The rapid advances in microelectronics and microprocessor technologies during the past decades have made the physical integration of mechanical systems, various sensors, and computer based control implementation platform rather affordable and a standard choice for any modern precision machines. Such a hardware configuration enables the control of the overall system to be constructed in the same way as what a human brain normally does seamless integration of the fast reaction (or instantaneous feedback reaction) to immediate feedback information and the slow learning utilizing large amount of stored past information that is available in the computer based control systems. The theoretically solid nonlinear adaptive robust control (ARC) theory that has been developed recently well reflects such an intuitive integrated design philosophy of human brains, and has been experimentally demonstrated achieving better control performance than existing nonlinear robust controls (e.g., sliding mode controls) or nonlinear adaptive controls in a number of motion control applications. This paper is to expose motion control engineers to the essences of such an advanced nonlinear control design methodology. Some recent ARC research results are discussed as well. The precision motion control of a linear motor driven high-speed/highacceleration X-Y positioning stage is used as a case study and comparative experimental results are presented to illustrate the performance and practical benefits that can be achieved by the proposed ARC approach in implementation.