基于伺服电机的流量标准装置换向器精度的研究

以气缸推动的方式实现换向器的换向会对流量标准装置的检定精度带来不利影响。针对热水流量标准装置的准确性和可靠性需求,研究并建立了一套连续同步可调触发的伺服电机驱动流量标准装置换向器换向系统,该系统有效降低了人工调节触发点对流量标准装置带来的误差。该研究通过对三组光电开关的设置完成了对换向器分流器挡片位置的运动监测,在此基础上研究了换向最佳转速。连续可调同步触发实验检定该换向器不确定度为0. 005%,验证了该系统的可靠性与可行性。基于伺服电机的换向器具有响应速度快、运动状态稳定、调节精度高的特点,较为明显地提升了换向器的性能。     

A compact design scheme of adaptive output-feedback control for uncertain nonlinear systems

Multiple uncertainties/noises, frequently exist in a plant, usually require multiple compensation techniques, which renders feedback controllers highly dynamic and nonlinear. This motivates us to search for a compact design scheme of compensation to reduce the complexity of controllers. In this paper, global output-feedback stabilisation is investigated for a class of uncertain nonlinear systems with unknown unmeasured states-dependent growth and input matching uncertainty. To solve the problem, a compact scheme is proposed to design a global adaptive output-feedback controller, which combines the technique of dynamic gain and extended state observer together. Particularly, only one dynamic gain, rather than two dynamic gains, is introduced to deal with the unknown polynomial-of-output growth rate, which makes our controller to have lower dynamics than those in the related works. Moreover, the input matching uncertainty is asymptotically estimated by the extended state observer, and thus its effect is well counteracted. It is shown that, under the designed controller, the system states globally converge to zero. A simulation example on non-zero set-point regulation demonstrates the effectiveness of the proposed approach.     

A novel matrix game with payoffs of Maxitive Belief Structure

Maxitive Belief Structures (MBSs), emerge as a novel class of belief structure to represent imprecise and uncertain information with a specific structure allowing it to model both probability nonspecificity and imprecise. A novel matrix game with payoffs of MBS is presented. The proposed model can be used to describe interactions among players, and an effective method is developed to find the solution of a game through reaching an equilibrium point. A numerical example is given to verify the validness of the proposed model.     

一类不确定性离散非线性重复过程的迭代学习容错控制

针对一类具有非线性和执行器故障的重复运行不确定离散系统,提出了一种迭代学习鲁棒容错控制算法.首先通过定义执行器故障系数矩阵,将迭代学习控制过程转化为等价形式的不确定性非线性重复过程模型,然后基于混合李亚普若夫函数方法讨论非线性重复过程在时间轴和批次轴两个维度上的稳定性,并以线性矩阵不等式形式给出鲁棒容错控制器存在的充分条件和设计方法,同时保证系统正常和执行器故障情形下系统的容错稳定性能.最后,单杆机械手系统的输出跟踪控制仿真结果验证了本文算法的有效性.     

回收数量不确定的双重竞争闭环供应链定价研究

为解决双重竞争闭环供应链中回收产品数量不确定对财政干预政策及定价决策影响的问题,运用博弈论和Matlab数值仿真的方法,构建回收产品数量不确定的双重竞争闭环供应链定价决策模型,从4个维度剖析并验证回收产品数量不确定对闭环供应链竞争强度、销售及回收价格、供应链节点企业利润及社会福利、回收率的影响规律,研究结果表明：当回收产品数量波动较大,回收商和再制造商的回收价格及回购价格呈现增加的趋势;闭环供链中回收商利润、销售商利润以及社会福利呈现增加的趋势,但是制造商利润下降,即回收数量不确定直接影响闭环供链中起主导作用的制造商执行再制造的积极性。     

含模型不确定性的上三角非线性系统的全局镇定

本文针对一类具有模型不确定性的上三角非线性系统,利用嵌套饱和函数方法研究其全局镇定问题.首先,对系统中存在的未知幂指数、未知控制参数和不确定性非线性函数施加适当假设,并基于Lyapunov稳定性定理利用已知的参数设计局部镇定控制器.然后,将设计的控制器与饱和函数结合得到饱和控制器.通过适当选取饱和度,可以证明只要不确定参数在限定的范围内,该控制器都能够使得闭环系统全局渐近稳定.最后,选取不同的系统幂指数搭建数值仿真算例.在相同的控制器作用下,系统状态和控制轨迹渐近收敛至原点,从而验证了所提控制算法的有效性和鲁棒性.     

Observer‐based position control of uncertain mechanical systems with measurement uncertainty

This paper studies the position control of uncertain mechanical systems with measurement uncertainty. Firstly, an observer using measurement signals is designed to estimate the unknown disturbances under an improved assumption of the uncertainties. The improved assumption can give smaller error estimation with same observer gain compared with the conventional assumption. Next, the essence of the observer and the method for selecting the observer gain are introduced. For the case when measurement uncertainties are not considered, the observer is allowed to have a large gain. As for the current case, it is shown that the observer with a large gain will lead to a failure. Then, by using the observed values, two switching controllers using measurement signals are proposed to realize the position control. The proposed control is a generalization of the sliding mode control without measurement uncertainty to the case with measurement uncertainty. Meanwhile, the features of the velocity change of the controlled system are discussed. Finally, as an application of the control design, the position control of a dynamic positioning system is investigated in details. The motion of the controlled system exhibits obviously three phases with different velocity features during the system moves to the target position: approximate acceleration phase, approximate uniform velocity phase, and approximate deceleration phase, and the velocity of the approximate uniform velocity phase can be easily adjusted with the change of the control gains.     

Robust adaptive fault‐tolerant tracking control for uncertain linear systems with time‐varying performance bounds

In this paper, the problem of robust adaptive fault‐tolerant tracking control with time‐varying performance bounds is investigated for a class of linear systems subject to parameter uncertainties, external disturbances and actuator failures. In order to ensure the norm of the tracking error less than the user‐defined time‐varying performance bounds, we propose a new control strategy which is predicated on the generalized restricted potential function. Compared with the existing result, a novel method which provides two design freedoms is developed to reduce the tracking error. According to the online estimation information provided by adaptive mechanism, a fault‐tolerant tracking control method guaranteeing time‐varying performance bounds is developed for robust tracking of reference model. It is shown that the closed‐loop signals are bounded and the tracking error within an a priori given, time‐varying performance bounds. A simulation result is provided to demonstrate the efficacy of the proposed fault‐tolerant tracking control method.     

L∞ Observer for Uncertain Linear Systems

In this paper, an L_∞ observer design method is proposed for linear system subject to parameter uncertainty and bounded disturbance. The proposed L_∞ observer, which satisfies a peak‐to‐peak disturbances attenuation performance, is designed to overbound the estimation error. Moreover, sufficient conditions for the design of L_∞ observer are derived and expressed in terms of linear matrix inequalities (LMIs). The novelty of the proposed method is that we develop an L_∞ observer that not only can attenuate bounded disturbance but also provides an upper bound of estimation error norm. Simulation results are presented to illustrate the effectiveness of the proposed method.     

Uncertain Method for Optimal Control Problems With Uncertainties Using Chebyshev Inclusion Functions

In this paper, a new uncertain analysis method is developed for optimal control problems, including interval variables (uncertainties) based on truncated Chebyshev polynomials. The interval arithmetic in this research is employed for analyzing the uncertainties in optimal control problems comprising uncertain‐but‐bounded parameters with only lower and upper bounds of uncertain parameters. In this research, the Chebyshev method is utilized because it generates sharper bounds for meaningful solutions of interval functions, rather than the Taylor inclusion function, which is efficient in handling the overestimation derived from the wrapping effect due to interval computations. For utilizing the proposed interval method on the optimal control problems with uncertainties, the Lagrange multiplier method is first applied to achieve the necessary conditions and then, by using some algebraic manipulations, they are converted into the ordinary differential equation. Afterwards, the Chebyshev inclusion method is employed to achieve the solution of the system. The final results of the Chebyshev inclusion method are compared with the interval Taylor method. The results show that the proposed Chebyshev inclusion function based method better handle the wrapping effect than the interval Taylor method.