The fault-tolerant consensus problem for leader-following nonlinear multi-agent systems with actuator faults is mainly investigated.A new super-twisting sliding mode observer is constructed to estimate the velocity an...The fault-tolerant consensus problem for leader-following nonlinear multi-agent systems with actuator faults is mainly investigated.A new super-twisting sliding mode observer is constructed to estimate the velocity and undetectable fault information simultaneously.The time-varying gain is introduced to solve the initial error problem and peak value problem,which makes the observation more accurate and faster.Then,based on the estimated results,an improved sliding mode fault-tolerant consensus control algorithm is designed to compensate the actuator faults.The protocol can guarantee the finite-time consensus control of multi-agent systems and suppress chattering.Finally,the effectiveness and the superiority of the observer and control algorithm are proved by some simulation examples of the multi-aircraft system.展开更多
This paper presents an adaptive gain,finite-and fixedtime convergence super-twisting-like algorithm based on a revised barrier function,which is robust to perturbations with unknown bounds.It is shown that this algori...This paper presents an adaptive gain,finite-and fixedtime convergence super-twisting-like algorithm based on a revised barrier function,which is robust to perturbations with unknown bounds.It is shown that this algorithm can ensure a finite-and fixed-time convergence of the sliding variable to the equilibrium,no matter what the initial conditions of the system states are,and maintain it there in a predefined vicinity of the origin without violation.Also,the proposed method avoids the problem of overestimation of the control gain that exists in the current fixed-time adaptive control.Moreover,it shows that the revised barrier function can effectively reduce the computation load by obviating the need of increasing the magnitude of sampling step compared with the conventional barrier function.This feature will be beneficial when the algorithm is implemented in practice.After that,the estimation of the fixed convergence time of the proposed method is derived and the impractical requirement of the preceding fixed-time adaptive control that the adaptive gains must be large enough to engender the sliding mode at time t=0 is discarded.Finally,the outperformance of the proposed method over the existing counterpart method is demonstrated with a numerical simulation.展开更多
基金supported by Key Laboratories for National Defense Science and Technology(6142605200402)the Aeronautical Science Foundation of China(20200007018001)+2 种基金the National Natural Science Foundation of China(61922042)the Aero Engine Corporation of China Industry-University-Research Cooperation Project(HFZL2020CXY011)the Research Fund of State Key Laboratory of Mechanics and Control of Mechanical Structures(Nanjing University of Aeron autics and astronautics)(MCMS-I-0121G03)。
文摘The fault-tolerant consensus problem for leader-following nonlinear multi-agent systems with actuator faults is mainly investigated.A new super-twisting sliding mode observer is constructed to estimate the velocity and undetectable fault information simultaneously.The time-varying gain is introduced to solve the initial error problem and peak value problem,which makes the observation more accurate and faster.Then,based on the estimated results,an improved sliding mode fault-tolerant consensus control algorithm is designed to compensate the actuator faults.The protocol can guarantee the finite-time consensus control of multi-agent systems and suppress chattering.Finally,the effectiveness and the superiority of the observer and control algorithm are proved by some simulation examples of the multi-aircraft system.
文摘This paper presents an adaptive gain,finite-and fixedtime convergence super-twisting-like algorithm based on a revised barrier function,which is robust to perturbations with unknown bounds.It is shown that this algorithm can ensure a finite-and fixed-time convergence of the sliding variable to the equilibrium,no matter what the initial conditions of the system states are,and maintain it there in a predefined vicinity of the origin without violation.Also,the proposed method avoids the problem of overestimation of the control gain that exists in the current fixed-time adaptive control.Moreover,it shows that the revised barrier function can effectively reduce the computation load by obviating the need of increasing the magnitude of sampling step compared with the conventional barrier function.This feature will be beneficial when the algorithm is implemented in practice.After that,the estimation of the fixed convergence time of the proposed method is derived and the impractical requirement of the preceding fixed-time adaptive control that the adaptive gains must be large enough to engender the sliding mode at time t=0 is discarded.Finally,the outperformance of the proposed method over the existing counterpart method is demonstrated with a numerical simulation.
