Robust path-following control of underactuated AUVs with multiple uncertainties and state constraints

This paper proposes a novel robust controller for horizontal path-following problem of an underactuated AUV subject to multiple uncertainties and state constraints. Firstly, four reduced-order extended state observes (ESOs) are designed to estimate the multiple uncertainties, and the estimated values are adopted in the design of kinematic and dynamic controller. Secondly, to address the state constraints, the barrier Lyapunov function is incorporated with the kinematic controller. To resolve the problem of input saturation, the auxiliary design system is utilized in the dynamic controller. To address the problem of “explosion of complexity” inherent in the conventional back-stepping method, a nonlinear tracking differentiator is utilized to obtain the derivative of the desired yaw speed. Finally, the results of numerical simulation are performed to demonstrate the effectiveness of the proposed controller.

The path-following control of the underactuated AUV with input saturation and multiple disturbances

Autonomous underwater vehicle (AUV) in marine resource surveys plays an important role. This paper proposes a new path-following control frame for the underactuated AUV with input saturation and multiple disturbances. The disturbances include external disturbances, model parameter uncertainties, unmodeled dynamics and other random disturbances. Compared to most of previously published literatures, which treat disturbances as lumped disturbances, a composite hierarchical anti-disturbance control (CHADC) strategy is adopted to achieve higher precision path following. A disturbance observer (DOB) is constructed to estimate and eliminate the disturbances with partial known information, while the H ∞ theory is used to optimize the path-following controller to attenuate the other disturbances satisfying the L 2-norm bound condition and improve the robustness of system. Besides, Lyapunov direct method and back-stepping method are used to design the path-following controller, where the input saturation is considered, the extended state observer (ESO) is used to estimate the uncertainty of kinematic controller and the nonlinear tracking differentiator (NTD) is used to simplify the controller. Finally, simulations are given to demonstrate the effectiveness of the proposed control law.

A Benchmarking analysis of analytical and advanced nonlinear tracking control techniques

This paper aims at studying two advanced techniques that are used in control theory of nonlinear affine systems. These later techniques tackle the problem of the trajectory tracking with high steady state performances. The objective of this work is to compare and analyze the dynamical behavior of the desired output when controlled by the gain scheduling method and afterward with a neural control approach. Both techniques are evaluated through a numerical simulation study of a photovoltaic system, which is characterized by hard nonlinear features and challenges. The efficiency and limitations of both techniques are accurately discussed.

Robust Nonlinear Tracking Control for Unmanned Aircraft in the Presence of Wake Vortex

The flight trajectory of unmanned aerial vehicles (UAVs) can be significantly affected by external disturbances such as turbulence, upstream wake vortices, or wind gusts. These effects present challenges for UAV flight safety. Hence, addressing these challenges is of critical importance for the integration of unmanned aerial systems (UAS) into the National Airspace System (NAS), especially in terminal zones. This work presents a robust nonlinear control method that has been designed to achieve roll/yaw regulation in the presence of unmodeled external disturbances and system nonlinearities. The data from NASA-conducted airport experimental measurements as well as high-fidelity Large Eddy Simulations of the wake vortex are used in the study. Side-by-side simulation comparisons between the robust nonlinear control law and both linear H∞ and PID control laws are provided for completeness. These simulations are focused on applications involving small UAV affected by the wake vortex disturbance in the vicinity of the ground (which models the take-off or landing phase) as well as in the out-of-ground zone. The results demonstrate the capability of the proposed nonlinear controller to asymptotically reject wake vortex disturbance in the presence of the nonlinearities in the system (i.e., parametric variations, unmodeled, time-varying disturbances). Further, the nonlinear controller is designed with a computationally efficient structure without the need for the complex calculations or function approximators in the control loop. Such a structure is motivated by UAV applications where onboard computational resources are limited.

Finite-time Tracking Control with Velocity Constraints for the Stochastic Rehabilitative Training Walker System Considering Different Rehabilitee Masses

This study discusses a finite-time tracking controller for a rehabilitative training walker that imposes velocity constraints. The walker was described using a stochastic model through which the rehabilitee mass can randomly change, and a velocity constraint method was proposed to control the velocity input to every omniwheel based on a model predictive algorithm. This approach is novel in that the velocity constraint information obtained from the kinematics model was used to design the tracking controller based on the stochastic dynamic model, thus successfully constraining the actual velocity of walker as per the stochastic system. The nonlinear tracking controller was built for the stochastic rehabilitative walker to make the system’s finite time stable. Also, simulation and experiment were performed, and results confirmed that the proposed tracking control method with velocity constraints is very effective, so it may enable various rehabilitees to train safely.