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To overcome the deficiencies addressed in the conventional PID control and improve the dynamic performance and robustness of the system, a simple design and parameters tuning approach of internal model control-PID (IMC-PID) controller was proposed for the first order plus time-delay (FOPTD) process and the second order plus time-delay (SOPTD) process. By approximating the time-delay term of the process model with the first-order Taylor series, the expressions for IMC-PID controller parameters were derived, and they had only one adjustable parameter λ which was directly related to the dynamic performance and robustness of the system. Moreover, an analytical approach of selecting λ was given based on the maximum sensitivity M s . Then, the robust tuning of the system could be achieved according to the value of M s . In addition, the proposed method could be extended to the integrator plus time-delay (IPTD) process and the first order delay integrating (FODI) process. Simulation studies were carried out on various processes with time-delay, and the results show that the proposed method could provide a better dynamic performance of both the set-point tracking and disturbance rejection and robustness against parameters perturbation.

A lattice Boltzmann method is developed for the direct numerical simulation of gas, liquid, and solid three-phase flows. The liquid–gas two-phase flow with a high density ratio is solved using a phase-field model where the interface evolution is described by the conservative Allen–Cahn equation, and the dynamics of the solid particle is captured by the momentum exchange method. By distributing the surface tension over the entire diffuse interface, a new model is proposed to account for the capillary force exerted on the particle, which not only is suited for curved boundaries but can also be implemented in a simple and accurate manner. Several typical benchmark cases, including the wetting behavior of a particle on the liquid–gas interface, a bubble adhering to a particle that can move freely, and the sinking of a horizontal cylinder through an air–water interface, are used to validate the present method. Results show the necessity to incorporate the capillary force on the contact lines, especially when the surface tension is a dominant factor, and that the new capillary force model is able to calculate the capillary force accurately and suppress the oscillations of the capillary force. In addition, the capability of the present method for particle interactions is further demonstrated by studying the self-assembling behavior of three hydrophilic particles on a liquid–gas interface.

Recently, fractional order (FO) processes with dead-time have attracted more and more attention of many researchers in control field, but FO-PID controllers design techniques available for the FO processes with dead-time suffer from lack of direct systematic approaches. In this paper, a simple design and parameters tuning approach of two-degree-of-freedom (2-DOF) FO-PID controller based on internal model control (IMC) is proposed for FO processes with dead-time, conventional one-degree-of-freedom control exhibited the shortcoming of coupling of robustness and dynamic response performance. 2-DOF control can overcome the above weakness which means it realizes decoupling of robustness and dynamic performance from each other. The adjustable parameter η2 of FO-PID controller is directly related to the robustness of closed-loop system, and the analytical expression is given between the maximum sensitivity specification Ms and parameters η2. In addition, according to the dynamic performance requirement of the practical system, the parameters η1 can also be selected easily. By approximating the dead-time term of the process model with the first-order Padé or Taylor series, the expressions for 2-DOF FO-PID controller parameters are derived for three classes of FO processes with dead-time. Moreover, compared with other methods, the proposed method is simple and easy to implement. Finally, the simulation results are given to illustrate the effectiveness of this method.

Background Mild cognitive impairment (MCI) occurs frequently in many end stage renal disease (ESRD) patients, may significantly worsen survival odds and prognosis. However, the exact neuropathological mechanisms of MCI combined with ESRD are not fully clear. This study examined functional connectivity (FC) alterations of the default-mode network (DMN) in individuals with ESRD and MCI. Methods Twenty–four individuals with ESRD identified as MCI patients were included in this study; of these, 19 and 5 underwent hemodialysis (HD) and peritoneal dialysis (PD), respectively. Another group of 25 age-, sex- and education level-matched subjects were recruited as the control group. All participants underwent resting-state functional MRI and neuropsychological tests; the ESRD group underwent additional laboratory testing. Independent component analysis (ICA) was used for DMN characterization. With functional connectivity maps of the DMN derived individually, group comparison was performed with voxel-wise independent samples t-test, and connectivity changes were correlated with neuropsychological and clinical variables. Results Compared with the control group, significantly decreased functional connectivity of the DMN was observed in the posterior cingulate cortex (PCC) and precuneus (Pcu), as well as in the medial prefrontal cortex (MPFC) in the ESRD group. Functional connectivity reductions in the MPFC and PCC/Pcu were positively correlated with hemoglobin levels. In addition, functional connectivity reduction in the MPFC showed positive correlation with Montreal Cognitive Assessment (MoCA) score. Conclusion Decreased functional connectivity in the DMN may be associated with neuropathological mechanisms involved in ESRD and MCI.

Surfactants are widely used in many industrial processes, where the presence of surfactants not only reduces the interfacial tension between fluids but also alters the wetting properties of solid surfaces. To understand how the surfactants influence the droplet motion on a solid surface, a hybrid method for interfacial flows with insoluble surfactants and contact-line dynamics is developed. This method solves immiscible two-phase flows through a lattice Boltzmann colorgradient model and simultaneously solves the convection− diffusion equation for surfactant concentration through a finite difference method. In addition, a dynamic contact angle formulation that describes the dependence of the local contact angle on the surfactant concentration is derived, and the resulting contact angle is enforced by a geometrical wetting condition. Our method is first used to simulate static contact angles for a droplet resting on a solid surface, and the results show that the presence of surfactants can significantly modify surface wettability, especially when the surface is more hydrophilic or more hydrophobic. This is then applied to simulate a surfactantladen droplet moving on a substrate subject to a linear shear flow for varying effective capillary number (Ca e ), Reynolds number (Re), and surface wettability, where the results are often compared with those of a clean droplet. For varying Ca e , the simulations are conducted by considering a neutral surface. At low values of Ca e , the droplet eventually reaches a steady deformation and moves at a constant velocity. In either a clean or surfactant-laden case, the moving velocity of the droplet linearly increases with the moving wall velocity, but the slope is always higher (i.e., the droplet moves faster) in the surfactantladen case where the droplet exhibits a bigger deformation. When Ca e is increased beyond a critical value (Ca e,c ), the droplet breakup would happen. The presence of surfactants is found to decrease the value of Ca e,c , but it shows a non-monotonic effect on the droplet breakup. An increase in Re is able to increase not only droplet deformation but also surfactant dilution. The role of surfactants in the droplet behavior is found to greatly depend upon the surface wettability. For a hydrophilic surface, the presence of surfactants can decrease the wetting length and enables the droplet to reach a steady state faster; while for a hydrophobic surface, it increases the wetting length and delays the departure of the droplet from the solid surface.

In this paper, a lattice Boltzmann method is developed to simulate two-phase flows with soluble surfactants in complex porous media. This method not only can recover the Langmuir adsorption isotherm when the bulk surfactant concentration is relatively low but also allows the surfactant concentration to exceed the critical micelle concentration. Thanks to its versatility, this method is used to study the influence of surfactants on steady-state fluid distributions, specific interfacial lengths (SILs), and relative permeabilities under different wetting fluid (WF) saturations (S w) and viscosity ratios (M) of WF to non-WF (NWF). Regardless of the values of S w and M, the SIL between two fluids and the SIL between a grain surface and WF are always higher in a surfactant-laden system than in a clean system, while the SIL between a grain surface and NWF is always lower in a surfactant-laden system. For M = 1, we find that the addition of surfactants dramatically increases the relative permeability (RP) of NWF but slightly decreases the RP of WF. By adjusting M at S w = 0.5, the RP of NWF is always higher in a surfactant-laden system than in a clean system, while the relative magnitude of the WF relative permeabilities in both systems depends on M: for M < 1, the RP of WF in a surfactant-laden system is higher, whereas for M ≥ 1, the RP of WF in a clean system is higher.

The dynamic model of overhead crane is highly nonlinear and uncertain. In this paper, Takagi-Sugeno (T-S) fuzzy modeling and PSO-based robust linear quadratic regulator (LQR) are proposed for anti-swing and positioning control of the system. First, on the basis of sector nonlinear theory, the two T-S fuzzy models are established by using the virtual control variables and approximate method. Then, considering the uncertainty of the model, robust LQR controllers with parallel distributed compensation (PDC) structure are designed. The feedback gain matrices are obtained by transforming the stability and robustness of the system into linear matrix inequalities (LMIs) problem. In addition, particle swarm optimization (PSO) algorithm is used to overcome the blindness of LQR weight matrix selection in the design process. The proposed control methods are simple, feasible, and robust. Finally, the numeral simulations are carried out to prove the effectiveness of the methods.