On Trajectory Planning, Backstepping Controller Design and Sliding Modes in Active Front-Ends

Adaptive super‐twisting sliding mode control of three‐phase power rectifiers in active front end applications

“…are positive definite matrices under condition (24). Considering V d and V q are the two Lyapunov functions of matrices P d and P q , as shown in (28), it can be obtained that 2 , then (30) can be rewritten as the following form:…”

“…However, it should be noted that the conventional ST controller requires that the upper bound of the time derivative of the disturbance is known a priori. In many practical systems, such as fuel cell power systems [25], aircraft [26], wind turbine systems [27], power electronics [16, 28, 29], and mechanical systems such as a slosh container [30] and a teleoperation system [31, 32], the value of this boundary, i.e. the Lipschitz constant, cannot be easily obtained.…”

Sliding-Mode Observer Based Voltage-Sensorless Model Predictive Power Control of PWM Rectifier Under Unbalanced Grid Conditions

“…Though sliding mode theory has been widely investigated in the design of controllers for PWM rectifiers [15], [16], relatively little research on sliding mode observers has been carried out for grid voltage estimation, especially under unbalanced grid conditions. The main reason may be the potential problem of high frequency chattering, which would introduce undesired ripple components in the control system.…”

Dynamic surface method–based adaptive backstepping control for the permanent magnet synchronous motor on parameter identification

“…Combined with Lyapunov’s function, the algorithm derives the final system control law and ensures the stability of the system. Backstepping sliding-mode variable structure control 8–10 approach has been used due to its favorable advantages, such as insensitive to parameter uncertainties and external disturbances, but the drawback of chattering is hard to overcome. In the studies of Anand and Narendran 11 and Lee et al, 12 backstepping feedback linearization control is presented which transformed the original nonlinear model into a linear model.…”