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.

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 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.

A model free adaptive control method based on self-adjusting PID algorithm in pH neutralization process

In this paper,a new model free adaptive control method based on self-adjusting PID algorithm(MFACSA-PID)is proposed to solve the problem that the pH process with strong nonlinearity is difficult to control near the neutralization point.The MFAC-SA-PID method also solves the problem that the parameters of the model free adaptive control(MFAC)method are not easy to be adjusted and the effect is not obvious by introducing a fuzzy self-adjusting algorithm to adjust the controller parameters.Then the convergence and stability of the MFAC-SA-PID method are proved in this paper.In the simulation study,the control performance of the MFAC-SA-PID method proposed in this paper is compared with the traditional MFAC method and the improved model free adaptive control(IMFAC)method,respectively.The results show that the proposed MFAC-SA-PID method has better control effect on the pH neutralization process.The MFAC-SA-PID control performance also outperforms the traditional MFAC method and IMFAC method when step input disturbances are added,which indicates that the MFAC-SA-PID method has better robustness and stability.

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.

Dual-stage Optimal Iterative Learning Control for Nonlinear Non-affine Discrete-time Systems

根据沿着重复轴的一种新动态 linearization 技术，双阶段的最佳的反复的学习控制为非线性、非仿射的分离时间的系统被介绍。双阶段显示二个最佳的学习阶段分别地被设计反复地改进控制输入顺序和学习获得。主要特征是控制器设计和集中分析仅仅取决于动态系统的 I/O 数据。换句话说，没有知道系统的任何另外的知识，我们能容易选择控制参数。模拟学习沿着重复轴说明介绍方法的几何集中，在哪个马路的一个例子控制为它的内在的工程重要性是引人注目的交通反复的学习。

New adaptive quasi-sliding mode control for nonlinear discrete-time systems

A new adaptive quasi-sliding mode control algorithm is developed for a class of nonlinear discrete-time systems, which is especially useful for nonlinear systems with vaguely known dynamics. This design is model-free, and is based directly on pseudo-partial-derivatives derived on-line from the input and output information of the system using an improved recursive projection type of identification algorithm. The theoretical analysis and simulation results show that the adaptive quasi-sliding mode control system is stable and convergent.

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.

Time delay control of hydraulic manipulators with continuous nonsingular terminal sliding mode

For the position tracking control of hydraulic manipulators,a novel method of time delay control(TDC) with continuous nonsingular terminal sliding mode(CNTSM) was proposed in this work.Complex dynamics of the hydraulic manipulator is approximately canceled by time delay estimation(TDE),which means the proposed method is model-free and no prior knowledge of the dynamics is required.Moreover,the CNTSM term with a fast-TSM-type reaching law ensures fast convergence and high-precision tracking control performance under heavy lumped uncertainties.Despite its considerable robustness against lumped uncertainties,the proposed control scheme is continuous and chattering-free and no pressure sensors are required in practical applications.Theoretical analysis and experimental results show that faster and higher-precision position tracking performance is achieved compared with the traditional CNTSM-based TDC method using boundary layers.

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。

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。

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。

Differences in pathological changes between two rat models of severe traumatic brain injury

The rat high-impact free weight drop model mimics the diffuse axonal injury caused by severe traumatic brain injury in humans,while severe controlled cortical impact can produce a severe traumatic brain injury model using precise strike parameters.In this study,we compare the pathological mechanisms and pathological changes between two rat severe brain injury models to identify the similarities and differences.The severe controlled cortical impact model was produced by an electronic controlled cortical impact device,while the severe free weight drop model was produced by dropping a 500 g free weight from a height of 1.8 m through a plastic tube.Body temperature and mortality were recorded,and neurological deficits were assessed with the modified neurological severity score.Brain edema and bloodbrain barrier damage were evaluated by assessing brain water content and Evans blue extravasation.In addition,a cytokine array kit was used to detect inflammatory cytokines.Neuronal apoptosis in the brain and brainstem was quantified by immunofluorescence staining.Both the severe controlled cortical impact and severe free weight drop models exhibited significant neurological impairments and body temperature fluctuations.More severe motor dysfunction was observed in the severe controlled cortical impact model,while more severe cognitive dysfunction was observed in the severe free weight drop model.Brain edema,inflammatory cytokine changes and cortical neuronal apoptosis were more substantial and blood-brain barrier damage was more focal in the severe controlled cortical impact group compared with the severe free weight drop group.The severe free weight drop model presented with more significant apoptosis in the brainstem and diffused blood-brain barrier damage,with higher mortality and lower repeatability compared with the severe controlled cortical impact group.Severe brainstem damage was not found in the severe controlled cortical impact model.These results indicate that the severe controlled cortical impact model is relatively more stable,more reproducible,and shows obvious cerebral pathological changes at an earlier stage.Therefore,the severe controlled cortical impact model is likely more suitable for studies on severe focal traumatic brain injury,while the severe free weight drop model may be more apt for studies on diffuse axonal injury.All experimental procedures were approved by the Ethics Committee of Animal Experiments of Tianjin Medical University,China(approval No.IRB2012-028-02)in Febru ary 2012.

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。

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。

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。

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。

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。

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。