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To Improve Drilling Efficiency by Multi-objective Optimization of Operational Drilling Parameters in the Complex Geological Drilling Process

To Improve Drilling Efficiency by Multi-objective Optimizati...

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第37届中国控制会议

作者： Chao Gan Weihua Cao Kangzhi Liu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Electrical and Electronic Engineering Chiba University

Operational drilling parameters optimization is necessary for increase drilling efficiency in complex geological drilling process. There are four key objectives to evaluate the drilling efficiency, including drilling cost, rate of penetration（ROP）, drill bit life, and drill bit’s specific energy. In this paper, we proposed a multi-objective optimization method to improve drilling efficiency in the complex geological drilling process considering all the four key objectives. Firstly, the characteristics of complex geological drilling process and optimization problems are analyzed to find the vital process parameters and problems for drilling efficiency optimization. Then, a multi-objective optimization model which combines the four key objectives is ***, an improved nondominated sorting genetic algorithm（improved nsga-ii） is used to optimize the operational drilling parameters include weight on bit（WOB） and rotational speed（RS） to make drilling efficiency improved. The real case results demonstrate that our method increases the drilling efficiency in four key objectives and saves the simulation time. The proposed method provides the foundation for intelligent optimization control in complex geological drilling process.

关键词： Operational Drilling Parameters Multi-objective Optimization Complex Geological Drilling Process Drilling Efficiency improved nsga-ii

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Greenhouse Microclimate Control Optimization Based on improved nsga-Ⅱ Algorithm

Greenhouse Microclimate Control Optimization Based on Improv...

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第32届中国控制与决策会议

作者： Lina Wang College of Mechanical and Electronic Engineering China Jiliang University

Optimization of systems can increase the efficiency of a control *** greenhouse microclimate includes temperature,light,water,gas,fertilizer and other environmental parameters within a controlled ***,the temperature or humidity is controlled through a single factor,but several control objectives may be *** solve this problem,an improved non-dominated sorting genetic algorithm-ii（nsga-ii） is *** adaptive mutation method is used to replace the traditional polynomial mutation method,which can increase the rate of obtaining the Pareto optimal solution while maintaining the diversity of the solution *** arithmetic crossover method is used to replace the original crossover method,which can enlarge its search domain,make the algorithm have better global searching ability and keep the diversity of the knowledge set *** simulation results show that when the improved multi-objective optimization algorithm is applied to the greenhouse environment model,the Pareto optimal frontier solution set has a more reasonable distribution and has good efficiency and performance in greenhouse environment control.

关键词： Greenhouse microclimate control improved nsga-ii Pareto optimization Cost minimization

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