Abstract: This paper presents a tracking control strategy based on Lyapunov approach for nonholonomic wheeled mobile robot. This control strategy consists of two levels. First, a kinematic controller is developed to adjust the right and left wheel velocities. Using this velocity control law, the stability of the tracking error is guaranteed using Lyapunov approach. This kinematic controller cannot be generated directly by the motors. To overcome this problem, the second level of the controllers, dynamic control, is designed. This dynamic control law is developed based on Lyapunov theory in order to track the desired trajectories of the mobile robot. The stability of the tracking error is proved using Lupunov and Barbalat approaches. Simulation results on a nonholonomic wheeled mobile robot are given to demonstrate the feasibility and effectiveness of the presented approach.
Abstract: This paper studies a secondary voltage control
framework of the microgrids based on the consensus for a
communication network of multiagent. The proposed control is
designed by the communication network with one-way links. The
communication network is modeled by a directed graph. At this
time, the concept of sampling is considered as the communication
constraint among each distributed generator in the microgrids. To
analyze the sampling effects on the secondary voltage control of
the microgrids, by using Lyapunov theory and some mathematical
techniques, the sufficient condition for such problem will be
established regarding linear matrix inequality (LMI). Finally, some
simulation results are given to illustrate the necessity of the
consideration of the sampling effects on the secondary voltage control
of the microgrids.
Abstract: This paper describes a sliding mode controller for
autonomous underwater vehicles (AUVs). The dynamic of AUV
model is highly nonlinear because of many factors, such as
hydrodynamic drag, damping, and lift forces, Coriolis and centripetal
forces, gravity and buoyancy forces, as well as forces from thruster.
To address these difficulties, a nonlinear sliding mode controller is
designed to approximate the nonlinear dynamics of AUV and
improve trajectory tracking. Moreover, the proposed controller can
profoundly attenuate the effects of uncertainties and external
disturbances in the closed-loop system. Using the Lyapunov theory
the boundedness of AUV tracking errors and the stability of the
proposed control system are also guaranteed. Numerical simulation
studies of an AUV are included to illustrate the effectiveness of the
presented approach.
Abstract: In this paper, we propose a sensorless backstepping control of induction motor (IM) associated with three levels neutral clamped (NPC) inverter. First, the backstepping approach is designed to steer the flux and speed variables to theirs references and to compensate the uncertainties. A Lyapunov theory is used and it demonstrates that the dynamic trajectories tracking are asymptotically stable. Second, we estimate the rotor flux and speed by using the adaptive Luenberger observer (ALO). Simulation results are provided to illustrate the performance of the proposed approach in high and low speeds and load torque disturbance.
Abstract: In this paper, we propose a robust controller design method for discrete-time systems with sector-bounded nonlinearities and time-varying delay. Based on the Lyapunov theory, delaydependent stabilization criteria are obtained in terms of linear matrix inequalities (LMIs) by constructing the new Lyapunov-Krasovskii functional and using some inequalities. A robust state feedback controller is designed by LMI framework and a reciprocally convex combination technique. The effectiveness of the proposed method is verified throughout a numerical example.
Abstract: This paper presents a method for functional projective H∞ synchronization problem of chaotic systems with external disturbance. Based on Lyapunov theory and linear matrix inequality (LMI) formulation, the novel feedback controller is established to not only guarantee stable synchronization of both drive and response systems but also reduce the effect of external disturbance to an H∞ norm constraint.
Abstract: An adaptive neural network controller for
autonomous underwater vehicles (AUVs) is presented in this paper.
The AUV model is highly nonlinear because of many factors, such as
hydrodynamic drag, damping, and lift forces, Coriolis and centripetal
forces, gravity and buoyancy forces, as well as forces from thruster.
In this regards, a nonlinear neural network is used to approximate the
nonlinear uncertainties of AUV dynamics, thus overcoming some
limitations of conventional controllers and ensure good performance.
The uniform ultimate boundedness of AUV tracking errors and the
stability of the proposed control system are guaranteed based on
Lyapunov theory. Numerical simulation studies for motion control of
an AUV are performed to demonstrate the effectiveness of the
proposed controller.
Abstract: This paper presents a new adaptive impedance control
strategy, based on Function Approximation Technique (FAT) to
compensate for unknown non-flat environment shape or time-varying
environment location. The target impedance in the force controllable
direction is modified by incorporating adaptive compensators and the
uncertainties are represented by FAT, allowing the update law to be
derived easily. The force error feedback is utilized in the estimation
and the accurate knowledge of the environment parameters are not
required by the algorithm. It is shown mathematically that the
stability of the controller is guaranteed based on Lyapunov theory.
Simulation results presented to demonstrate the validity of the
proposed controller.