Sampled-data model-free adaptive integral sliding mode control for nonlinear continuous-time networked control systems with fading channels and packet dropouts

In this work, a sampled-data model-free adaptive integral sliding mode control (SMFAISMC) scheme is presented for nonlinear continuous-time networked control systems (NCSs) where the control input of the NCSs is assumed to be transmitted over the fading channel and the random packet dropouts is encountered at the output side simultaneously. Firstly, the original nonlinear continuous-time NCSs are converted to a linearized sampled-data model by employing the dynamic linearization (DL) method. Then, the controller gain updating algorithm and the auxiliary prediction compensation strategy are designed to counteract the adverse effects of stochastic fading and packet dropouts, respectively. Furthermore, a SMFAISMC scheme with sampling period is constructed, which is almost data -driven except that the sampling period and the structure information from the state to the output are needed. Note that the introduction of the sampling period gives the SMFAISMC scheme the ability to suppress the disadvantages of poor convergence due to the improper selection of sampling time. Finally, the boundedness of the tracking error is proved by using the contraction mapping principle and the validity of the developed SMFAISMC scheme is further verified via simulation.