Takayuki Nakayama

A new gravity compensation mechanism for lower limb rehabilitation

This paper proposes a new mechanical gravity compensation mechanism suitable for the wearable lower limb rehabilitation system. Although the previous gravity compensation systems can also compensate the gravitational moment exerting on each joint perfectly, they are not sufficiently safe if they are applied to the wearable rehabilitation systems because the springs and wires must be barely stretched between the limbs over the joints. In the proposed system, the mechanisms to generate the gravity compensation torques are totally embedded in the link body, so that it can be said that the proposed gravity compensation systems are safer than previous ones. The gravity compensation ability of the proposed mechanism and the effectiveness of the proposed system as a lower limb rehabilitation system are examined by some computer simulations and experiment using the actual equipment.

Trajectory Tracking Control of Tendon Driven Robots Using Delayed Force Feedback

This paper proposed a trajectory tracking controller for the tendon driven robot with reference to the structure of the biological control systems. The proposed controller can achieve the quick tracking to the desired trajectories by applying the delayed reflexive force feedback. Whereas the load compensation by the reflexive force feedback makes the quick tracking possible, on the other side, it occasionally destabilizes the controlled system. Thus, in the proposed controller, the adaptive controller which is derived through the modeling of the cerebellum is incorporated to stabilize the motion. The stability of the proposed controller is proven using the Lyapunov-Krasovskii stability theorem. The effectiveness of the proposed controller is examined through some simulations executed for the two link tendon driven robot.

Stability analysis of output feedback receding horizon controller with Kalman-Bucy filter

This paper proposed a model predictive controller with state observer for the system whose internal state can not be fully measured. The proposed controller is constructed by the combination of the receding horizon optimal regulator and the Kalman-Bucy type IIR state observer in the sense of the certainty equivalence principle. The stability of the controlled system is analyzed in the same way as the previous method proposed by Kwon et al. The stability conditions are given by Riccati differential inequality and Lyapunov differential inequality. The feasibility of the proposed method is shown by a simple numerical example.

Bio-mimetic Trajectory Tracking Control of Tendon driven Robot Using Delayed Force Feedback

Tendon driven robots can contact with environment softly at any time by grace of the intrinsic elasticity of actuators. Meanwhile it is difficult to manipulate them accurately due to their own flexibilities. In the biologic systems, the muscles are controlled by the spinal cord and cerebellum at the lowest level. Due to those control systems, we can manipulate our limbs as intended. Thus, this paper attempts to develop a new trajectory tracking controller for the tendon driven robot by integrating the computational models of the spinal cord and cerebellum in the same manner as the biological system. The proposed controller consists of the reflex control inputs composed of the delayed force feedback and PD position error feedback, and the adaptive controller which estimates and eliminates the excess reflex component of reflexes caused by the inertial force. The asymptotic stability of the controlled system is proven along the Liapunov-Krasovskii stability theorem. The effectiveness of the proposed controller and the dependence of the control performance on delays are examined through some computer simulations.