A Predictive Control-Based Approach to Networked Hammerstein Systems: Design and Stability Analysis
Yun‐Bo Zhao, Shuai Liu, D. Rees
Abstract
Yun‐Bo Zhao, Shuai Liu, D. Rees
Abstract
In this paper, a predictive control-based approach is proposed for a Hammerstein-type system which is closed through some form of network. The approach uses a two-step predictive controller to deal with the static input nonlinearity of the Hammerstein system and a delay and dropout compensation scheme to compensate for the communication constraints in a networked control environment. Theoretical results are presented for the closed-loop stability of the system. Simulation examples illustrating the validity of the approach are also presented.
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In this paper, a predictive control-based approach is proposed for a Hammerstein-type system which is closed through some form of network. The approach uses a two-step predictive controller to deal with the static input nonlinearity of the Hammerstein system and a delay and dropout compensation scheme to compensate for the communication constraints in a networked control environment. Theoretical results are presented for the closed-loop stability of the system. Simulation examples illustrating the validity of the approach are also presented.
Key concepts: Model predictive control, Control theory (sociology), Dropout (neural networks), Compensation (psychology), Computer science, Stability (learning theory), Nonlinear system, Networked control system