Robust Control of Permanent Magnet Synchronous Motors

In this paper, permanent magnet synchronous motors (PMSMs) are investigated. According to the feature of PMSMs, a novel state equation of PMSMs is obtained by choosing suitable state variables. Based on the state equation, robust controllers are designed via interval matrix and PI control idea. In terms of bilinear matrix inequations, sufficient conditions for the existence of the robust controller are derived. In order to reduce the conservation and the dependence on parameter, the control inputs of PMSMs are divided into two parts, a feedforward control input and a feedback control input, and relevant sufficient conditions for the existence of the controller are obtained. Because of the suitable choice of state variables, the proposed control strategies can cope with the load uncertainty and have robustness for disturbance. Finally, simulations are carried out via Matlab/Simulink soft to verify the effectiveness of the proposed control strategies. The performance of the proposed control strategies are demonstrated by the simulation results.      

A design of experiments investigation into dry separation using a Knelson Concentrator

Enhanced gravity, or centrifugal, separators have revolutionised gold processing over the past decades, significantly increasing the recovery of fine (−100 μm) free gold. One of the main drawbacks of centrifugal gravity concentrators is the large volume of water required (even if it is all recycled). With water becoming an ever increasingly important “commodity”, reducing this is of importance both from an environmental and a monetary point of view. This work investigated operating a laboratory scale Knelson Concentrator with a dry feed and using air as the fluidising medium. The feed used was a synthetic mixture of tungsten and quartz, used to mimic a gold ore. The response surface method and central composite design techniques were used to design the experiments and to model the results, with the experimental variables being the bowl speed (G-Level), air fluidising pressure and the feed rate. The models corresponded well to the experimental results, indicating that for this experimental setup, the optimal conditions were a bowl G-Level of 40 G, a feed rate of 220 g/min and an air fluidising pressure of 8 psi.     

Synthesis and characterization of a novel Ca-alginate-biochar composite as efficient zinc (Zn2+) adsorbent: Thermodynamics,process design,mass transfer and isotherm modeling

In this present work, Ca-alginate-biochar adsorbent has been synthesized, characterized and tested its effectiveness in the removal of aqueous phase Zn²⁺ metal. The removal efficiency was studied under various physicochemical process parameters. External mass transfer model, intraparticle diffusion model and pseudo-first-order and pseudo-second-order models were used to fit the experimental Zn²⁺ adoption kinetic results and to identify the mechanism of adsorption. The desorption studies indicate the possibilities of ion-exchange and physical–chemical adsorption of Zn^2+. The adsorption was best described by Langmuir isotherm model. Thermodynamic parameters suggested that the adsorption process becomes spontaneous, endothermic and irreversible in nature.     

Homogenization with uncertainty in Poisson ratio for polymers with rubber particles

The main aim of this work is dual computer analysis of probabilistic coefficients for the homogenized tensor of the polymer filled with the rubber particles having randomized Poisson ratios of both constituents. The major issue is to verify an influence of a randomness in rubber Poisson ratio close to the compressibility limit on the uncertainty of the effective tensor probabilistic characteristics. Probabilistic analysis presented here is carried out using mainly the stochastic perturbation technique provided by the common application of the traditional FEM commercial code ABAQUS and the symbolic computations package MAPLE. This FEM-based technique employs polynomial response function of the optimum order recovered from the weighted least squares method and following a set of deterministic solutions obtained for various values of the randomized input parameter. Optimization procedure is released entirely into a symbolic environment, where maximization of the correlation factor together with minimization of the fitting variance and approximation error are applied. Homogenization technique consists in equating of deformation energies for the real composite and the artificial one characterized by the effective elasticity tensor with uncertainty.     

Covariance matrix adaptation evolution strategy based design of fixed structure robust H∞ loop shaping controller

This paper proposes the application of Covariance Matrix Adaptation Evolution Strategy (CMA-ES) in fixed structure H_∞ loop shaping controller design. Integral Time Absolute Error (ITAE) performance requirement is incorporated as a constraint with an objective of maximization of stability margin in the fixed structure H_∞ loop shaping controller design problem. Pneumatic servo system, separating tower process and F18 fighter aircraft system are considered as test systems. The CMA-ES designed fixed structure H_∞ loop-shaping controller is compared with the traditional H_∞ loop shaping controller, non-smooth optimization and Heuristic Kalman Algorithm (HKA) based fixed structure H_∞ loop shaping controllers in terms of stability margin. 20% perturbation in the nominal plant is used to validate the robustness of the CMA-ES designed H_∞ loop shaping controller. The effect of Finite Word Length (FWL) is considered to show the implementation difficulties of controller in digital processors. Simulation results demonstrated that CMA-ES based fixed structure H_∞ loop shaping controller is suitable for real time implementation with good robust stability and performance.     

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.     

Novel thermal-sensitive properties of NBT-BZT composite ceramics for high-temperature NTC thermistors

We found for the first time that (1 − x) Na_0.5Bi_0.5TiO₃-xBiZn_0.5Ti_0.5O₃ (NBT–BZT) composite ceramics showed negative temperature coefficient (NTC) at a high temperature. The NBT–BZT nanopowders were successfully prepared by Pechini method. Their ceramics were sintered at 1100°C. The NBT–BZT ceramic exhibited a good linear relationship between logarithm of electrical resistivity (Inρ) and reciprocal of absolute temperature (1000/T) at 250°C–1050°C. The obtained ρ₆₀₀, ρ₉₀₀, and B_600/900 constants of the NBT–ZBT NTC thermistors are approximately 5.92 × 10⁶ to 3.01 × 10⁴ Ω cm, 7.03 × 10³ to 7.60 × 10² Ω cm and 2.3 × 10⁴-1.3 × 10⁴ K, respectively. The electrical characteristics can be tuned to the desired value by changing the Na_0.5Bi_0.5TiO₃ content in the compound. The electrical conductivity in these compounds is due to the electron jumps between Ti³⁺ and Ti⁴⁺ and oxygen-ion conductivity. Results demonstrate a tremendous potential of the studied system for perovskite materials with NTC performance.     

工艺参数对超声辅助脉冲电沉积镍-氮化钛复合镀层的影响

在45钢表面以超声波辅助脉冲电沉积制备Ni-TiN复合镀层。研究了平均阴极电流密度、脉冲占空比、超声功率和TiN粒子(平均直径20~30 nm)添加量对复合镀层的TiN粒子含量和显微硬度的影响。得到较优的工艺参数为:NiSO4ꞏ6H2O 300 g/L,NiCl2ꞏ6H2O 30 g/L,H3BO330 g/L,十二烷基硫酸钠0.3 g/L,TiN 25 g/L,pH 4.1~4.3,温度40°C,平均阴极电流密度4 A/dm2,脉冲占空比40%,脉冲频率1000 Hz,超声功率300 W,机械搅拌速率200 r/min,时间60 min。该条件下所得Ni-TiN复合镀层的TiN质量分数为8.35%,显微硬度为819 HV,表面平整、致密,晶粒尺寸均匀。     

高密度聚乙烯/铅硼复合材料屏蔽性能和力学性能研究

研究了高密度聚乙烯/铅硼复合材料的屏蔽性能和力学性能，通过屏蔽仿真比较了密度及碳化硼（B4C）含量对屏蔽性能的影响，通过试验比较了B4C含量对屏蔽性能、弯曲强度及冲击强度的影响。仿真结果表明,随聚乙烯/铅硼复合材料密度升高，快中子屏蔽性能下降，热中子屏蔽性能和γ屏蔽性能提高；保持聚乙烯/铅硼复合材料密度不变，随B4C含量的提高，中子屏蔽性能提高而γ屏蔽性能下降;实验数据表明,随B4C含量的升高，高密度聚乙烯/铅硼材料的快中子屏蔽性能、热中子屏蔽性能升高，γ屏蔽系数下降，冲击强度和弯曲强度下降明显，屏蔽性能测试结果和仿真结果规律性相符；综合仿真结果和实验数据表明，含B4C 2 %左右的高密度聚乙烯/铅硼复合材料同时具有较好的屏蔽性能和力学性能。