A robust adaptive controller for a nonholonomic mobile robot with unknown kinematic and dynamic parameters is proposed. A kinematic controller whose output is the input of the relevant dynamic controller is provided by using the concept of backstepping. An adaptive algorithm is developed in the kinematic controller to approximate the unknown kinematic parameters, and a simple single-layer neural network is used to express the highly nonlinear robot dynamics in terms of the known and unknown parameters. In order to attenuate the effects of the uncertainties and disturbances on tracking performance, a sliding mode control term is added to the dynamic controller. In the deterministic design of feedback controllers for the uncertain dynamic systems, upper bounds on the norm of the uncertainties are an important clue to guarantee the stability of the closed-loop system. However, sometimes these upper bounds may not be easily obtained because of the complexity of the structure of the uncertainties. Thereby, simple adaptation laws are proposed to approximate upper bounds on the norm of the uncertainties to address this problem. The stability of the proposed control system is shown through the Lyapunov method. Lastly, a design example for a mobile robot with two actuated wheels is provided and the feasibility of the controller is demonstrated by numerical simulations.
六价铬Cr(VI)的不稳定性使其成为RoHS(限定有害物质,Restriction of Hazardous Substances)符合性测试的难点之一.采用分光光度法对塑料中痕量Cr(VI)进行检测,着重研究Cr(VI)萃取与显色中的过程参数与干扰因素的影响,并建立了一套试样制备、萃取、显色等标准程序.研究表明,采用混合碱萃取法可对Cr(VI)进行有效提取,同时消除Cr(III)的干扰,通过排除共存离子影响,优化萃取、显色、标定过程中pH值、温度和时间等参数,可使试样和加标溶液的回复率保持在90%～110%之间,RSD<1%,校准在低浓度范围(0～500μg/L)呈良好线性关系.提出的方法和检测程序具有较高的精确度和灵敏度,而且操作简单、快速,为信息产业应对RoHS符合性测试提供了较好的技术支持.
