In this paper, the tracking control of a underactuated quadrotor aerial vehicle is presented where position and yaw trajectory tracking is achieved using feedback control system. The control design is complicated by considering parametric uncertainty in the dynamic modeling of the quadrotor aerial-robot. Robust control schemes are then designed using a Lyapunov-based approach to compensate for the unknown parameters in each dynamic subsystem model. Lyapunov-type stability analysis suggests a global uniform ultimately bounded (GUUB) tracking result.

In this paper, we design an adaptive position/force controller for robot manipulators during constrained motion. The proposed controller can compensate for parametric uncertainty while only requiring measurements of link position and end-effector force. A filtering technique is utilized to produce a pseudo-velocity error signal and thus, eliminate the need for link velocity measurements. The control strategy provides semiglobal asymptotic tracking performance for the end-effector position and the interaction force between the constraint and the end-effector. An experimental implementation of the proposed controller on a two-link planar robot is also presented.

Presents a control strategy for the horizontal position control of a two degree-of-freedom overhead crane. The approach transforms the underactuated crane dynamics into a form similar to the well known ball-and-beam dynamics. A controller is then developed based on the work of Teel (1992, 1995) for the transformed dynamics using a saturation control design technique. The control approach is based on a crane model which includes the typically neglected, higher-order nonlinearities. The resulting controller provides for asymptotic positioning of the crane payload from a large set of initial conditions. Experimental trials demonstrate the performance of the proposed controller while a computer simulation is used to suggest the benefit of the proposed saturation controller over a standard linear controller.

In this paper, we consider the problem of designing a position/force controller for robot manipulators during constrained motion. The proposed controllers are based on exact knowledge of the system dynamics and do not require measurements of link velocity and end-effector force. The elimination of velocity measurements is accomplished by two different methods: 1) a model-based velocity observer, and 2) a high-pass filtering technique. Both of the controllers also include an open-loop force control strategy to achieve semi-global exponential end-effector position/velocity/force tracking.

In this paper, we propose a robust output feedback link position tracking controller for the full-order model used to describe rigid-link flexible-joint (RLFJ) robot manipulators. The method uses a bank of dynamic filters, with the link position tracking error as the input, to generate surrogates for the immeasurable system states. One of these generated filter states is then used in the feedback control strategy. The method is distinguished from previous results by the limited amount of modeling information required, the utilization of only link position measurements, and the overall simplicity of the controller. Even though the approach only requires link position measurements, the controller exhibits good robustness properties while ensuring semi-global uniformly ultimately bounded link position tracking.

In this paper an adaptive partial state feedback controller is designed for rigid-link electrically-driven (RLED) robot manipulators actuated by multi-phase motors. The controller is based on structural knowledge of the electromechanical dynamics of the RLED robot and measurements of link position and electrical winding current in each of the link actuators. The proposed controller is designed to adapt for parametric uncertainty in the electromechanical dynamics while utilizing a dynamic filter to generate link velocity tracking error information. The controller, adaptation laws, and the pseudo-velocity filter are designed via a Lyapunov-like approach, the benefit of which is that at the end of the design procedure, the controller can be mathematically shown to produce semiglobal asymptotic link position tracking.

In this paper, we present an adaptive partial state feedback position/force controller for rigid-link robot manipulators under constrained motion. The proposed controller can compensate for parametric uncertainty while only requiring measurements of link position and end-effector force. The control strategy provides semi-global asymptotic tracking performance for the position of the end-effector and the interaction force between the constraint and the end-effector.