultaneously. Secondly, based on the information of on-line fault estimates, a robust fault-tolerant controller based on static output-feedback controller (SOFC) design approach is developed. To provide linear matrix inequalities of less conservatism, the results are conducted in the non-quadratic framework dealing with unmeasurable premise variables case. Simulation results show the effectiveness of the proposed control approach when the vehicle road adhesion conditions change and the sideslip angle is unavailable for measurement.
This paper is concerned with a non‐fragile H∞ state feedback control issue for linear parameter‐varying collaborative adaptive cruise control systems subject to denial‐of‐service attacks. The ...dynamics of the collaborative adaptive cruise control system is described by a linear model where the deviation of the position and the velocity are selected as the state variables. The attack model is utilized, thereby better reflecting the randomly occurring phenomenon of the denial‐of‐service attacks based on a sequence of binary random variables. The main objective of this note is to develop a non‐fragile state feedback control scheme such that, for denial‐of‐service attacks and possible parameter variations in controller gains, the exponential mean‐square stability and the predefined performance index for the system states are guaranteed simultaneously. By using the matrix analysis techniques and Lyapunov stability theory, sufficient conditions for the desired controller are established and solved based on the solutions to the linear matrix inequality conditions. Finally, a three‐car model is provided to check the feasibility of the designed control scheme.
•Ultrasonic assisted synthesis of ZnS QDs capped by l-Cys and 2-ME.•Characterization of the QDs by XRD, TEM and UV–Vis spectroscopy.•Study of the photocatalytic activity of QDs based on ...decolorization of CV dye.•High performance photodegradation of the dye using low amount of QDs.
This study presents a rapid water-based chemical precipitation method for synthesis of zinc sulfide (ZnS) quantum dots (QDs), under the ultrasonic radiation, using two capping agents; including 2-mercaptoethanol and l-cysteine. It is demonstrated that by applying ultrasonic radiation, the synthesis time can be significantly decreased. The effect of capping agent type on the color specifications (using colorimetry), absorption spectra (using ultraviolet–visible absorption spectroscopy) and ZnS structure (using X-ray diffraction) are investigated. The results of the research indicate that the as-synthesized QDs were cubic structures with dimensions less than 10 nm. After characterization, the QDs samples were performed as nano-scaled photoatalysts, through a UV-driven photodegradation process for the degradation of crystalline violet (CV) as a pollutant dye. Moreover, the present study assesses the effect of operating conditions including the pH of the dye solution, UV-irradiation time, ionic strength, type and dosage of nanophotocatalyst on degradation efficiency. Experimental results of the research demonstrate the QDs can be reused for at-least five times, without a significant decrease in their photocatalytic properties. The maximum photodegradation efficiency for the CV solution adjusted at pH 11, in the presence of a low amount of QDs (i.e. 5 mg) was observed after 90 min irradiation time. Finally, the probable mechanism and kinetics of degradation reaction are proposed in the study. From the kinetic data, the acceptable regression coefficient values (>0.98) for the pseudo first-order kinetic model was obtained for expression the present QD-based photodegradation approach.
This paper is concerned with the recursive fusion estimation‐based mobile robot localization (RL) problem by employing multiple energy harvesting sensors (EHSs). In the addressed RL problem, multiple ...sensors with energy harvesting capacity are deployed to produce measurements used for RL. When the sensors own sufficient energy, the sensors can output measurements and then send them to the corresponding local filter. Otherwise, the sensor energy‐induced missing measurement phenomenon will occur. In order to obtain the missing measurement rate, at each time instant, the relationship between the totality of the sensor energy and its probability distribution is derived recursively. This paper aims at seeking out a practicable solution to the addressed mobile RL problem. First, in the presence of the sensor energy‐induced measurement missing phenomenon, an upper bound (UB) of the local localization error covariance is recursively acquired. Then, such a derived UB is minimized by suitably devising the desired local filter parameter. Subsequently, the covariance intersection fusion method is adopted to achieve the addressed RL problem. In the end, a simulation is conducted to verify the practicability of the developed RL scheme.
•We develop a model for a spar-type floating wind turbine with a TMD in platform.•Unknown parameters in the model are estimated and further verified.•We investigate different optimization methods to ...tune TMD parameters.•High fidelity simulations are conducted under different wind and wave conditions.•Results demonstrate both the effectiveness and limitation of different designs.
Compared with fixed-bottom installation, deep water floating wind turbine has to undergo more severe structural loads due to extra degrees of freedom. Aiming for effective load reduction, this paper deals with the evaluation of a passive structural control design for a spar-type floating wind turbine, and the proposed strategy is to install a tuned mass damper (TMD) into the spar platform. Firstly, a mathematical model for wind turbine surge-heave-pitch motion is established based on the D’Alembert’s principle of inertial forces. Then, parameter estimation is performed by comparing the outputs from the proposed model and the state-of-the-art simulator. Further, different optimization methods are adopted to optimize TMD parameters when considering different performance indices. Finally, high fidelity nonlinear simulations with previous optimized TMD designs are conducted under different wind and wave conditions. Simulation results demonstrate both the effectiveness and limitation of different TMD parameter choices, providing parametric analysis and design basis for future improvement on floating wind turbine load reduction with structural control methods.
This paper addresses the problem of delay-dependent robust and reliable, H ∞ static output feedback (SOF) control for uncertain discrete-time piecewise-affine (PWA) systems with time-delay and ...actuator failure in a singular system setup. The Markov chain is applied to describe the actuator faults behaviors. In particular, by utilizing a system augmentation approach, the conventional closed-loop system is converted into a singular PWA system. By constructing a mode-dependent piecewise Lyapunov-Krasovskii functional, a new H ∞ performance analysis criterion is then presented, where a novel summation inequality and S-procedure are succeedingly employed. Subsequently, thanks to the special structure of the singular system formulation, the PWA SOF controller design is proposed via a convex program. Illustrative examples are finally given to show the efficacy and less conservatism of the presented approach.
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•Enhanced Cefixime degradation in a novel continuous optical-fiber microreactor.•The ZnO nanorods array/TiO2/GO photocatalyst composite was successfully coated on the optical fiber ...via simple step-by-step chemical bath deposition.•The effect of operational and geometrical parameters on the removal efficiency of Cefixime for two different light sources was performed.•Using a low-intensity focused light can introduce higher removal efficiency compared with conventional high-intensity diffused light source.•The intermediates created under optimal operating conditions are non-toxic.
A new high-efficiency continuous photocatalytic system composed of a microreactor and an optical fiber coated with a ZnO nanorod array/TiO2/GO with a retention time of 4–7 min was introduced. Using a new step-by-step chemical bath deposition method, a ZnO nanorod array coated with TiO2 and GO was grown on the surface of an optical fiber with different mass ratios. The coated photocatalytic layer was characterized using XRD, XPS, Raman spectra, UV-drs, TEM, and SEM. The photocatalytic degradation efficiency of Cefixime (CEF) in the microreactor was studied under irradiation from two diffusing and focusing light sources to determine the effect of light radiation type on the efficiency. ZnO nanorods/TiO2 coated optical fiber (Ti/Zn weight ratio = 0.37) and GO deposition during the growth of ZnO nanorods demonstrated the highest degradation efficiency. The operational and geometrical parameters were optimized as fiber length = 15 cm, fiber diameter = 500 µm, CEF concentration = 10 ppm, and pH = 4.8. The removal efficiency under these conditions was approximately 67 % with a diffused light source and 80.1 % with a focused light source. The coated photocatalytic composite showed high stability to the liquid flow after 1200 min of continuous operation, indicating the ZnO nanorods/TiO2/GO coating method's success.
Large wind farms are gaining prominence due to increasing dependence on renewable energy. In order to operate these wind farms reliably and efficiently, advanced maintenance strategies such as ...condition based maintenance are necessary. However, wind turbines pose unique challenges in terms of irregular load patterns, intermittent operation and harsh weather conditions, which have deterring effects on life of rotating machinery. This paper reviews the state-of-the-art in the area of diagnostics and prognostics pertaining to two critical failure prone components of wind turbines, namely, low-speed bearings and planetary gearboxes. The survey evaluates those methods that are applicable to wind turbine farm-level health management and compares these methods on criteria such as reliability, accuracy and implementation aspects. It concludes with a brief discussion of the challenges and future trends in health assessment for wind farms.
In this work, the sliding mode control (SMC) problem is addressed for the discrete‐time interval type‐2 fuzzy singularly perturbed systems. A component‐based dynamic event‐triggering scheme is first ...proposed to determine the transmission of each measurement component according to the prespecified triggering condition, under which each sensor node will transmit independently its signal to the controller. Meanwhile, the SMC approach is used to design an effective interval‐type‐2 fuzzy controller by only utilizing the transmitted component signals, and the ε‐independent conditions are developed to attain the stability of the closed‐loop system and the reachability of the sliding domain. In addition, a framework of the optimization control design is established, where the learning‐based iterative optimization algorithm is proposed via reducing the convergence domain around the sliding surface. Finally, the proposed SMC scheme is verified via the simulation results.
Some artificial intelligence algorithms have gained much attention in the rotating machinery fault diagnosis due to their robust nonlinear regression properties. In addition, existing deep learning ...algorithms are usually dependent on single signal features, which would lead to the loss of some information or incomplete use of the information in the signal. To address this problem, three kinds of popular signal processing methods, including Fast Fourier Transform (FFT), Short-Time Fourier Transform (STFT) and directly slicing one-dimensional data into the two-dimensional matrix, are used to create four different datasets from raw vibration signal as the input data of four enhancement Convolutional Neural Networks (CNN) models. Then, a fuzzy fusion strategy is used to fuse the output of four CNN models that could analyze the importance of each classifier and explore the interaction index between each classifier, which is different from conventional fusion strategies. To show the performance of the proposed model, an artificial fault bearing dataset and a real-world bearing dataset are used to test the feature extraction capability of the model. The good anti-noise and interpretation characteristics of the proposed method are demonstrated as well.
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