TY - JOUR
T1 - Event-triggered robust control for quadrotors with preassigned time performance constraints
AU - Shao, Xingling
AU - Yue, Xiaohui
AU - Li, Jie
N1 - Publisher Copyright:
© 2020 Elsevier Inc.
PY - 2021/3/1
Y1 - 2021/3/1
N2 - In this paper, an event-triggered robust control for quadrotors with preassigned time performance constraints is presented. In order to prolong operational time and enhance mission completion efficiency subject to limited onboard power, a switching threshold event-triggered strategy is embedded in controller-to-actuator and sensor-to-controller channels, where switching threshold event-triggered based extended state observers (SET-ESO) are respectively established in the trajectory and attitude subsystems to accomplish the real-time estimation of linear velocity, angular velocity along with lumped disturbances using intermittent measurements, and the quantitative analysis between the ultimate observation error and parameters of SET-ESO is revealed. Based on the estimation results, an event-triggered output feedback control law including a robust compensation term is established to realize an anti-disturbance time-varying trajectory tracking without involving Zeno phenomena. Moreover, to eliminate severe fluctuations at the transient inherent in traditional prescribed performance control (TPPC) with a fast convergent rate, a tracking differentiator-based prescribed performance control (TDPPC) mechanism is exploited to ensure the trajectory state converge to a pre-given region with a preassigned prescribed time, such that a smooth and pre-specified finite-time tracking capability independent of control parameters is preserved. Next, with the aid of Lyapunov synthesis, all the signals involved in the closed-loop quadrotor system are proved to be bounded, and the preassigned time performance constraints are not violated. The simulation and comparison results are shown to validate the effectiveness of the proposed control scheme.
AB - In this paper, an event-triggered robust control for quadrotors with preassigned time performance constraints is presented. In order to prolong operational time and enhance mission completion efficiency subject to limited onboard power, a switching threshold event-triggered strategy is embedded in controller-to-actuator and sensor-to-controller channels, where switching threshold event-triggered based extended state observers (SET-ESO) are respectively established in the trajectory and attitude subsystems to accomplish the real-time estimation of linear velocity, angular velocity along with lumped disturbances using intermittent measurements, and the quantitative analysis between the ultimate observation error and parameters of SET-ESO is revealed. Based on the estimation results, an event-triggered output feedback control law including a robust compensation term is established to realize an anti-disturbance time-varying trajectory tracking without involving Zeno phenomena. Moreover, to eliminate severe fluctuations at the transient inherent in traditional prescribed performance control (TPPC) with a fast convergent rate, a tracking differentiator-based prescribed performance control (TDPPC) mechanism is exploited to ensure the trajectory state converge to a pre-given region with a preassigned prescribed time, such that a smooth and pre-specified finite-time tracking capability independent of control parameters is preserved. Next, with the aid of Lyapunov synthesis, all the signals involved in the closed-loop quadrotor system are proved to be bounded, and the preassigned time performance constraints are not violated. The simulation and comparison results are shown to validate the effectiveness of the proposed control scheme.
KW - Event-triggered
KW - Extended state observer
KW - Preassigned time performance constraints
KW - Quadrotors
KW - Tracking differentiator
UR - http://www.scopus.com/inward/record.url?scp=85091739751&partnerID=8YFLogxK
U2 - 10.1016/j.amc.2020.125667
DO - 10.1016/j.amc.2020.125667
M3 - Article
AN - SCOPUS:85091739751
SN - 0096-3003
VL - 392
JO - Applied Mathematics and Computation
JF - Applied Mathematics and Computation
M1 - 125667
ER -