Capillary Electrophoretic Separation of Proteins under the Control of Radial Electric Field

Separation of basic proteins was performed using a homemade field-modulated capillary electrophoresis system. The resolution. elution and even wall adsorption can be regulated by ad-lusting the radial rather than axial voltage applied. Selection of running buffer and pH was found to be critical.

System Design of a Reference Model Adaptive Control for Radial Plasma Position on HL-2A Tokamak

The design of the control system for radial plasma position on HL-2A based on model reference adaptive control (MRAC) principle is presented in this paper. The simulated results show that it can be used to improve the performance of the system greatly. Compared with the classical PID control system, it has obvious advantages in the better dynamic response, the smaller quantity of calculation and the better robustness.

Maximum power point tracking of a photovoltaic energy system using neural fuzzy techniques

In order to improve the output efficiency of a photovoltaic （PV） energy system, the real-time maximum power point （MPP） of the PV array should be tracked closely. The non-linear and time-variant characteristics of the photovoltaic array and the non-linear and non-minimum phase characteristics of a boost converter make it difficult to track the MPP as in traditional control strategies. A neural fuzzy controller （NFC） in conjunction with the reasoning capability of fuzzy logical systems and the learning capability of neural networks is proposed to track the MPP in this paper. A gradient estimator based on a radial basis function neural network is developed to provide the reference information to the NFC. With a derived learning algorithm, the parameters of the NFC are updated adaptively. Experimental results show that, compared with the fuzzy logic control algorithm, the proposed control algorithm provides much better tracking performance.

Radial basis function‐based exoskeleton robot controller development

The realisation of a model‐based controller for a robot with a higher degree of freedom requires a substantial amount of computational power.A high‐speed CPU is required to maintain a higher sampling rate.Multicore processors cannot boost the performance or reduce the execution time as the programs are sequentially structured.The neural network is a great tool to convert a sequentially structured program to an equivalent parallel architecture program.In this study,a radial basis function(RBF)neural network is developed for controlling 7 degrees of freedom of the human lower extremity exoskel-eton robot.A realistic friction model is used for modelling joint friction.High trajectory tracking accuracies have been obtained.Evidence of computational efficiency has been observed.The stability analysis of the developed controller is presented.Analysis of variance is used to assess the controller's resilience to parameter variation.To show the effectiveness of the developed controller,a comparative study was performe between the developed RBF network‐based controller and Sliding Mode Controller,Computed Tor-que Controller,Adaptive controller,Linear Quadratic Regulator and Model Reference Computed Torque Controller.

Creation of radially polarized optical fields with multiple controllable parameters using a vectorial optical field generator

A vectorial optical field generator(VOF-Gen) based on two reflective phase-only liquid crystal spatial light modulators enables the creation of an arbitrary optical complex field. In this work, the capabilities of the VOF-Gen in terms of manipulating the spatial distributions of phase, amplitude, and polarization are experimentally demonstrated by generating a radially polarized optical field consisted of five annular rings, the focusing properties of which are also numerically studied with vectorial diffraction theory. By carefully adjusting the relative amplitude and phase between the adjacent rings, an optical needle field with purely longitudinal polarization can be produced in the focal region of a high numerical aperture lens. The versatile method presented in this work can be easily extended to the generation of a vectorial optical field with any desired complex distributions.