A part of engine torque is used to overcome the interior friction and to accelerate engine inertia. To enhance the driveability at the clutch slip control of AMT(Automated Manual Transmission) or parallel type hybrid system, it is important to know the exact drving torque of clutch. In this study, engine friction and rotational inertia are estimated by using LMS(Least Mean Square) method with vehicle test result. To verify the validity of method, the performance of vehicle is simulated with adjusted parameters. The test result and simulation result show the similar trend.

In this paper, a method for estimation of external force on an end-effector using joint torque sensor is proposed. The method is based on portion of measure torque caused by external force. Due to noise in the torque measurement data from the torque sensor, a recursive least-square estimation algorithm is used to ensure a smoother estimation of the external force data. However it is inevitable to create a delay for the sensor to detect the external force. In order to reduce the delay, modified recursive least-square is proposed. The performance of the proposed estimation method is evaluated in an experiment on a developed six-degree-of-freedom robot. By using NI DAQ device and Labview, the robot control, data acquisition and The experimental results output are processed in real time. By using proposed modified RLS, the delay to estimate the external force with the RLS is reduced by 54.9%. As an experimental result, the difference of the actual external force and the estimated external force is 4.11% with an included angle of 5.04° while in dynamic state. This result shows that this method allows joint torque sensors to be used instead of commonly used external sensory system such as F/T sensors.

A variable release torque-based compliance spring-clutch (VCSC) is presented. VCSC is a safe joint to reduce the impact of collisions between humans and robots. It is composed of four functional plates, balls, springs to make some functions in compliant movement, release mechanism, gravity compensation during its work. Also, it can estimate torque applied to a joint by using distance sensor and parameters of cam profile. The measured variable torque of prototype is 4.3~7.6 Nm and release torque is 4.3 Nm. In our future studies, a calibration for torque estimation will be conducted.

In this paper, an external torque estimation problem in one-degree-of-freedom (1-DOF) flexible-joint robot equipped with a joint-torque sensor is revisited. Since a sensor torque from the jointtorque sensor is distorted by two dynamics having a spring connection, i.e., motor dynamics and link dynamics of a flexible-joint robot, a model-based estimation, rather than a simple linear spring model, should be required to extract external torques accurately. In this paper, an external torque estimation algorithm for a 1-DOF flexible-joint robot is proposed. This algorithm estimates both an actuating motor torque from the motor dynamics and an external link torque from the link dynamics simultaneously by utilizing the flexible-joint robot model and the Kalman filter estimation based on random-walk model. The basic structure of the proposed algorithm is explained, and the performance is investigated through a custom-designed experimental testbed for a vertical situation under gravity.