Jian Tang

In wastewater treatment process (WWTP), reducing energy consumption (EC) and enhancing effluent quality (EQ) is the primary operational goal. However, the dynamical working conditions of WWTP make it challenging to balance the conflicted relationship between EC and EQ. To complete this target, the knowledge guidance and twin support vector machine classifier based dynamic multiobjective optimization control (KGTSVMC-DMOC) is designed. Firstly, the performance indices models are constructed using the incremental support vector regression, whose parameters can be online updated. Secondly, the dynamic multiobjective optimization evolution algorithm is designed to search the changeable optimal set-points of control variables (i.e. the concentration of dissolved oxygen and nitrate nitrogen). Specifically, to reduce distribution discrepancies under different working conditions, the knowledge guided subspace alignment method is proposed. To explore the nonlinear relationships between neighboring solutions, the twin support vector machine classifier is introduced. Thirdly, due to its self-organizing and adaptive nature, the event-triggered incremental PID controller is designed to track the time-varying set-points. Finally, the algorithm applicability is verified by the benchmark simulation platform of WWTP, which demonstrates that the KGTSVMC-DMOC can effectively reduce EC while ensuring the effluent parameters meet the discharge standards.

Actual dioxin (DXN) concentrations often deviate significantly from theoretical models. The dynamics of DXN generation, adsorption, and emission concentrations

The operating conditions of municipal solid waste incineration (MSWI) are affected by manipulated variables such as feed rate, primary air supply, and grate

Municipal solid waste incineration (MSWI) has become a predominant emission source of dioxins (DXNs). Research focusing on the impact of operating conditions,

Dioxin (DXN) emissions from the municipal solid waste incineration (MSWI) process are typically monitored under steady operating conditions. There has been

The process flow of a typical municipal solid waste incineration (MSWI) power plant utilizing a grate furnace is outlined, along with an overview of the

This book presents a comprehensive investigation into the modeling of multiple points dioxins concentration in the municipal solid waste incineration (MSWI)

The modeling samples of difficulty-to-measure key performance indicator such as dioxin (DXN) are characterized by high dimensionality, significant uncertainty,