摘要：This paper is concerned with the practical application control of a pneumatically actuated Stewart-Gough platform with 6-degrees of freedom （6-DOF）. The control approach for motion control of the platform is presented using a modern control technique, namely, linear quadratic Gaussinn （LQG） with reference tracking. The LQG controller is the combination of a Kalman filter, i.e., a linear-quadratic estimator （LQE） with a linear-quadratic regulator （LQR）. The robustness of the control scheme is accessed under various load conditions, and the experimental results are shown.

摘要：Soft-sensing is widely used in industrial applications. The traditional soft-sensing structure is open-loop without correction mechanism. If the working condition is changed or there is unknown disturbance, the forecast result of soft-sensing model may be incorrect. In order to obtain accurate values, it is necessary to carry out online correction. In this paper, a semiclosed-loop framework (SLF) is proposed to establish a soft-sensing approach, which estimates the input variables in the next moment by a prediction model and calibrates the output variables by a compensation model. The experimental results show that the proposed method has better prediction accuracy and robustness than other open-loop models.

摘要：Two types of coaxial self-balancing robots(CSBR)were proposed,one can be used as a mobile robot platform for parts transporting in unmanned factory or as an inspector in dangerous areas,and the other can be used as a personal transporter ridden in *** designing and control structures as well as control strategies were described and compared in order to get a general way to develop such robots.A state feedback controller and a fuzzy controller were designed for the robot using DC servo motors and the robot using torque motors,*** experiments indicate that the robots can realize various desired operations smoothly and agilely at the velocity of 0.6 m/s with an operator of 65 ***,the robustness of the controllers is revealed since these controllers can stabilize the robot even with unknown external disturbances.