TieJun Zhang

Superhydrophobic CuO nanoneedle-covered copper surfaces for anticorrosion

With unique water-repellency and self-cleaning properties, superhydrophobic surfaces promise a great potential of anticorrosion for engineered metals. The current study reports a facile and controllable anodization approach to fabricate superhydrophobic CuO nanoneedle array (NNA) films for the enhancement of corrosion resistance of copper substrates. The anodic CuO NNA films were grown on copper foils by electrochemical anodization in an aqueous KOH solution for different anodization times. The morphological features and crystalline structures of the anodic CuO NNA were characterized by SEM-EDS and XRD. The superhydrophobicity on the hierarchical CuO NNA films was achieved by chemical modification with fluoroalkyl-silane (FAS-17). The presence of low surface energy fluorosilanized carbon (–CFx) groups on the FAS-modified surfaces was ascertained by EDS, XPS and water contact angle analyses. The wetting behaviour of the FAS-modified surfaces was investigated to elucidate the correlation between the static water contact angles, surface roughness, dynamic water contact angle hysteresis, and anodization time. The FAS-modified copper surfaces demonstrated not only the desirable superhydrophobicity with a water contact angle as high as approximately 169° and contact angle hysteresis as low as about 5°, but also substantially improved corrosion resistance in an aqueous NaCl solution (3.5%) with an inhibition efficiency higher than 90%, as revealed by means of Tafel plots and EIS measurements. The stability and durability of the superhydrophobic FAS-modified surfaces were evaluated by observing the change in surface wettability and geometric microstructures as a function of exposure time in an aqueous NaCl solution.

Approaches to Robust Filtering Design of Discrete Time Fuzzy Dynamic Systems

This paper presents two filter design methods for discrete time fuzzy dynamic systems based on a piecewise quadratic Lyapunov function. It is shown that the resulting filtering error system is globally stable with guaranteed Hinfin or generalized H2 performance and the filter gains can be obtained by solving a set of linear matrix inequalities. Two simulation examples are also given to illustrate the performance of the proposed approaches.

Fuzzy Constrained Min-Max Model Predictive Control Based on Piecewise Lyapunov Functions

This paper proposes two novel stable fuzzy model predictive controllers based on piecewise Lyapunov functions and the min-max optimization of a quasi-worst case infinite horizon objective function. The main idea is to design state feedback control laws that minimize the worst case objective function based on fuzzy model prediction, and thus to obtain the optimal transient control performance, which is of great importance in industrial process control. Moreover, in both of these predictive controllers, piecewise Lyapunov functions have been used in order to reduce the conservatism of those existent predictive controllers based on common Lyapunov functions. It is shown that the asymptotic stability of the resulting closed-loop discrete-time fuzzy predictive control systems can be established by solving a set of linear matrix inequalities. Moreover, the controller designs of the closed-loop control systems with desired decay rate and input constraints are also considered. Simulations on a numerical example and a highly nonlinear benchmark system are presented to demonstrate the performance of the proposed fuzzy predictive controllers.

Rapid Load Following of an SOFC Power System via Stable Fuzzy Predictive Tracking Controller

The solid oxide fuel cell (SOFC) is widely accepted for clean and distributed power generation use, but critical operation problems often occur when the stand-alone fuel cell is directly connected to the electricity grid or the dc electric user. In order to address these problems, in this paper, a data-driven fuzzy modeling method is employed to identify the dynamic model of an integrated SOFC/capacitor system. A novel offset-free input-to-state stable fuzzy predictive controller is developed based on the obtained fuzzy model. Both the rapid power load following and safe SOFC operation requirements are taken into account in the design of the closed-loop control system. Simulations are also given to demonstrate the load following control performance of the proposed fuzzy predictive control strategy for the SOFC/capacitor power system.

Output tracking of constrained nonlinear processes with offset-free input-to-state stable fuzzy predictive control

This paper develops an efficient offset-free output feedback predictive control approach to nonlinear processes based on their approximate fuzzy models as well as an integrating disturbance model. The estimated disturbance signals account for all the plant-model mismatch and unmodeled plant disturbances. An augmented piecewise observer, constructed by solving some linear matrix inequalities, is used to estimate the system states and the lumped disturbances. Based on the reference from an online constrained target generator, the fuzzy model predictive control law can be easily obtained by solving a convex semi-definite programming optimization problem subject to several linear matrix inequalities. The resulting closed-loop system is guaranteed to be input-to-state stable even in the presence of observer estimation error. The zero offset output tracking property of the proposed control approach is proved, and subsequently demonstrated by the simulation results on a strongly nonlinear benchmark plant.

Piecewise Fuzzy Anti-Windup Dynamic Output Feedback Control of Nonlinear Processes With Amplitude and Rate Actuator Saturations

In this paper, a novel anti-windup dynamic output compensator is developed to deal with the robust H infin output feedback control problem of nonlinear processes with amplitude and rate actuator saturations and external disturbances. Via fuzzy modeling of nonlinear systems, the proposed piecewise fuzzy anti-windup dynamic output feedback controller is designed based on piecewise quadratic Lyapunov functions. It is shown that with sector conditions, robust output feedback stabilization of an input-constrained nonlinear process can be formulated as a convex optimization problem subject to linear matrix inequalities. Simulation study on a strongly nonlinear continuously stirred tank reactor (CSTR) benchmark plant is given to show the performance of the proposed anti-windup dynamic compensator.

Output Tracking of Piecewise-Linear Systems via Error Feedback Regulator With Application to Synchronization of Nonlinear Chua's Circuit

This paper considers the output tracking problem of general piecewise discrete-time linear systems via error feedback scheme. A number of sufficient conditions are obtained based on piecewise-quadratic Lyapunov functions in the framework of output regulation theory. The resulting closed-loop system is guaranteed to be stable and the output tracking is achieved asymptotically. Moreover, the proposed piecewise-linear model based regulator has been successfully applied to the chaos synchronization of general nonlinear Chuas circuits. Simulation results are also given to illustrate the performance and advantages of the proposed approach.

Medium-temperature plasma immersion-ion implantation of austenitic stainless steel

Conventional elevated-temperature plasma immersion-ion implantation (PIII) is usually conducted at 350°C, or above, to achieve a thick modified layer for practical engineering applications. In this paper, we focus on medium-temperature PIII treatment of SS304 stainless steel. Two experimental protocols: high frequency, low voltage (LV); and high voltage (HV), low frequency are evaluated. The samples are characterized by Auger electron spectroscopy, glancing angle X-ray diffraction (XRD), corrosion test, pin-on-disk friction and wear test, and so on, to determine the composition, phase structure, as well as the tribological properties of the modified layer. Our results indicate that PIII at 300°C not only improves the mechanical properties, but also the corrosion resistance. Comparison of the wear tracks shows that 300°C-PIII results in an 11-fold improvement in the surface-wear resistance. A procedure involving high implantation flux at LV is more favorable to the formation of a thick modified layer with a higher nitrogen concentration.

Microscopic Droplet Formation and Energy Transport Analysis of Condensation on Scalable Superhydrophobic Nanostructured Copper Oxide Surfaces

Utilization of nanotechnologies in condensation has been recognized as one opportunity to improve the efficiency of large-scale thermal power and desalination systems. High-performance and stable dropwise condensation in widely-used copper heat exchangers is appealing for energy and water industries. In this work, a scalable and low-cost nanofabrication approach was developed to fabricate superhydrophobic copper oxide (CuO) nanoneedle surfaces to promote dropwise condensation and even jumping-droplet condensation. By conducting systematic surface characterization and in situ environmental scanning electron microscope (ESEM) condensation experiments, we were able to probe the microscopic formation physics of droplets on irregular nanostructured surfaces. At the early stages of condensation process, the interfacial surface tensions at the edge of CuO nanoneedles were found to influence both the local energy barriers for microdroplet growth and the advancing contact angles when droplets undergo depinning. Local surface roughness also has a significant impact on the volume of the condensate within the nanostructures and overall heat transfer from the vapor to substrate. Both our theoretical analysis and in situ ESEM experiments have revealed that the liquid condensate within the nanostructures determines the amount of the work of adhesion and kinetic energy associated with droplet coalescence and jumping. Local and global droplet growth models were also proposed to predict how the microdroplet morphology within nanostructures affects the heat transfer performance of early-stage condensation. Our quantitative analysis of microdroplet formation and growth within irregular nanostructures provides the insight to guide the anodization-based nanofabrication for enhancing dropwise and jumping-droplet condensation performance.

Robust Model Predictive Control for Discrete-Time Takagi–Sugeno Fuzzy Systems With Structured Uncertainties and Persistent Disturbances

In this paper, robust model predictive control for uncertain discrete-time Takagi-Sugeno (T-S) fuzzy systems with input constraints and persistent disturbances is considered. The robust positively invariant set for T-S fuzzy systems is investigated. Based on this result, computation of the terminal constraint set is proposed, which is of crucial importance in the robust predictive controller design. A zero-step predictive controller is discussed first, which has a time-varying terminal constraint set. The recursive feasibility and input-to-state stability can be ensured. Then, a novel controller with N-step prediction is further proposed, which can be used to deal with the case of fixed terminal constraint set. The implementation of the N-step controller involves both online and offline computations. It is shown that a sequence of approximating robust one-step sets can be computed offline. Then, bisection searches are carried out online, as well as a constrained convex optimization problem. The N-step controller guarantees that the system state can be steered to the terminal constraint set in less than N-steps, if the initial state lies in a specific region. Simulation results are finally presented to show the effectiveness of the proposed controllers.