This paper presents an error-constrained line-of-sight (ECLOS) path-following control method for a surface vessel subject to uncertainties, disturbances, and actuator saturation and faults. Based on a cascaded three degrees-of-freedom model of surface vessel, the backstepping technique is adopted as the main control framework. Error constraint of the vessel position is handled by integrating a novel tan-type barrier Lyapunov function. The proposed ECLOS method is in accordance with the classical line-of-sight method where no constraint is imposed. A nonlinear disturbance observer is developed to estimate the lumped disturbance that comprises the effects of parametric uncertainties, external environment disturbances, and actuator saturation and faults. It is proved that under the proposed control, the constrained requirements on the vessel position error are never violated and all closed-loop signals are uniformly ultimately bounded, regardless of fully actuated or under-actuated control configuration. Simulation results and comparisons illustrate the effectiveness and advantages of the proposed ECLOS path-following method.

This paper presents a six-degree-of-freedom relative motion control method for autonomous spacecraft rendezvous and proximity operations subject to input saturation, full-state constraint, kinematic coupling, parametric uncertainty, and matched and mismatched disturbances. Relative rotational and relative translational controllers are developed separately based on a unified adaptive backstepping technique. Both element-wise and norm-wise adaptive estimation techniques are used for handling parametric uncertainties, kinematic couplings, and matched and mismatched disturbances, where the bounds of disturbances are unknown. Two auxiliary design systems are employed to deal with input saturation in the relative rotational and relative translational control designs, and the stability of the saturated control solution is verified. Full-state constraint of the relative pose motion is handled by using barrier Lyapunov functions while achieving a satisfactory control performance. All signals in the closed-loop system are guaranteed to be uniformly ultimately bounded, and the relative motion states are all restricted within the known constraints. Compared with the previous control designs of spacecraft rendezvous and proximity operations, the proposed control strategy in this paper can simultaneously deal with input saturation, full-state constraint, kinematic coupling, parametric uncertainty, and matched and mismatched disturbances. Experimental simulation results validate the performance and robustness improvement of the proposed control strategy.

A fixed-time trajectory tracking control method for uncertain robotic manipulators with input saturation based on reinforcement learning (RL) is studied. The designed RL control algorithm is implemented by a radial basis function (RBF) neural network (NN), in which the actor NN is used to generate the control strategy and the critic NN is used to evaluate the execution cost. A new nonsingular fast terminal sliding mode technique is used to ensure the convergence of tracking error in fixed time, and the upper bound of convergence time is estimated. To solve the saturation problem of an actuator, a nonlinear antiwindup compensator is designed to compensate for the saturation effect of the joint torque actuator in real time. Finally, the stability of the closed-loop system based on the Lyapunov candidate is analyzed, and the timing convergence of the closed-loop system is proven. Simulation and experimental results show the effectiveness and superiority of the proposed control law.

The problem of control input saturation and measurement uncertainties in spacecraft attitude control systems is investigated in this paper. Asymmetric limitation of the control torque and additive attitude measurement errors are considered in the backstepping attitude controller design. Stable antiwindup compensator is employed to handle the adverse effect of input saturation. The additive attitude measurement errors, external disturbances, and parametric uncertainties are compensated by the outputs of stable nonlinear disturbance observers in the robust controller design. The tuning conditions of controller parameters are derived based on the Lyapunov analysis, and it is proved that attitude, angular velocity, saturation compensator states, and disturbance observer states converge to small neighborhoods of zero. Simulation results illustrate the effectiveness of the proposed control approach.