BIO-INSPIRED SELF-ADAPTIVE MANUFACTURING SYSTEM CONTROL ARCHITECTURE

Future manufacturing systems need to cope with frequent changes and disturbances, therefore their control architectures require constant adaptability, agility, stability, self-organization, intelligence, and robustness. Bio-inspired manufacturing system can well satisfy these requirements. For this purpose, by referencing the biological organization structure and the mechanism, a bio-inspired manufacturing cell is presented from a novel view, and then a bio-inspired self-adaptive manufacturing model is established based on the ultra-short feedback mechanism of the neuro-endocrine system. A hio-inspired self-adaptive manufacturing system coordinated model is also established based on the neuro-endocrine-immunity system （NEIS）. Finally, an example based on pheromone communication mechanism indicates that the robustness of the whole manufacturing system is improved by bio-inspired technologies.

Fuzzy Model Free Adaptive Control for Rotor Blade Full-Scale Static Testing

To eliminate the node traction coupling during wind turbine blade full-scale static testing,a model free adaptive control algorithm is presented based on fuzzy control performance function compensation. Based on the universal model theory,the fuzzy model free adaptive control( FMFAC) algorithm is designed by configuring the spot static testing experiences as compensation function F( ·). Then the algorithm implementation process is provided and its quick convergence is proved. Using software to establish static load coupling model of multi-nodes,simulate and verify the validity of FMFAC algorithm,which is applied to wind turbines blade full-scale static testing. The results show that the adaptive decoupling ability of FMFAC is better. The traction of four load points can stay steady and change coordinately. Process error is not over ± 6 k N. The error rate is lower than 1% in special phase.This algorithm effectively eliminates the traction coupling of the static testing process,and makes wind turbine blade testing steadily.

Model Free Adaptive Predictive Control of Desulfurization Slurry pH Based on CPS Framework

In order to improve the slurry pH control accuracy of the absorption tower in the wet flue gas desulfurization process,a model free adaptive predictive control algorithm for the desulfurization slurry pH which is based on a cyber physical systems framework is proposed.First,aiming to address system characteristics of non-linearity and pure hysteresis in slurry pH change process,a model free adaptive predictive control algorithm based on compact form dynamic linearization is proposed by combining model free adaptive control algorithm with model predictive control algorithm.Then,by integrating information resources with the physical resources in the absorption tower slurry pH control process,an absorption tower slurry pH optimization control system based on cyber physical systems is constructed.It is turned out that the model free adaptive predictive control algorithm under the framework of the cyber physical systems can effectively realize the high-precision tracking control of the slurry pH of the absorption tower,and it has strong robustness.

Model-free Adaptive Control for Spacecraft Attitude

A model-free adaptive control method is proposed for the spacecrafts whose dynamical parameters change over time and cannot be acquired accurately. The algorithm is based on full form dynamic linearization.A dimension reduction matrix is introduced to construct an augmented system with the same dimension input and output. The design of the controller depends on the system input and output data rather than the knowledge of the controlled plant. The numerical simulation results show that the improved controller can deal with different models with the same set of controller parameters,and the controller performance is better than that of PD controller for the time-varying system with disturbance.

Fast Ferry Smoothing Motion via Intelligent PD Controller

A novel type of control law was adopted to reduce the vertical acceleration of a fast ferry as well as the motion sickness incidence suffered by the passengers onboard by means of a submerged T-foil.Considering the system changing characteristics under high disturbances,a model-free approach was adopted.In addition,an upgraded proportional-derivative(PD)controller with correction terms resulting from a fast-online estimation of the system dynamics was designed.The overall controller,known as intelligent PD(i-PD)controller,was tested,and the obtained results were compared with those of a classic PD controller.The controllers were also tested in a changing environment and at different operating velocities.The results confirmed the effectiveness of the i-PD controller to smooth the motions with low computational cost control schemes.Furthermore,thanks to ability of the i-PD controller to continually update the estimated dynamics of the system,it showed a better reduction in both vertical motions and the seasickness level of the passengers with the needed robustness under external disturbances and system changing parameters.

柔性关节空间机械臂传感容错无模型自适应控制

针对传感信号畸变、丢失等故障状态严重影响空间机械臂控制系统性能的问题,提出基于空间机械臂运动传感器故障观测的无模型自适应容错控制方法。采用动态线性化和递推参数估计思想设计传感故障监测器,实现对传感畸变及数据丢失等故障的判定,并进行运动状态预测估计;建立包含跟踪误差变化率项的无模型自适应控制准则函数,有效惩罚由传感故障引起的参数估计突变问题;设计面向柔性关节空间机械臂的新型传感容错无模型自适应控制(SFT-MFAC)算法。仿真结果表明,在不同传感故障情况下,所提控制策略均能快速准确识别传感故障信息,避免系统瞬时发散,有效延长系统响应时间,增加控制系统的鲁棒性。

计及采样扰动抑制的电压源逆变器三矢量无模型预测电流控制方法

针对传统电压源逆变器无模型预测电流控制(model-free predictive current control,MFPCC)方法存在电流纹波大、电流梯度更新停滞以及预测性能易受采样扰动影响的问题。该文提出一种计及采样扰动的三矢量MFPCC方法。在一个控制周期应用3个基本矢量,并根据价值函数计算矢量作用时间,降低了输出电流纹波;其次,通过建立不同矢量作用下的电流梯度方程组,实现电流梯度数据的实时更新,消除了停滞现象;再次,分析采样扰动对MFPCC的影响,采用扩张状态观测器估计采样扰动以补偿预测电流控制,抑制其对输出电流的影响。最后,通过仿真和实验,对所提方法的有效性进行了验证。

A Model of Perfect Pediatric Vaccination of Dengue with Delay and Optimal Control

A delayed mathematical model of Dengue dynamical transmission between vector mosquitoes and human, incorporating a control strategy of perfect pediatric vaccination is proposed in this paper. By some analytical skills, we obtain the existence of disease-free equilibria and endemic equilibrium, the necessary conditions of global asymptotical stability about two disease-free equilibria. Further, by Pontryagin’s maximum principle, we obtain the optimal control of the disease. Finally, numerical simulations are carried out to verify the correctness of the theoretical results and feasibility of the control measure.

引入ESO的永磁超环面电机无模型预测电流控制

为改善无差拍预测电流控制(DPCC)对永磁超环面电机系统参数的依赖性,研究了引入扩张状态观测器(ESO)的永磁超环面电机无模型预测电流控制(MFPCC-ESO)策略。根据永磁超环面电机的复合转子结构,引入自转运动影响系数与磁势系数,在旋转坐标系下建立该电机的时变数学模型;利用永磁超环面电机系统的输入与输出,建立该电机具有时变比例因子的超局部模型,同时引入ESO对超局部模型的干扰部分进行实时估计,并利用朱利稳定判据证明了ESO的稳定性;结合延时补偿的DPCC预测得到参考电压矢量,从而实现永磁超环面电机的MFPCC-ESO策略。对参数匹配和失配下永磁超环面电机MFPCC-ESO策略与DPCC策略进行对比分析,仿真结果表明:MFPCC-ESO策略下的永磁超环面电机具有优越的动态和稳态性能及强鲁棒性,同时该控制策略还能有效降低永磁超环面电机的输出波动。

一种永磁同步电机模型失配容错控制算法

针对高精度永磁同步电机驱动系统因转动惯量、摩擦系数与磁链参数失配造成其控制精度和稳定性降低的问题,提出了一种基于有限时间收敛扩张状态观测器的无模型滑模容错控制方法。首先,建立了考虑内外不确定性的永磁同步电机转速环超局部模型,并设计了无模型全局积分终端滑模控制器;其次,设计了有限时间收敛扩张状态观测器来降低模型失配带来的影响;最后,通过与其他方法的仿真和实验对比,验证了所提方法能够在不获取精确模型的情况下实现了对多种模型失配与外部扰动工况的容错控制,并提高了电机的控制精度。

无模型控制技术在丁二烯装置应用研究

对丁二烯控制技术的难点进行了剖析,重点阐述了无模型控制技术的基本原理、特性、功能、控制方法以及实现过程等,无模型控制技术通过对复杂控制系统进行闭环稳定安全控制,大大提高了生产设备的自动控制效率,改善了丁二烯产品品质,降低了生产技术人员的劳动强度,降低了因人为因素而产生的不安定影响,从而增加了生产设备运行的平稳性。无模型控制系国内丁二烯装置首次应用精准优化控制,可以实现脱重塔单元整体的闭环稳定控制,在无模型控制基础上实现黑屏操作的自控投用率为100%实现精准控制,增加丁二烯的产量,提高了产品质量;投用无模型控制后正常工况下控制回路波动范围上下限可减少30%左右,实现控制回路参数更加稳定,装置运行更加平稳,提高装置的安全性和装置的寿命,延长装置的运行周期。

基于ESMDO的级联双模型永磁同步电机鲁棒控制

考虑永磁同步电机调速控制系统中传统电流环数学模型的耦合非线性,结合无模型控制的优势,提出了一种基于扩展滑模观测器(extended sliding mode disturbance observer,ESMDO)的级联双模型永磁同步电机鲁棒控制方法,有效解决了传统PI控制器的鲁棒性差、动态响应慢的问题。首先,在转速环利用传统永磁同步电机数学模型设计了引入自校正开关增益的离散滑模转速控制器,通过离散的ESMDO观测综合扰动项并进行补偿。然后,在考虑电机参数的不确定性和外部扰动的情况下,建立了电流环超局部模型,设计了基于离散的ESMDO的无模型无差拍电流预测控制器。最后,以PI控制为对比方法进行仿真分析,仿真结果表明了所提方法的可行性与有效性。

基于无模型自适应控制的半潜式平台运动性能研究

南海海域油气资源极其丰富,半潜式平台在该海域工作时常常面临着系泊失效这一重大危险情况。该研究以一艘装配有悬链式系泊系统和DP-3动力定位系统的半潜式平台为研究对象,利用AQWA软件开展系泊失效前后半潜式平台运动性能研究。同时,借助于AQWA软件二次开发功能,将无模型自适应控制作为动力定位系统控制理论,以研究半潜式平台系泊失效后运动性能恢复。数值仿真模拟结果表明,采用无模型自适应控制作为动力定位系统控制理论的半潜式平台能很好地恢复系泊失效后的运动性能,有效地减小系泊失效带来的危害;基于偏格式动态线性化和全格式动态线性化的无模型自适应控制比基于紧格式动态线性化的无模型自适应控制能让半潜式平台更快地恢复运动性能。

运行工况自适应的风储系统双层功率平滑策略

针对风电并网带来的功率波动问题,提出一种运行工况自适应的风电-混合储能系统双层功率平滑策略。在上层,考虑风储系统并网功率波动和储能运行状态,利用无模型自适应控制动态跟踪经滑动平均算法得到的并网参考功率,生成混合储能总功率任务;在下层,考虑储能介质的技术特性,利用模糊控制动态调节经变分模态分解确定的混合储能总功率任务的频率分界点,完成功率的自适应分配。算例分析表明:所提策略可以自适应平抑多工况下的风电功率波动,实现混合储能各介质间功率的合理分配。

考虑磁链变化率的永磁同步电机失磁故障复合容错控制

针对永磁同步电机(PMSM)失磁故障中磁链变化较快,近似认为磁链变化率为0会导致传统PMSM失磁容错控制方法性能受限的问题,本文提出一种基于智能比例积分微分的无模型超螺旋滑模复合容错控制(iPID-MFSTSMC)方法。首先,构建考虑永磁体磁链变化量的PMSM失磁故障数学模型,根据这一模型设计了磁链滑模观测器,实现了对于磁链及其变化率的观测。此外,针对快速变化的负载转矩设计了负载转矩导数滑模观测器。然后,基于磁链及其变化率、负载转矩导数的观测,设计了iPID无模型容错控制方法,该方法采用超螺旋滑模算法对观测误差及其他扰动进行抑制,改善了动态性能且降低了控制器参数的设计难度。利用Lyapunov稳定性定理证明了所设计容错控制方法的稳定性,并给出了参数的设计条件。最后,在磁链以及负载转矩快速变化工况下,通过仿真和实验分析表明,该方法可以有效减少系统抖振并降低超调量。

柔性机械臂干扰力观测与无模型振动控制

为了抑制柔性机械臂运动过程中的非线性振动,提出一种基于干扰力在线观测的无模型轨迹跟踪和振动抑制混合控制策略。采用拉格朗日方程和奇异摄动法对存在未知干扰的柔性机械臂进行动力学建模和解耦,将其分解为表征刚性运动的慢变子系统和表征柔性振动的快变子系统;考虑到建模的复杂性和模型参数的不确定性,采用PD控制方法实现轨迹跟踪,并提出无模型自适应控制算法以实现柔性臂杆的非线性振动控制。针对未知外界干扰可能引起的控制发散问题,提出了改进的干扰力状态观测器,用于干扰力矩的在线估计和实时补偿,有效提高无模型振动控制算法的收敛性能。仿真试验结果表明,所提算法在存在干扰力的情况下对柔性机械臂的振动抑制效果显著,且具有良好的动态性能和鲁棒性。

基于LabVIEW的无模型自适应控制算法实现与应用

为了有效地将无模型自适应控制算法(MFAC)应用于实际场景,该文研究LabVIEW开发环境中实现基于紧格式动态线性化的无模型自适应控制(MFAC-CFDL)。实验结果表明,对于相同的被控对象,LabVIEW实现与Matlab的仿真运行结果一致,证明该方法准确性。进一步与传统的PID控制方法相比较,MFAC-CFDL显示出更强的鲁棒性,并能保证闭环系统的稳定性以及输出误差跟踪的收敛性,通过实验说明该方法工程实践应用有效性和可行性。

基于ESO的永磁同步电机自耦合无模型滑模控制

为了解决基于模型的永磁同步电机调速系统易受外部负载扰动影响的问题,实现转速的高性能控制,提出自耦合无模型滑模级联式统一化控制策略。考虑参数不确定性以及内外扰动,建立了永磁同步电机双环超局部矢量模型。在传统无模型滑模控制器的基础上,通过选取比例双重积分滑模面设计了级联式无模型滑模速度、电流控制器,有效减小了转速的稳态误差。通过设计速度因子解决了控制器比例积分增益整定不合理的问题,同时采用扩张状态观测器对超局部模型中的未知部分进行估计并进行前馈补偿,设计了基于扩张状态观测器的永磁同步电机自耦合无模型滑模控制调速系统。通过与PI控制及传统无模型滑模控制的对比仿真与实验分析,验证了所提控制策略的可行性与有效性。

基于自抗扰的感应电机无模型预测电流控制

针对采用传统比例积分(proportional integral,PI)控制算法的感应电机在面对复杂扰动时控制性能降低的问题,基于矢量控制系统,提出了感应电机的自抗扰(active disturbance rejection control,ADRC)无模型预测控制(model-free predictive control,MFPC)方法。首先,结合转速环和磁链环数学模型,设计了转速环和磁链环的ADRC控制器,对负载变化和内参摄动产生的内外扰动进行观测并补偿。其次,为避免内环控制器对电机参数的依赖,基于无模型控制原理,建立了dq电流环的超局部方程,将控制量之外的变量视为干扰量,并引入非线性扩张状态观测器估计干扰量。最后,结合预测控制思想设计了电流环控制器,得到开关状态作用于逆变器。仿真与实验结果表明提出的算法相对PI算法有更好的抗扰性和鲁棒性,可以有效提高感应电机的动态和稳态性能。