Sampled-data Feedback Control Law Research Articles

Robust perimeter control design for two urban regions with sampled-data and input saturation

This paper investigates the robust perimeter control for two urban regions with sampled-data and input saturation. Based on the macroscopic fundamental diagram, an uncertain network vehicle balance model is established for two urban regions. Instead of the continued feedback control, this paper designs a sampled-data feedback control law to stabilize the traffic accumulations at the desired state. Based on the Lyapunov function theory, the stability condition of two urban regions is given in the form of linear matrix inequalities (LMIs), which ensures that the traffic accumulation for each region is stabilized at the desired state. Moreover, for the inevitable disturbances, the robust saturation control strategy is designed such that the traffic accumulation for each region is robustly stabilized at the desired state, and meanwhile a less disturbance attenuation level is guaranteed. Numerical examples are given to illustrate the effectiveness of the proposed methods.

Global Asymptotical Synchronization of Chaotic Lur'e Systems Using Sampled Data: A Linear Matrix Inequality Approach

Sampled-data feedback control for master-slave synchronization schemes that consist of identical chaotic Lur'e systems is studied. Sufficient conditions for global asymptotic synchronization of such chaotic Lur'e systems are obtained using the free-weighting matrix approach and expressed in terms of linear matrix inequalities (LMIs). With the help of the LMI solvers, the sampled-data feedback control law can easily be obtained to globally asymptotically synchronize Lur'e chaotic systems. The effectiveness of the proposed method is finally illustrated via numerical simulations of chaotic Chua's circuits.