Caisheng Wei

Efficient adaptive constrained control with time-varying predefined performance for a hypersonic flight vehicle:

A novel low-complexity adaptive control method, capable of guaranteeing the transient and steady-state tracking performance in the presence of unknown nonlinearities and actuator saturation, is investigated for the longitudinal dynamics of a generic hypersonic flight vehicle. In order to attenuate the negative effects of classical predefined performance function for unknown initial tracking errors, a modified predefined performance function with time-varying design parameters is presented. Under the newly developed predefined performance function, two novel adaptive controllers with low-complexity computation are proposed for velocity and altitude subsystems of the hypersonic flight vehicle, respectively. Wherein, different from neural network-based approximation, a least square support vector machine with only two design parameters is utilized to approximate the unknown hypersonic dynamics. And the relevant ideal weights are obtained by solving a linear system without resorting to specialized optimization algorithms. Based on the approximation by least square support vector machine, only two adaptive scalars are required to be updated online in the parameter projection method. Besides, a new finite-time-convergent differentiator, with a quite simple structure, is proposed to estimate the unknown generated state variables in the newly established normal output-feedback formulation of altitude subsystem. Moreover, it is also employed to obtain accurate estimations for the derivatives of virtual controllers in a recursive design. This avoids the inherent drawback of backstepping — “explosion of terms” and makes the proposed control method achievable for the hypersonic flight vehicle. Further, the compensation design is employed when the saturations of the actuator occur. Finally, the numerical simulations validate the efficiency of the proposed finite-time-convergent differentiator and control method.

Adaptive model-free constrained control of postcapture flexible spacecraft: a Euler–Lagrange approach:

This paper investigates an adaptive model-free constrained prescribed performance control approach for flexible spacecraft with an unknown captured object subject to unknown inertial properties, elastic vibration, actuator saturation, and external disturbance. First, the attitude kinematics and dynamics of the postcapture flexible spacecraft are transformed into a Euler–Lagrange form, based on which a model-free constrained attitude prescribed performance controller comprising a nominal control term and an adaptive compensation control term is developed. Then, by employing norm equalities of the Euler–Lagrange systems, a model-free adaptive scheme is designed to improve the robustness with respect to uncertainty, actuator saturation, and external disturbance just only using the state information. Compared with the existing works, the primary advantage is that the resultant controller and adaptive scheme are computationally very simple without any requirement of unknown inertial information. But the transient and steady-state performance is a priori guaranteed without resorting to repeated regulations of the controller parameters. Finally, the application to attitude stabilization and tracking of postcapture flexible spacecraft along with active vibration suppression is employed to validate the effectiveness of the proposed approach.

Event-triggered neuroadaptive control for postcapture spacecraft with ultralow-frequency actuator updates

Abstract This paper investigates an event-triggered neuroadaptive control approach for postcapture flexible spacecraft with guaranteed prespecified tracking performance in the presence of unknown inertial properties, actuator constraints, and external space perturbations. By employing the minimum-learning parameter technique into the neural proportional integral-like controller, only two adaptive parameters are required to update online, which completely avoids the tedious inertial parameter identifications and dramatically reduces the complexity of controller in the meanwhile. Compared with existing works, the primary advantage of the proposed attitude control approach is that the actuator updates are determined by the prescribed event-based conditions in an aperiodic way rather than a periodic one, which greatly reduces the actuator updates. Finally, two groups of illustrative examples are organized to validate the effectiveness of the proposed approach in terms of attitude stabilization and tracking for the postcapture flexible spacecraft.

Robust inertia-free attitude takeover control of postcapture combined spacecraft with guaranteed prescribed performance

In this paper, a robust inertia-free attitude takeover control scheme with guaranteed prescribed performance is investigated for postcapture combined spacecraft with consideration of unmeasurable states, unknown inertial property and external disturbance torque. Firstly, to estimate the unavailable angular velocity of combination accurately, a novel finite-time-convergent tracking differentiator is developed with a quite computationally achievable structure free from the unknown nonlinear dynamics of combined spacecraft. Then, a robust inertia-free prescribed performance control scheme is proposed, wherein, the transient and steady-state performance of combined spacecraft is first quantitatively studied by stabilizing the filtered attitude tracking errors. Compared with the existing works, the prominent advantage is that no parameter identifications and no neural or fuzzy nonlinear approximations are needed, which decreases the complexity of robust controller design dramatically. Moreover, the prescribed performance of combined spacecraft is guaranteed a priori without resorting to repeated regulations of the controller parameters. Finally, four illustrative examples are employed to validate the effectiveness of the proposed control scheme and tracking differentiator.

Learning-Based Adaptive Attitude Control of Spacecraft Formation With Guaranteed Prescribed Performance

This paper investigates a novel leader-following attitude control approach for spacecraft formation under the preassigned two-layer performance with consideration of unknown inertial parameters, external disturbance torque, and unmodeled uncertainty. First, two-layer prescribed performance is preselected for both the attitude angular and angular velocity tracking errors. Subsequently, a distributed two-layer performance controller is devised, which can guarantee that all the involved closed-loop signals are uniformly ultimately bounded. In order to tackle the defect of statically two-layer performance controller, learning-based control strategy is introduced to serve as an adaptive supplementary controller based on adaptive dynamic programming technique. This enhances the adaptiveness of the statically two-layer performance controller with respect to unexpected uncertainty dramatically, without any prior knowledge of the inertial information. Furthermore, by employing the robustly positively invariant theory, the input-to-state stability is rigorously proven under the designed learning-based distributed controller. Finally, two groups of simulation examples are organized to validate the feasibility and effectiveness of the proposed distributed control approach.