Nonlinear Control for Unstable Networked Plants in the Presence of Actuator and Sensor Limitations Using Robust Right Coprime Factorization

In this paper, a nonlinear control approach for an unstable networked plant in the presence of actuator and sensor limitations using robust right coprime factorization is proposed. The actuator is limited by upper and lower constraints and the sensor in the feedback loop is subjected to network-induced unknown time-varying delay and noise. With this nonlinear control method, we first employ right coprime factorization based on isomorphism and operator theory to factorize the plant, so that bounded input bounded output (BIBO) stability can be guaranteed. Next, continuous-time generalized predictive control (CGPC) is utilized for the unstable operator of the right coprime factorized plant to guarantee inner stability and enables the closed-loop dynamics of the system with predictive characteristics. Meanwhile, a second-DoF (degrees of freedom) switched controller that satisfies a perturbed Bezout identity and a robustness condition is designed. By using the CGPC controller that possesses predictive behavior and the second-DoF switched stabilizer, the overall stability of the plant subjected to actuator limitations is guaranteed. To address sensor limitations that exist in networked plants in the form of delay and noise which often cause system performance degradation, we implement an identity operator definition in the feedback loop to compensate for these adverse effects. Further, a pre-operator is designed to ensure that the plant output tracks the reference input. Finally, the effectiveness of the proposed design scheme is demonstrated by simulations.