Abstract
An output constrained control with input delay is proposed for a central heating system. Due to the delay of signal transmission and valves opening time, an input delay is considered into the system and an auxiliary system is employed to handle this issue by converting the delayed input into a delay-free one. Moreover, to ensure the output supply water temperature within a limited range, Barrier Lyapunov algorithm is involved to achieve desired control accuracy. Finally, external disturbance and model uncertainty are incorporated into the dynamic system and neural networks (NN) are trained in an online fashion for the compensation. The stability of the control system is guaranteed through rigorous Lyapunov analysis and the excellent control performance over traditional PID control is demonstrated via numerical simulation study.
Highlights
Central heating system is playing an essential role to human’s daily life and the boast of economy in everywhere all over the world
(ii) The input delay control is proposed in combination with output constraints that can regulate the tracking accuracy of the supply water temperature in the secondary loop with designed Barrier Lyapunov Function (BLF) method
A novel adaptive neural networks (NN) based constrained control has been proposed to a city central heating system in the presence of input delay
Summary
Central heating system is playing an essential role to human’s daily life and the boast of economy in everywhere all over the world. In this paper, inspired by the aforementioned researches, we will convert the original input delay heating system into a delayfree one similar to the Artstein model [10] together with the output constrained control which will be introduced in the following contents. This design will enhance to the stability. (ii) The input delay control is proposed in combination with output constraints that can regulate the tracking accuracy of the supply water temperature in the secondary loop with designed BLF method.
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