Robust trajectory tracking control of a marine surface vessel using asymmetric error constraints and output feedback

Abstract

This article investigates the problem of robust trajectory tracking for a marine surface vessel in the presence of asymmetrical error time-varying constraints and output feedback. To deal with system uncertainties, adaptive neural networks (NNs) are used to approximate unknown dynamics model parameters and external disturbances. To obtain unmeasured velocities, a predictive observer based on output feedback is developed to estimate unknown velocities. A tan-type asymmetric barrier Lyapunov function is used to deal with asymmetric error time-varying constraints. The high-frequency robust adaptive law is used to compensate for parameter estimation errors. The kinematic controller is designed based on the barrier Lyapunov function method, and the kinetics controller is designed base on an observer, an adaptive NN and a robust high-frequency control. All signals of the closed-loop systems are proved to be semiglobally uniformly and ultimately bounded via Lyapunov analysis, and the asymmetrical error constraints are not violated. Simulations are performed, and synthetic comparison is used to verify the feasibility and robustness of the proposed control law.

Robust Tracking Control of the Euler–Lagrange System Based on Barrier Lyapunov Function and Self‐Structuring Neural Networks

“…In [22], the BLF-based control method is proposed for robotic systems with fullstate constraints, which demonstrated that the BLF design method has advantages in dealing with state constraint problems of the El system. For research position constraint problems, a BLF-based controller is proposed for the marine vessel with uncertainty in [23], which also demonstrates the superiority of BLF in the El system design. e BLF technique can dynamically constrain the error within the specified range and guaranteed the performance of tracking control, which enhances the robustness of the control.…”

Adaptive integral terminal super‐twisting with finite‐time convergence for an unmanned surface vehicle under disturbances

“…Consider the dynamic system (5) where the functions a(𝜘, t), b(𝜘, t) satisfy Assumptions 1 and 2 for unknown parameters 𝛿 1 , 𝛿 2 , 𝛾 1 ∈ R + . Then, for any initial conditions 𝜘(0), 𝜎(0), there exist a finite-time 0 < T F and a parameter 𝜖 ∈ R + , so that a real 2-sliding mode, that is, |𝜎| ≤ 𝜂 1 and | σ| ≤ 𝜂 2 , is established ∀t ≥ T F , in presence of bounded additive (9) and multiplicative (6) perturbations with unknown boundaries, via the AST control…”

“…For fully‐actuated vessels, trajectory tracking has been widely studied. Different techniques have been applied, such as data‐driven control, 3,4 neural‐network‐based control, 5,6 and extended state observer‐based control 7 . Nevertheless, given the theoretical and practical challenge it represents, the trajectory tracking scenario is still a research interest for underactuated USVs 2,8 …”

Practical Tracking Control of a Class of Uncertain Surface Vessels Under Weak Assumptions on Uncertainties and Reference Trajectories

“…where Remark 2 Assumption 2 shows that the disturbance is bounded without any requirements on the smoothness and hence includes those of [5,11,12,14,17,21,27] where the disturbance must be continuously differentiable. Actually, the disturbance may be quite unexpected in practice, such as non-smooth or even noncontinuous, which can not be overcome by the compensation technique in the literature.…”