Decoupling control based on terminal sliding mode and wavelet network for the speed and tension system of reversible cold strip rolling mill

To weaken the nonlinear coupling influences among the variables in the speed and tension system of reversible cold strip rolling mill, a novel dynamic decoupling control strategy is proposed based on nonsingular fast terminal sliding mode (NFTSM) and wavelet neural network (WNN). First, nonlinear disturbance observers are developed to counteract the mismatched uncertainties, and then input/output dynamic decoupling and linearisation for the speed and tension nonlinear coupling system are realised by utilising the inverse system theory. Second, nonsingular fast terminal sliding mode controller (NFTSMC) for each pseudo linear subsystem is presented based on backstepping and two-power reaching law, so as to improve the global convergence speed and robust stability of the system. Third, adaptive WNNs are used to approximate the uncertain items of the system, so as to improve the control precision of the speed and tension of reversible cold strip rolling mill. Theoretical analyses show that the NFTSMs satisfy reachability condition, the system error variables can converge to equilibrium point in finite time, and the resulting closed-loop system is globally asymptotically stable. Finally, simulation research is carried out on the speed and tension system of a 1422 mm reversible cold strip rolling mill by using the actual data, and results show the superiority of the proposed control strategy in comparison with the strategies of cascade PI, linear sliding mode control and internal model control.     

可逆冷带轧机速度张力系统的耗散Hamilton 控制

研究基于侵入与不变流形(I&I)自适应方法和非线性干扰观测器(NDO)的可逆冷带轧机速度张力系统耗散Hamilton控制问题。首先采用I&I自适应方法估计系统的摄动参数;其次,通过预反馈建立系统速度张力外环的耗散Hamilton模型,并利用互联和阻尼配置以及能量整形方法设计耗散Hamilton控制器;再次,选用NDO对系统电流内环的外扰进行观测,并引入设计的积分滑模控制器中进行补偿;最后将该方法应用于某1422 mm可逆冷带轧机速度张力系统中进行仿真,结果验证了所提出方法的有效性。     

基于Hamilton理论的可逆冷带轧机速度张力系统无张力计控制

基于反馈耗散Hamilton理论研究了可逆冷带轧机速度张力系统的无张力计控制问题. 首先,对系统速度张力外环(主轧机速度环和左、右卷取机张力控制环)进行预反馈控制, 并采用反馈耗散Hamilton理论完成了速度张力外环控制器的设计. 其次, 为了实现系统的无张力计控制及对摄动参数的自适应估计, 基于"扩张系统+反馈"方法完成了系统速度张力外环自适应状态观测器的设计. 再次, 为了实现可逆冷带轧机主轧机速度和左、右卷取机张力间的协调控制及对外扰不确定项的干扰抑制, 基于backstepping方法完成了系统电流内环鲁棒控制器的设计. 理论分析表明, 所提出的控制方法能够保证闭环系统的鲁棒稳定性. 最后, 基于某1422mm可逆冷带轧机速度张力系统的实际数据进行仿真, 并同串级PI控制方法相比较, 结果验证了本文所提方法的有效性.     

可逆冷带轧机速度张力多变量耦合系统的建模及分散控制

针对具有多变量、非线性、强耦合和不确定性的可逆冷带轧机速度张力系统,提出了一种基于扩张状态观测器(extended state observer,ESO)的全局积分滑模自适应反步分散控制方法.首先,采用机理建模方法,建立了相对完备的可逆冷带轧机速度张力多变量耦合系统的数学模型.其次,将各子系统的耦合项和不确定项看成外扰,通过构造的ESO对其进行动态观测,并分别引入所设计的全局积分滑模自适应反步控制器中进行补偿,速度张力系统实现了有效的动态解耦和协调控制.理论分析表明,所提出的控制方法能够保证滑模面的渐近稳定和闭环系统的渐近跟踪性能.最后,基于某1422mm可逆冷带轧机速度张力系统的实际数据进行仿真,结果验证了所提方法的有效性.     

基于Hamilton理论的冷带轧机速度张力系统非奇异 快速终端滑模控制

针对交流异步电机驱动的冷带轧机速度张力系统的跟踪控制问题,给出一种基于Hamilton理论的非奇异快速终端滑模控制器设计方法.首先,设计了一种新型扰动观测器对系统中由参数摄动和负载扰动引起的不确定项进行观测;其次,通过预反馈控制建立了冷带轧机系统速度张力磁链外环的耗散Hamilton模型,进而基于互联–阻尼配置及能量整形方法完成耗散Hamilton控制器的设计;再次,基于串级控制思想完成了冷带轧机系统电流内环非奇异快速终端滑模控制器的设计.通过理论分析证明了所提控制方法能够保证闭环系统全局稳定.最后,基于某交流异步电机驱动的冷带轧机系统的现场实际数据进行仿真对比研究,仿真结果验证了本文所提方法的有效性.     

可逆冷带轧机速度张力系统的动态滑模解耦控制

为削弱可逆冷带轧机速度张力系统中各变量间的非线性耦合影响,本文提出了一种基于幂指数趋近律的微分几何动态滑模解耦控制方法.首先,应用微分几何理论,通过非线性状态反馈和坐标变换,实现了可逆冷带轧机速度张力非线性耦合系统的输入/输出动态解耦和线性化.其次,针对解耦后得到的各独立线性子系统,综合考虑可逆冷带轧机速度张力系统的负载扰动、参数摄动和未建模动态等不确定部分的影响,基于幂指数趋近律设计了动态滑模控制器.理论分析表明,所提出的控制方法能够保证闭环系统渐近稳定,并能有效削弱系统抖振.最后,对某1422mm可逆冷带轧机速度张力非线性耦合系统进行仿真,并同其他解耦控制方法相比较,结果验证了所提出方法的有效性.     

轧机两侧液压伺服位置系统自抗扰同步控制

针对轧机传动侧和操作侧液压伺服位置系统存在不一致性而引起两侧位置不同步的问题, 提出一种自抗扰同步控制方法.首先建立了液压伺服位置同步系统动态机理模型, 并在考虑两侧位置伺服系统都具有参数摄动及外负载波动的情况下, 设计了扩张状态观测器对同步系统中不确定性和不一致性进行估计, 并采用状态误差反馈律给予主动补偿, 同时消除同步误差. 仿真和实验结果表明, 所提出的同步控制方法能够使两侧液压伺服位置系统动态响应和稳态特性保持一致, 并提高了单侧子系统的动态性能及抗干扰能力.     

Adaptive dynamic surface control of flexible-joint robots using self-recurrent wavelet neural networks.

A new method for the robust control of flexible-joint (FJ) robots with model uncertainties in both robot dynamics and actuator dynamics is proposed. The proposed control system is a combination of the adaptive dynamic surface control (DSC) technique and the self-recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides the ability to overcome the "explosion of complexity" problem in backstepping controllers. The SRWNNs are used to observe the arbitrary model uncertainties of FJ robots, and all their weights are trained online. From the Lyapunov stability analysis, their adaptation laws are induced, and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a three-link FJ robot are utilized to validate the good position tracking performance and robustness against payload uncertainties and external disturbances of the proposed control system.     

Robust adaptive NN-based output feedback control for a dynamic positioning ship using DSC approach

A robust adaptive NN-based output feedback control scheme is presented for a dynamic positioning ship with uncertainties and unknown external disturbances. We tackle the problem that velocity vector of a ship is not available by employing a high-gain observer, and develop the proposed control approach by combing vectorial backstepping with dynamic surface control approach, which is simpler and easier to implement in engi- neering practice. The neural network （NN） approximation technique is used to compensate for the uncertainties and unknown external disturbances, and it removes the requirement for the prior knowledge about the vessel parameters and external disturbances. Also, it is demonstrated that the proposed control strategy can force the position and yaw angle of a dynamic positioning ship to approach the desired point while guaranteeing all singles of the designed closed-loop dynamic positioning system semi-globally uniformly ultimately bounded by means of the Lyapunov function. Simulation results of a supply ship illustrate the effectiveness of the proposed scheme.     

近空间飞行器纵向抗干扰轨迹控制研究

针对近空间飞行器( nearspace vehicle,NSV) 在高超音速飞行时,气动参数变化剧烈且容易受到外界干扰的特点,研究了NSV 纵向轨迹系统的干扰问题,提出了鲁棒自适应动态面的回馈递推控制方法。首先对高度非线性、高度复杂的NSV 的纵向运动的模型进行坐标变换,采用输入－输出反馈线性化方法,将其转化为仿射非线性模型; 然后通过一阶低通滤波器对控制器设计中的虚拟控制律进行估计,从而避免了对其求导带来的计算膨胀问题; 再结合神经网络逼近理论以及虚拟控制器中的鲁棒项,一起消除近空间飞行器的纵向系统中存在的参数摄动不确定和外界干扰。最后通过稳定性分析,表明了该方法在降低系统控制器复杂性的同时仍具有很好的鲁棒性。