Multi-Model Predictive Control Strategy Based on Improved DE Solid Waste Pyrolysis Kettle
Due to the nonlinearity,large lag,and time-varying characteristics of temperature control in the cracking kettle,an improved differential evolution(IDE)algorithm is used to adopt a solid waste multi model temperature prediction control strategy.A soft switch is used to cope with temperature changes in the solid waste thermal cracking kettle.Meanwhile,the improved DE algorithm and model predictive control(MPC)are utilized to update the model parameters,in order to minimize control errors and ensure system stability.This control strategy can adapt to temperature dynamics under different working conditions.The results show that compared with existing algorithms,the proposed algorithm has significant advantages in suppressing disturbances,with a tracking average percentage error increase of 0.11%and a root mean square error decrease of 0.0268.
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