Luis Govinda García-Valdovinos

Transparency has been a major objective in bilateral teleoperation systems, even in the absence of time delay induced by the communication channel, since a high degree of transparency would allow humans to drive the remote teleoperator as if he or she were directly interacting with the remote environment, with the remote teleoperator as a physical and sensorial extension of the operator. When fast convergence of position and force tracking errors are ensured by the control system, then complete transparency is obtained, which would ideally guarantee humans to be tightly kinaesthetically coupled. In this paper a model-free Cartesian second order sliding mode (SOSM) PD control scheme for nonlinear master-slave systems is presented. The proposed scheme does not rely on velocity measurements and attains very fast convergence of position trajectories, with bounded tracking of force trajectories, rendering a high degree of transparency with lesser knowledge of the system. The degree of transparency can easily be improved by tuning a feedback gain in the force loop. A unique energy storage function is introduced; such that a similar Cartesian-based controller is implemented in the master and slave sides. The resulting properties of the Cartesian control structure allows the human operator to input directly Cartesian variables, which makes clearer the kinaesthetic coupling, thus the proposed controller becomes a suitable candidate for practical implementation. The performance of the proposed scheme is evaluated in a semi-experimental setup.

Underwater remotely operated vehicles (ROVs) play an important role in a number of shallow and deep-water missions for marine science, oil and gas extraction, exploration and salvage. In these applications, the motions of the ROV are guided either by a human pilot on a surface support vessel through an umbilical cord providing power and telemetry, or by an automatic pilot. In the case of automatic control, ROV state feedback is provided by acoustic and inertial sensors and this state information, along with a controller strategy, is used to perform several tasks such as station-keeping and auto-immersion/heading, among others. In this paper, the modelling, design and control of the Kaxan ROV is presented: i) The complete six degrees of freedom, non linear hydrodynamic model with its parameters, ii) the Kaxan hardware/software architecture, iii) numerical simulations in Matlab/Simulink platform of a model-free second order sliding mode control along with ocean currents as disturbances and thruster dynamics, iv) a virtual environment to visualize the motion of the Kaxan ROV and v) experimental results of a one degree of freedom underwater system.

Tracking of robot manipulators has been addressed with the aid of model-based regressor, and several techniques have been proposed, wherein asymptotic, and even exponential stability properties are obtained depending on how much knowledge is assumed over the regressor and the physical parameters of the robot. Well-posed finite time convergence using time base generators has been obtained, in contrast to the ill-posed terminal attractors with fractional powers. When the regressor is completely unknown, soft computing techniques have been proposed to reconstruct it and carry out adaptive compensation, while another input stabilize the system. However, they usually lack of formal stability results for tracking and they are computationally expensive to implement. In this paper, a new and very simple, chattering-free, decentralized nonlinear PID controller that does not use the regressor (and does not attempt to reconstruct it) is proposed, which guarantees local tracking in arbitrary finite time for robot manipulators. Simulation results show the performance of our controller compared versus regressor-based controllers and linear PID control.