Adaptive-gain multivariable super-twisting sliding mode control for reentry RLV with torque perturbation

Abstract

Summary Reusable launch vehicle (RLV) should be under control in the presence of model uncertainty and external disturbance, which is considered as torque perturbation in this paper during the reentry phase. Such a challenge imposes tight requirements to the enhanced robustness and accuracy of the vehicle autopilot. The key of this paper is to propose an adaptive‐gain multivariable super‐twisting sliding mode controller when considering that the bounds of uncertainty and perturbation are not known. The important features of the controller are that the adaptation algorithm can achieve non‐overestimating values of the control gains and the multivariable super‐twisting sliding mode approach can obtain a more elegant solution in finite time. According to the multiple‐time scale features, the dynamics of RLV attitude motion are divided into outer‐loop subsystem and inner‐loop subsystem. On this basis, the controllers are designed respectively to ensure the finite‐time reentry attitude tracking. In addition, a proof of the finite‐time convergence for the overall system is derived using the Lyapunov function technique and multiple‐time scale characteristic. Finally, simulation results of six degree‐of‐freedom RLV are provided to verify the effectiveness and robustness of the proposed controller in tracking the guidance commands as well as achieving a safe and stable reentry flight. Copyright © 2016 John Wiley & Sons, Ltd.

Adaptive multivariable finite‐time continuous fault‐tolerant control of rigid spacecraft

“…Parameter λ is selected according to with . In order to verify the effectiveness of our proposed AMSTW algorithm, we use the AMSTW algorithm in the work of Dong et al but with the same FNTSM surface provided in our method. The controller can be designed as with the adaptive gains α and β are as follows: where κ i > 0, i = 1,2,3,4, are arbitrary positive constants and parameter η , α m are arbitrary small positive constants.…”

“…In Figure , the control actions are provided to show the ability of alleviating the control chattering compared with the ANTSM provided in the work of Zong and Shao . In addition, the proposed algorithm can make the control gains smaller and has better tracking performance than the ASTW algorithm in the work of Dong et al, which can be seen from the variation of β in Figure .…”

“…Moreover, considering the requirement of minimum actuator energy cost, the research on adaptive‐gain STW (ASTW) SCM has been undertaken, whereby the control gains attempt to adapt to a level where they are as small as possible and yet guarantee sliding is maintained . To achieve nonoverestimating values of the control gain, an ASTW sliding mode controller was proposed in the works of Shtessel et al and Dong et al However, none of the aforementioned algorithms resulted in the minimum possible value of control. Utkin and Poznyak develop an adaptive scheme to search the minimum possible value of control based on evaluations of the equivalent control.…”

“…From theoretical aspects, the proposed algorithm guarantees that the attitude tracking errors converge to zero in finite time. However, the traditional nonoverestimating ASTW algorithm in other works can only guarantee that the errors converge to a small region of origin. To our best knowledge, this is the first work to propose a novel AMSTW sliding mode algorithm, which develops the multivariable STW SMC theory and integrates the multivariable STW algorithm with double‐layer adaptive algorithm. …”

Vector-Coupled Flight Controller Design Based on Multivariable Backstepping Sliding Mode

“…Design of control laws that ensure the stability of the whole control system. In some studies [22,23], the design of the control systems is based on the assumption with "timescale separation", wherein the slow attitude dynamics are separated from the fast angular-rate dynamics. The outer and inner controllers correspond to the slow and fast subsystems, respectively.…”