Self-Organizing Approximation Command Filtered Backstepping Control for Higher Order SISO Systems in Internet of Things

Abstract

With the rapid development of the Internet of Things (IOT) and increasing research on tracking control of the affine IOT systems with uncertainty, a nonlinear control method of command filtering backstepping with self-organizing approximation is proposed. A command filter with a saturation structure is used to eliminate the analytic computation of command derivatives, and tracking errors are redefined to compensate the discrepancy between the command filtered signals and the analytic computation of command derivatives. Command filtered backstepping is used to decouple the higher IOT system and simplify the structure of the IOT system. Self-organizing approximation is used to online approximate the uncertain and eliminate the effect of the uncertain in the IOT system. The approximation for the uncertain is finished by a linear product between a set of basis functions and weighted functions on the local region. The weighted sum of compensated tracking errors is used as the prespecified tracking accuracy performance. A new local approximator is added to the control system according to the criterion based on the Lyapunov theory to enhance the capacity of the approximator when the prespecified tracking accuracy performance cannot be achieved. Finally, an application for a simple IOT system is analyzed by simulations. The simulation results show that the control method for the IOT system is effective.

Keywords

• Internet of Things system
• command filtered backstepping control
• nonlinear control systems
• self-organizing feature maps