中文摘要：

为 nonholonomic 的一个柔韧的适应控制器有未知运动学、动态的参数的活动机器人被建议。其产量是相关动态控制器的输入的一个运动学的控制器被使用背走的概念提供。一个适应算法在运动学的控制器被开发接近未知运动学的参数，和一个简单单个层的神经网络被用来表示高度非线性的机器人动力学以知道并且未知参数。以便在追踪性能上稀释不确定性和骚乱的效果，一个滑动模式控制术语被加到动态控制器。在为不明确的动态系统的反馈控制器的确定的设计，不确定性的标准上的上面的界限是重要线索保证靠近环的系统的稳定性。然而，因为不确定性的结构的复杂性，有时，这些上面的界限不能容易被获得。从而，简单改编法律在不确定性的标准上被建议到近似上面的界限处理这个问题。建议控制系统的稳定性通过 Lyapunov 方法被显示出。最后，为有二个激活的车轮的一个活动机器人的一个设计例子被提供，控制器的可行性被数字模拟表明。

英文摘要：

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.