During sea missions, underwater vehicles are exposed to changes in the parameters of the system and subject to persistent external disturbances due to the ocean current influence. These issues make the design of a robust controller a quite challenging task. This paper focuses on the design of a adaptive high order sliding mode control for trajectory tracking on an underwater vehicle. The main feature of the developed control law is that it preserves the advantages of robust control, it does not need the knowledge of the upper bound of the disturbance and easy tuning in real applications. Using Lyapunov concept, asymptotic stability of the closed-loop tracking system is ensured. The effectiveness and robustness of the proposed controller for trajectory tracking in depth and yaw dynamics are demonstrated through real-time experiments.

International audienceThis paper deals with two nonlinear controllers based on saturation functions with varying parameters, for set-point regulation and trajectory tracking on an Underwater Vehicle. The proposed controllers combine the advantages of robust control and easy tuning in real applications. The stability of the closed-loop system with the proposed nonlinear controllers is proven by Lyapunov arguments. Experimental results for the trajectory tracking control in 2 degrees of freedom, these are the depth and yaw motion of an underwater vehicle, show the performance of the proposed control strategy

During sea missions, underwater vehicles are often exposed to changes in the parameters of their control systems and subject to external disturbances due to the influences of ocean currents. These issues make the design of a robust controller quite a challenging task. This paper focuses on the design of a nonlinear PID controller, based on a set of saturation functions for trajectory tracking on an underwater vehicle. The main feature of the proposed control law is that it preserves the advantages of robust control and remains easy to fine-tune in real applications. Using the Lyapunov concept, we prove the asymptotic stability of the closed-loop tracking system. The effectiveness and robustness of our proposed controller for trajectory tracking in depth and yaw dynamics is demonstrated through real-time experiments.

This paper deals with a control approach dedicated to stable limit cycle generation for underactuated mechanical systems. The proposed approach is based on partial nonlinear feedback linearization and dynamic control for optimal periodic reference trajectories tracking. The computation of the reference trajectories is performed in order to optimize the behavior of the whole dynamics of the system and especially its zero dynamics at the end of each cycle. Simulation results as well as experiments show the performance and the efficiency of the proposed control scheme.

Complex and highly coupled dynamics, time-variance, unpredictable disturbances and lack of knowledge of hydrodynamic parameters, complicate the control of underwater vehicles. This paper deals with the adaptive disturbance observer design for the robust trajectory tracking problem for underwater vehicles in presence of unknown external disturbances and parametric uncertainties. First, the dynamics of the vehicle is transformed into the socalled regular form. Then, based on the Extended State Observer technique and High Order Sliding Modes Control, a disturbance observer is proposed. Furthermore, the gains of the observer are automatically adjusted by the introduction of an adaption law. The stability of the whole controller/observer scheme is proven using Lyapunov's arguments. The adaptive disturbance observer aims to improve the Backstepping and nonlinear PD controllers. Real-Time experiments demonstrate the effectiveness of the proposed algorithm for the trajectory tracking task under several scenarios.

We address the problem of stabilizing a planar biped robot on a complete walking cycle. Our approach is based on singling out the three fundamental phases of motion of a biped : single and double-support, separated (sequentially) by an impact "instantaneous" phase. We propose control laws to drive the robot for a finite time during each phase, while ensuring certain robustness vis-a-vis the impacts which are treated as external perturbations. We also provide some simulation results.

Cable-driven parallel robots (CDPR) are efficient manipulators able to carry heavy payloads across large workspaces. Therefore, the dynamic parameters such as the mobile platform mass and center of mass location may considerably vary. Without any adaption, the erroneous parametric estimate results in mismatch terms added to the closed-loop system, which may decrease the robot performances. In this paper, we introduce an adaptive dual-space motion control scheme for CDPR. The proposed method aims at increasing the robot tracking performances, while keeping all the cable tensed despite uncertainties and changes in the robot dynamic parameters. Reel-time experimental tests, performed on a large redundantly actuated CDPR prototype, validate the efficiency of the proposed control scheme. These results are compared to those obtained with a non-adaptive dual-space feedforward control scheme.

A Model Predictive Control (MPC) strategy is proposed in this paper for large-dimension cable-driven parallel robots working at low speeds. The latter characteristic reduces the non-linearity of the system within the MPC prediction horizon. Therefore, linear MPC is applied and compared with two commonly used strategies: Sliding mode control and PID+ control. The simulations aim at comparing disturbance rejection performances and the results indicate a superior performance of the proposed controller. Indeed, MPC takes into account control limits (cable tension limits) directly in the control design which allows the controller to better exploit the robot capabilities. In addition, actuation redundancy is resolved as an integral part of the control strategy, instead of calculating the desired wrench and then applying a tension distribution method.