Synthesis of Noisy Sampled-Data Networked Control Systems Under Deception Attacks: Direct Current Motor Applications

The stabilization issue of noisy sampled-data networked control systems in the presence of deception attacks and noisy sampling intervals is investigated in this paper. Firstly, networked control systems with deception attacks and noisy sampling intervals are acquired under a consistent structure. Next, feedback interconnection model with zero initial state is established, which facilitates the use of the stochastic discrete-time integral quadratic constraint. Uniform exponential stability conditions are given for networked control systems related to operators expectations with stochastic properties. Subsequently, the difficulties associated with the nonlinear term are overcome and a novel controller algorithm that enables uniform exponential stability of the networked control systems is designed. Lastly, the effectiveness of the designed algorithm is validated by numerical example and direct current motor simulation example.