基于Matlab的制芯机器人夹持器稳定性研究与分析

由于铸造厂制芯机器人的工作环境恶劣,机器人抓取砂芯的稳定性较差,时常出现掉砂芯、夹伤砂芯的问题。针对上述问题建立以夹持器、气压、机械振动的系统数学模型,采用高阶系统极点在[s]平面的分布法来判定该系统的稳定性。在确保高阶系统极点值不变的情况下,通过改变系统的零点值来观察零点值对系统稳定性、振荡衰减时间的影响。用Matlab的pzmap和impulse函数分别对系统的零点、极点分布和零点值的不同对系统响应进行仿真,运用仿真结果与现场试验进行优化参数,结果表明采用一种刚度与柔度各为1/2的夹持器对制芯机器人的稳定性具有较好优化效果。     

Improved synergetic excitation control for transient stability enhancement and voltage regulation of power systems

This paper proposes decentralized improved synergetic excitation controllers (ISEC) for synchronous generators to enhance transient stability and obtain satisfactory voltage regulation performance of power systems. Each generator is considered as a subsystem, for which an ISEC is designed. According to the control objectives, a manifold, which is a linear combination of the deviation of generator terminal voltage, rotor speed and active power, is chosen for the design of ISEC. Compared with the conventional synergetic excitation controller (CSEC), a parameter adaptation scheme is proposed for updating the controller parameter online in order to improve the transient stability and voltage regulation performance simultaneously under various operating conditions. Case studies are undertaken on a single-machine infinite-bus power system and a two-area four-machine power system, respectively. Simulation results show the ISEC can provide better damping and voltage regulation performance, compared with the CSEC without parameter adaptation scheme and the conventional power system stabilizer.     

生姜主要病虫害及其防治技术分析

生姜的根状茎为使用部分,其中包含姜油酮、姜油醇、姜油酚、蛋白质、粗脂肪、糖,并且钙、铁的含量也较为丰富,是人们日常生活当中不可或缺的调味品,还能够加工成为姜片、糖姜片和盐姜片等诸多食品,其在医药方面的应用也较为广泛,备受人们的推崇与喜爱。我国在生姜栽培方面的历史较为悠久,技术也较为成熟,每年生姜出口贸易都能为我国带来非常可观的经济效益。     

轨道式垃圾回收机器人设计与分析

针对高速公路高峰期拥挤产生的垃圾等问题,设计一种轨道式垃圾回收机器人,由光伏发电装置、机器人壳体、末端手爪、关节臂以及控制系统等组成,主体结构采用双臂三关节结构,采用西门子PLC控制系统,通过控制关节臂的旋转以及偏转、末端手爪的旋转及开合等动作来实现工作的目的。结合外场作业的特殊性,采用光伏能源装置,对其结构及控制系统进行设计,通过对机器人进行三维建模、运动和控制仿真分析,验证系统的可行性及有效性。     

Filtered adaptive constrained sampled-data control for uncertain multivariable nonlinear systems

A filtered adaptive constrained sampled-data controller for uncertain multivariable nonlinear systems in the presence of various constraints is synthesized in this paper. A piecewise constant adaptive law drives that estimation error dynamics to zero at each sampling time instant yields adaptive parameters. The filtered control scheme consists of two components. Based on an estimation/cancellation strategy, a disturbance rejection control law is designed to compensate the nonlinear uncertainties within the bandwidth of low-pass filters, whereas a constraint violation avoidance control law is designed to solve an online constrained optimization problem. Although a reduced sampling time helps to minimize the estimation error caused by the neglect of unknowns, the resulting aggressive signals put more restrictions on the control law. Greater sacrifice of tracking performance is required to satisfy the constraints. The constraints violation avoidance control law is in favor of a larger sampling time. Sufficient conditions are given to guarantee the stability of the closed-loop system with the sampled-data controller, where the input/output signals are held constant over the sampling period. Numerical examples are provided to validate the theoretical results, comparisons between the constrained sampled-data controller and unconstrained adaptive controller with the implementation of different sampling times are carried out.     

NH2-MCM-41的改性及其pH响应性释药的研究

采用正硅酸乙酯（TEOS）和3-氨丙基三乙氧基硅烷（APTES）通过共缩聚法合成介孔二氧化硅（MCM-41）。首先对其氨基修饰，再通过有机合成接枝—R基团（—R：—CHO、—OH、—CH₃、—COOH），制备得到Me-Ph-NH-MCM-41、OHC-Ph-NH-MCM-41、HO-Ph-NH-MCM-41、HOOC-Ph-NH-MCM-41四种不同的药物载体。利用FT-IR、Zeta电位、XRD和SEM对其结构和形貌表征，结果表明NH₂-MCM-41改性成功。以罗丹明B（RhB）为模型进行载药性能测试，并考察了此释药系统在模拟不同pH的体液下的敏感释药行为，同时探究了不同—R基团对释药的影响。结果显示，四种载体在中性条件下几乎不发生药物释放，通过改变环境体系pH可以有效控制药物释放，其释药行为可以用Korsmeyer-Peppas动力学模型来描述。实验表明，释药量：RhB@HOOC-Ph-NH-MCM-41>RhB@OHC-Ph-NH-MCM-41>RhB@HO-Ph-NH-MCM-41>RhB@Me-Ph-NH-MCM-41，不同—R基团的药物载体的pH响应性不同，其中RhB@HOOC-Ph-NH-MCM-41释药量在pH=1.2时可达57.87%，在用于药物智能控释材料方面具有一定的应用潜力。     

Three-phase four-wire shunt active power filter based on the SOGI filter and Lyapunov function for DC bus control

The three-phase four-wire shunt active power filter (SAPF) was developed to suppress the harmonic currents generated by nonlinear loads, and for the compensation of unbalanced nonlinear load currents, reactive power, and the harmonic neutral current. In this work, we consider instantaneous reactive power theory (PQ theory) for reference current identification based on the following two algorithms: the classic low-pass filter (LPF) and the second-order generalized integrator (SOGI) filter. Furthermore, since an important process in SAPF control is the regulation of the DC bus voltage at the capacitor, a new controller based on the Lyapunov function is also proposed. A complete simulation of the resultant active filtering system confirms its validity, which uses the SOGI filter to extract the reference currents from the distorted line currents, compared with the traditional PQ theory based on LPF. In addition, the simulation performed also demonstrates the superiority of the proposed approach, for DC bus voltage control based on the Lyapunov function, compared with the traditional proportional-integral (PI) controller. Both novel approaches contribute towards an improvement in the overall performance of the system, which consists of a small rise and settling time, a very low or nonexistent overshoot, and the minimization of the total harmonic distortion (THD).     

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.      

Superior foetal electrocardiogram signal elicitation using a novel artificial intelligent Bayesian methodology

Innumerable casualties due to intrauterine hypoxia are a major worry during prenatal phase besides advanced patient monitoring with latest science and technology. Hence, the analysis of foetal electrocardiogram (fECG) signals is very vital in order to evaluate the foetal heart status for timely recognition of cardiac abnormalities. Regrettably, the latest technology in the cutting edge field of biomedical signal processing does not seem to yield the desired quality of fECG signals required by physicians, which is the major cause for the pathetic condition. The focus of this work is to extort non-invasive fECG signal with highest possible quality with a motive to support physicians in utilizing the methodology for the latest intrapartum monitoring technique called STAN (ST analysis) for forecasting intrapartum foetal hypoxia. However, the critical quandary is that the non-invasive fECG signals recorded from the maternal abdomen are affected by several interferences like power line interference, baseline drift interference, electrode motion interference, muscle movement interference and the maternal electrocardiogram (mECG) being the dominant interference. A novel hybrid methodology called BANFIS (Bayesian adaptive neuro fuzzy inference system) is proposed. The BANFIS includes a Bayesian filter and an adaptive neuro fuzzy filter for mECG elimination and non-linear artefacts removal to yield high quality fECG signal. Kalman filtering frame work has been utilized to estimate the nonlinear transformed mECG component in the abdominal electrocardiogram (aECG). The adaptive neuro fuzzy filter is employed to discover the nonlinearity of the nonlinear transformed version of mECG and to align the estimated mECG signal with the maternal component in the aECG signal for annulment. The outcomes of the investigation by the proposed BANFIS system proved valuable for STAN system for efficient prediction of foetal hypoxia.     

Study on maximum power point tracking of photovoltaic array in irregular shadow

Traditional maximum power point tracking (MPPT) methods can hardly find global maximum power point (MPP) because output characteristics curve of photovoltaic (PV) array may have multi local maximum power points in irregular shadow, and thus easily fall into the local maximum power point. To address this drawback, Considering that sliding mode variable structure (SMVS) control strategy have such advantages as simple structure, fast response and strong robustness, and P&O method have the advantages of simple principle and convenient implementation, so a new algorithm combining SMVS control method and P&O method is proposed, besides, PI controller is applied to reduce system chattering caused by switching sliding surface. It is applied to MPPT control of PV array in irregular shadow to solve the problem of multi-peak optimization in partial shadow. In order to verity the rationality of the proposed algorithm, the experimental circuit is built, which achieves MPPT control by means of the proposed algorithm and P&O method. The experimental results show that compared with the traditional P&O algorithm, the proposed algorithm can fast track the global MPP, tracking speed increases by 60% and the relative error decreased by 20%. Moreover, the system becomes more stable near the MPP, the fluctuations of output power is greatly reduced, and thus make full use of solar energy.