Optimal filtering and control for wireless networked closed-loop control systems

This article studies the optimal filtering and control for wireless networked control systems (WNCSs). In WNCSs, packets may be lost in both control and feedback channels and user datagram protocol is usually used to improve the performance of the real-time control. Relevant literature indicates that the conventional optimal filtering for such a system cannot be applied in practice due to the complex calculation with Gaussian mixtures. This paper proposes a novel scheme to realize the optimal filtering and the linear quadratic Gaussian control for WNCSs, in which the controlled node performs a local estimation and the remote-control node performs the final estimation and control, and a synchronization of two estimators is guaranteed by a communication mechanism. An optimal filtering algorithm is developed, the stability condition of the filtering error covariance is obtained, optimal finite-horizon and infinite-horizon control are derived, and the stability of the closed-loop control system is proved. Numerical simulations show the validity and feasibility of the theoretical results.     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

Mechanophysical Cues in Extracellular Matrix Regulation of Cell Behavior

The extracellular matrix (ECM) is a macromolecular network that can provide biochemical and structural support for cell adhesion and formation. It regulates cell behavior by influencing biochemical and physical cues. It is a dynamic structure whose components are modified, degraded, or deposited during connective tissue development, giving tissues strength and structural integrity. The physical properties of the natural ECM environment control the design of naturally or synthetically derived biomaterials to guide cell function in tissue engineering. Tissue engineering is an important field that explores physical cues of the ECM to produce new viable tissue for medical applications, such as in organ transplant and organ recovery. Understanding how the ECM exerts physical effects on cell behavior, when cells are seeded in synthetic ECM scaffolds, is of utmost importance. Herein we review recent findings in this area that report on cell behaviors in a variety of ECMs with different physical properties, i.e., topology, geometry, dimensionality, stiffness, and tension.     

An airlight estimation method for image dehazing based on gray projection

Multimedia Tools and Applications - As the key parameter of dehazing algorithms, airlight value directly affect the calculation accuracy of sky region, and any deviation will lead to the chromatic...     

Effects of hydrolysis of precursor on the structures and properties of polymer-derived SiBN ceramic fibers

In this paper, polyborosilazane precursor was synthesied from HMDZ, HSiCl₃, BCl₃ and CH₃NH₂ using a multistep method. By controlling the storage conditions, parts of the polyborosilazane fibers were hydrolyzed. FT-IR, NMR, XRD, TEM and monofilament tensile strength test were employed to study the effects of hydrolysis of precursor on the structures and properties of polymer-derived SiBN ceramic fibers. FT-IR and NMR results indicate that Si-N group in PBSZ reacts with H₂O to form Si-O-Si group. After pyrolysis reaction at 1400℃, Si-O-Si group will finally transformed into highly ordered cristobalite and β-quartz, resulting in formation of the wrinkled surface of the obtained SiBN ceramic fiber. The strip-like defects on fiber surface, according to monofilament tensile strength test, had a significant effect on mechanical property of the obtained SiBN ceramic fiber and caused no increase in fiber tensile strength of hydrolytic polyborosilazane fiber before and after pyrolytic process.     

A dense and compact laser cladding layer with solid metallurgical bonding significantly improved corrosion resistance of Mg alloy for engineering applications

Although Mg alloy attracts great attention for engineering applications because of high specific strength and low density, low corrosion resistance limits its extensive use. In this study, Mg–Al–Zn–Mn alloy was treated via a laser cladding process to generate a dense and compact laser cladding layer with solid metallurgical bonding on the substrate for improving corrosion resistance, effectively hindering the corrosion pervasion into Mg alloy. The corrosion current density declined from 103 μA/cm² for Mg alloy to 13 μA/cm² for the laser cladding layer in NaCl aqueous solution. Moreover, the laser cladding layer was slightly corroded in comparison with Mg alloy in NaCl aqueous solution. Besides, the microhardness of the cladding layer reached a mean value of 170.5 HV, 3.1 times of Mg alloy (56.8 HV) due to the in situ formation of hardening intermetallic phases. Wear resistance of laser cladding layer was also obviously improved. These results demonstrated that the laser cladding layer obviously enhanced anticorrosion property of Mg alloy for engineering applications.     

Improving storability,physiological disorders,and antioxidant properties of ‘Bartlett’ and ‘d’Anjou’ pears (Pyrus communis L.) by pre-harvest 1-methylcyclopropene spraying

Ethylene continues to be a major factor influencing quality of European pears during storage. Although research has been done on the effect of pre-harvest 1-methylcyclopropene (1-MCP) on physiological characteristics in pears, a full understanding of cultivar response and antioxidant metabolism remains elusive. Spraying 1-MCP on ‘Bartlett’ and ‘d’Anjou’ pears was studied with respect to physiology, storage and eating quality, disorders, and antioxidant properties at two harvest date (H1 and H2) during storage and ripening. Treatment with 1-MCP extended the harvest window of ‘Bartlett’ and ‘d’Anjou’ pears 3 and 4 days, respectively, without reducing storage or eating quality. Treatment with 1-MCP reduced ethylene production (EPR) and respiration rates (RR), maintained fruit firmness and green colour during storage and retarded development of desirable melting texture in both cultivars. Additionally, 1-MCP lowered the incidence of disorders by alleviating membrane lipid peroxidation, retaining high total flavonoids (TF) and antioxidant capacity, and enhancing superoxide dismutase (SOD), catalase (CAT) and ascorbate peroxidase (APX) activity in both cultivars. Overall, pre-harvest 1-MCP applications could extend storage time of ‘Bartlett’ and ‘d’Anjou’ pears to 5 and 6 months, respectively, at −1.1 ± 0.5 °C, by reducing ethylene synthesis and enhancing antioxidant metabolism.     

Reoptimization framework and policy analysis for maritime inventory routing under uncertainty

We study a maritime inventory routing problem, in which shipments between production and consumption nodes are carried out by a fleet of vessels. The vessels have specific capacities and can be chartered under different agreements. The inventory levels of all consumption nodes and some production nodes should be maintained within specified bounds; for the remaining production nodes, orders should be picked up within pre-defined time windows. We propose a discrete-time mixed-integer programming model. In the face of new information and uncertainty, this optimization model has to be re-solved, as the horizon is rolled forward. We discuss how to account for different sources of uncertainty. We present a rolling-horizon reoptimization framework that allows us to study different policies that impact the quality of the implemented solution, so we can identify the optimal set of policies.