基于PI建模和反步滑模控制的主动波浪补偿策略

海上起重船受风、浪、涌影响会产生剧烈的船舶姿态变化,造成起重机和货物的位姿变化,对货物和人员存在安全隐患,波浪补偿平台的稳定性控制能有效减少复杂海况下船舶运动对海上作业安全性、稳定性和精准性的影响,对浮式起重船海上设备精准装载作业极其重要。针对补偿平台的迟滞非线性导致的建模困难和控制不精确问题,本文提出基于PI(Prandtle–Ishlinskii)建模和反步滑模控制的主动波浪补偿策略。首先,通过实验得到补偿系统的迟滞效应曲线,分析系统迟滞环建立PI迟滞模型,并采用递推最小二乘法辨识模型的各个参数,从而求得系统模型。然后,基于李雅普诺夫(Lyapunov)稳定性设计反步控制补偿方法,并结合滑模控制规律加快初始控制速度。最后,将反步滑模法应用于补偿系统,采用MATLAB软件仿真在规则波和不规则波下的响应来验证算法和模型的正确性,并在工控机中用C#编写控制程序,驱动运动控制卡控制伺服电机带动电缸进行补偿运动,同时通过传感器采集系统运动的实时数据,并反馈给工控机形成闭环,以期验证补偿平台在补偿规则波和不规则波下的补偿效果。实验结果表明,所建立的斯图尔特(Stewart)浮式平台中,PI迟滞模型具有良好的精度,反步终端滑模控制算法在Stewart平台的实际控制中能够很好地补偿波浪运动,相比比例–积分–微分控制(PID)、反步法、强化学习等控制方法,反步终端滑模方法能快速较好跟踪期望位移,补偿精度达到0.9729。

DAB储能变换器双闭环模型预测控制与PI补偿控制策略研究

针对直流微电网中分布式电源输入输出功率不稳定造成的直流母线电压波动问题,鉴于双有源桥(DAB)储能变换器具有能量双向流动的特点,提出一种基于内模原理的双闭环模型预测控制策略。在分析DAB变换器扩展移相调制原理与特性基础上,重点研究电压外环和电流内环的模型预测控制策略。针对模型预测控制性能依赖电路参数准确度问题,分别从电路主要参数失配对功率传输和直流母线稳压的影响两个角度出发,深入分析模型参数敏感度。最终设置直流母线电压稳态误差灵敏度区,在误差灵敏度区外仅采用双闭环模型预测控制以保证系统的动态响应性能,在误差灵敏度区内采用双闭环模型预测控制和PI补偿控制以消除系统稳态误差。搭建实验平台进行实验验证,结果表明:在系统受到扰动时,DAB储能变换器可实现快速地充放电对系统进行补偿,混合控制策略可快速保持母线电压的稳定,实现系统功率均衡,增强系统抗扰能力。

高压输电线软体巡检机器人磁致动机制及PI滑模控制研究

为解决高压输电线刚性悬臂巡检机器人尺寸大、笨重、越障不灵活、效率低等问题,设计一种高压磁致动软体巡检机器人,利用载流线圈在高压直流环形磁场中受到的安培力驱动软体机器人以柔顺和蠕动方式高效灵活地跨越多种障碍物。对该机器人进行本体构型设计并分析其工作姿态,实现稳定巡检功能;对磁致动驱动器进行理论设计和分析,利用Comsol仿真软件对其所需驱动力进行仿真,验证理论的可实行性;通过拉格朗日法对高压磁致动软体巡检机器人进行动力学建模,构建系统动力学方程,获取机器人的关节角度、速度、加速度之间的关系;最后,通过MATLAB利用基于PI滑模控制法对简化后的高压磁致动软体巡检机器人动力学模型实行速度和角速度高精度追踪仿真。仿真结果表明:在滑模控制下,角度在1.5 s追踪上理想信号,角速度在0.3 s后追上理想信号,证明基于PI的滑模控制器能够实现对高压磁致动软体巡检机器人的有效控制。

Adaptive Optimal Discrete-Time Output-Feedback Using an Internal Model Principle and Adaptive Dynamic Programming

In order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming(ADP) technique based on the internal model principle(IMP). The proposed method, termed as IMP-ADP, does not require complete state feedback-merely the measurement of input and output data. More specifically, based on the IMP, the output control problem can first be converted into a stabilization problem. We then design an observer to reproduce the full state of the system by measuring the inputs and outputs. Moreover, this technique includes both a policy iteration algorithm and a value iteration algorithm to determine the optimal feedback gain without using a dynamic system model. It is important that with this concept one does not need to solve the regulator equation. Finally, this control method was tested on an inverter system of grid-connected LCLs to demonstrate that the proposed method provides the desired performance in terms of both tracking and disturbance rejection.

基于自适应PI模型的压电陶瓷驱动器精密定位方法

由于具备较高的定位精确度,压电陶瓷驱动器在超精密加工、微纳米测试等领域应用广泛,然而压电陶瓷固有的迟滞性严重影响其定位精确度。研究了驱动范围对压电陶瓷驱动器迟滞性的影响,实验得出迟滞性随驱动范围增大而显著。而在压电陶瓷驱动器的实际应用中,驱动范围是其主要的设置参数之一。为此,提出基于自适应Prandtle-Ishlinskii(PI)模型的拟合方法,根据不同驱动范围下获得的迟滞曲线的斜率变化趋势设置分段区间,采用二次规划算法辨识PI模型的权重参数,基于分段区间对迟滞曲线进行拟合,大大提高了拟合精确度。设计基于自适应PI模型的逆模型作为前馈控制器对压电陶瓷驱动器进行迟滞补偿,并搭建基于Labview的实验平台验证了该算法的可行性。实验结果表明,基于自适应PI逆模型的前馈控制器将压电陶瓷驱动器的定位精确度提高至1.8 nm。

基于PIS的综采工作面巷道监控中心工业设计

为提升国产智能制造装备的品牌竞争力,研究适合智能化转型升级、兼顾外观设计和价值塑造的产品形象系统(PIS)设计方法。首先,遵循品牌认知过程,提出基于认知心理学的PIS设计层次模型,从低到高依次是识别层、体验层和记忆层,并给出相应的评价指标;其次,顺应智能制造的发展趋势,明确面向智能制造装备PIS设计的基本流程及其所需考虑的要素;最后,以煤矿综采工作面巷道监控中心的工业设计为例,应用所提出的方法进行企业创新设计实践,塑造独特、高效、值得信赖的产品形象,并大幅提升品牌形象,可为智能制造装备的工业设计提供理论参考及实例借鉴。

无速度传感器的异步电动机模糊自适应PI直接转矩控制

文章针对传统无速度传感器直接转矩控制转速不稳定、超调量大等问题做出两点改进。首先,引入自耦PI对传统MRAS无速度传感器直接转矩控制进行改进,该方法改善无传感器直接转矩控制调速性能、降低超调量、减小稳态误差;其次,针对直接转矩控制具有转矩脉动大、调速性能差等缺点,提出变论域静态模糊自适应PI控制策略,减小转矩脉动并改善调速性能,大大提升了抗负载能力;最后,在Matlab/Simulink仿真环境下进行了仿真并进行分析,证明了上述方法的有效性和可行性。结果表明,相对于传统的无速度传感器直接转矩控制系统,仿真结果显示减小了转速超调量,缩短了转速上升中到达高速工况的响应时间,提升了抗负载能力。

基于模型变结构PI的BLDC电机驱动液压泵的压力控制

在自动变速箱液压控制的应用中,滑阀板液压系统存在控制精度差、多参数耦合、系统模型难以建立等缺陷。文章提出基于模型变结构比例积分(PI)的直流无刷(BLDC)电机驱动液压泵的压力控制策略,将直流无刷电机动态特性好、控制精度高等优点与液压泵结构简单、可靠性好等特点相结合。根据液压泵的转速、流量、压力特性关系和油液温度、黏度、弹性模量等参数建立电机转速比例积分控制模型,通过较易控制的电机驱动占空比信号实现对液压泵输出压力的调节。控制系统通过变结构比例积分控制,消除压力偏差和超调量,提高系统精度。仿真结果表明,变结构比例积分控制具有可行性,而试验结果证明,模型控制的系统响应优于纯比例积分闭环控制,并且具有很好的抗负载扰动能力。

Robust Stability of Nonlinear Plants with a Non-symmetric Prandtl-Ishlinskii Hysteresis Model

In this paper, robust stability of nonlinear plants represented by non-symmetric Prandtl-Ishlinskii （PI） hysteresis model is studied. In general, PI hysteresis model is the weighted superposition of play or stop hysteresis operators, and the slopes of the operators are considered to be the same. In order to make a hysteresis model, a modified form of non-symmetric play hysteresis operator with unknown slopes is given. The hysteresis model is described by a generalized Lipschitz operator term and a bounded parasitic term. Since the generalized Lipschitz operator is unknown, a new condition using robust right coprime factorization is proposed to guarantee robust stability of the controlled plant with the hysteresis nonlinearity. As a result, based on the proposed robust condition, a stabilized plant is obtained. A numerical example is presented to validate the effectiveness of the proposed method.

滑模-PI混合控制及解耦补偿的PMSM控制研究

针对传统滑模控制存在较大抖动和控制增益值导致启动电流过大等问题,提出一种新型趋近律的滑模-PI混合控制策略。在传统指数趋近律基础上,设计了新型混合趋近律解决系统的抖动问题,电机启动时,结合PI调节器降低启动电流。针对三相永磁同步电机中存在的凸极效应和模型误差对系统性能的影响,提出解耦电流PI控制策略。电流环引入前馈解耦补偿,通过内模控制方式对电流环参数进行整定以提高控制系统的鲁棒性和解耦性能。仿真和实验结果表明:所提出控制策略能提高控制精度和稳定性。

Hybrid control based on inverse Prandtl-Ishlinskii model for magnetic shape memory alloy actuator

The hysteresis characteristic is the major deficiency in the positioning control of magnetic shape memory alloy actuator. A Prandtl-Ishlinskii model was developed to characterize the hysteresis of magnetic shape memory alloy actuator. Based on the proposed Prandtl-Ishlinskii model, the inverse Prandtl-Ishlinskii model was established as a feedforward controller to compensate the hysteresis of the magnetic shape memory alloy actuator. For further improving of the positioning precision of the magnetic shape memory alloy actuator, a hybrid control method with hysteresis nonlinear model in feedforward loop was proposed. The control method is separated into two parts: a feedforward loop with inverse Prandtl-Ishlinskii model and a feedback loop with neural network controller. To validate the validity of the proposed control method, a series of simulations and experiments were researched. The simulation and experimental results demonstrate that the maximum error rate of open loop controller based on inverse PI model is 1.72%, the maximum error rate of the hybrid controller based on inverse PI model is 1.37%.

Composition control and temperature inferential control of dividing wall column based on model predictive control and PI strategies

The dividing wall column （DWC） is considered as a major breakthrough in distillation technology and has good prospect of industrialization. Model predictive control （MPC） is an advanced control strategy that has acquired extensive applications in various industries. In this study, MPC is applied to the process for separating ethanol, n-propanol, and n-butanol ternary mixture in a fully thermally coupled DWC. Both composition control and tem- perature inferent/al control are considered. The multiobjective genetic algor/thm function ＂gamult/obj＂ in Matlab is used for the weight tuning of MPC. Comparisons are made between the control performances of MPC and PI strategies. Simulation results show that although both MPC and PI schemes can stabilize the DWC in case of feed disturbances, MPC generally behaves better than the PI strategy for both composition control and tempera- ture inferential control, resulting in a more stable and superior performance with lower values of integral of squared error （ISE）.

基于模糊自适应PI控制和模型预测控制的MMC-HVDC控制方法

模块化多电平换流器的高压直流输电(modular multilevel converter-high voltage direct current,MMC-HVDC)系统包含外环控制器和内环控制器,是柔性直流输电系统的重要组成部分。传统的外环比例-积分(propor⁃tional⁃integral,PI)控制器的参数固定,没有自适应能力,稳定性和抗干扰性能较差;同时传统的内环控制器是在dq旋转坐标系下的解耦控制系统,其结构复杂,容易出现超调。因此,提出一种基于模糊自适应PI控制和模型预测控制(model predictive control,MPC)的MMC-HVDC控制方法,以简化系统结构,增强动态响应性能,进而使用准比例谐振(proportional resonance,PR)环流抑制控制器来替换传统环流抑制控制器,消除静差值。在Power Systems Computer Aided Design(PSCAD)仿真平台搭建MMC-HVDC系统模型,分别对比了改进前后内外环控制器的性能和环流抑制控制器的环流抑制效果,结果验证了所提方法的有效性和实用性。

模糊PI控制器与干扰观测器相结合的空间柔性机械臂的转动控制策略

为了减少外部干扰对空间柔性机械臂的系统误差,提高系统的控制精度,提出了一种模糊PI控制器与干扰观测器相结合的转动控制策略。首先,采用假设模态法和拉格朗日方法,建立了含有干扰力矩的空间柔性机械臂的初始动力学模型;其次,提出了分别忽略二维变形和忽略非线性项的2种简化动力学模型,并通过仿真分析对比2种简化模型的建模精度;第三,基于极点配置方法和模糊规则设计了模糊PI控制器,并基于系统的名义模型设计了干扰观测器;最后,通过仿真分析和地面物理样机实验验证了该方法的有效性。研究结果表明:忽略非线性项的简化模型与初始模型具有相似的建模精度,极大地降低了计算难度,能够代替初始模型进行控制系统的设计;模糊PI控制器与干扰观测器相结合的转动控制策略能够实时调整控制器参数,观测并补偿干扰力矩引起的系统误差,有效提高系统的控制精度。

Modeling and identification of magnetostrictive hysteresis with a modified rate-independent Prandtl-Ishlinskii model

This paper presents a modified rate-independent Prandtl-Ishlinskii （MRIPI） model based on the Fermi-Dirac distri- bution for the asymmetric hysteresis description of magnetostrictive actuators. Generally, the classical Prandtl-Ishlinskii （CPI） model can hardly describe the asymmetric hysteresis. To overcome this limitation, various complex operators have been developed to replace the classical operator. In this study, the proposed MRIPI model maintains the classical operator while a modified input function based on the Fermi-Dirac distribution is presented to replace the classical input function. With this method, the MRIPI model can describe the asymmetric hysteresis of magnetostrictive actuators in a relatively simple mathematic format and has fewer parameters to be identified. A velocity-based sine cosine algorithm （VSCA） is also proposed for the parameter identification of the MRIPI model. To verify the validity of the MRIPI model, experiments are performed and the results are compared with those of the existing modeling methods.

桥臂不对称情形下MMC无源性PI控制方法

考虑模块化多电平变换器(modular multilevel converter,MMC)桥臂不对称情形,针对环流基频分量不对称引起的dq解耦变换误差问题,提出基于双线性模型的无源性PI控制方法,实现故障相电容电压保持稳定、不对称环流分量的准确抑制、三相并网电流的平衡输出。在abc坐标系下,建立桥臂不对称情形下MMC双线性模型,完成非线性系统控制变量随状态变量同步变化的线性化转换,简化控制器设计,避免dq解耦变换引入的控制误差。从系统全局能量耗散特性出发,设计形式简单的无源性PI控制器,实现子模块电容电压纹波快速抑制,消除桥臂电流不对称性,同时确保闭环控制系统全局渐近稳定运行。基于Matlab的仿真结果验证了所提控制策略能够有效抑制MMC桥臂不对称的不利影响,具有响应快速、稳定性好、鲁棒性强的特点。

Topological Structure of Vortex Solution in Jackiw-Pi Model

By using φ-mapping method,we discuss the topological structure of the self-duality solution in Jackiw-Pimodel in terms of gauge potential decomposition.We set up relationship between Chern-Simons vortex solution andtopological number,which is determined by Hopf index and Brouwer degree.We also give the quantization of flux inthis ease.Then,we study the angular momentum of the vortex,which can be expressed in terms of,the flux.

Design of Li River Water Quality Dynamic Monitoring System Based on Raspberry Pi and TinyML

In order to solve the problem of scientific monitoring of water quality, a trophic monitoring system for Li River water quality is developed to improve the decision-making of related environmental management departments. The system is based on embedded computing, deep learning and Internet of Things technology, combined with software and hardware design, to automatically obtain real-time water quality parameters with Raspberry Pi equipped with sensors and positioning modules. A camera is employed to capture the screen, and yolo-tiny image recognition is implemented in the Raspberry Pi. Lastly, the cloud storage is used for interaction to realize real-time monitoring of water quality, real-time positioning of the boat, real-time return of image recognition and visualization. The system is proven efficient and intelligent in facilitating water quality protection.

UPQC的非线性PI-模型预测控制策略

由于统一电能质量调节器(unified power quality conditioner, UPQC)系统复杂性高,使得其控制难度大并且动静态性能不理想。为了进一步提高UPQC的控制性能,提出了基于非线性比例积分(proportional-integral, PI)与模型预测控制(model predictive control, MPC)的混合控制策略。UPQC的混合控制策略中电压外环采用非线性PI控制器来获取更加准确的期望电流,有效地抑制了静态误差;采用模型预测控制来设计电流内环控制器,使得内环电流能更好地跟踪期望值,UPQC系统的鲁棒性更强。计算机仿真结果表明,该控制策略有效提升了UPQC动静态性能,与PI-MPC及PI-PI控制策略相比,当电网电压发生谐波污染、电压突增、电压突降时可获得更接近正弦的负载电压,当负载电流发生突变时可获得更接近正弦的电网电流。

A DFIM Sensor Faults Multi-Model Diagnosis Approach Based on an Adaptive PI Multiobserver—Experimental Validation

This paper studies the problem of diagnosis strategy for a doubly fed induction motor (DFIM) sensor faults. This strategy is based on unknown input proportional integral (PI) multiobserver. Thecontribution of this paper is on one hand the creation of a new DFIM model based on multi-model approach and, on the other hand, the synthesis of an adaptive PI multi-observer. The DFIM Volt per Hertz drive system behaves as a nonlinear complex system. It consists of a DFIM powered through a controlled PWM Voltage Source Inverter (VSI). The need of a sensorless drive requires soft sensors such as estimators or observers. In particular, an adaptive Proportional-Integral multi-observer is synthesized in order to estimate the DFIM’s outputs which are affected by different faults and to generate the different residual signals symptoms of sensor fault occurrence. The convergence of the estimation error is guaranteed by using the Lyapunov’s based theory. The proposed diagnosis approach is experimentally validated on a 1 kW Induction motor. Obtained simulation results confirm that the adaptive PI multiobserver consent to accomplish the detection, isolation and fault identification tasks with high dynamic performances.