CAJ | 학술논문

针对集气管压力系统具有强干扰、强耦合、非线性、多参数等特性，依据逆系统解耦原理，分析了集气管压力系统数学模型的可逆性；采用对非线性具有较强逼近能力的BP 神经网络，逼近集气管压力系统的逆系统；神经网络逆系统与原系统构成伪线性解耦复合系统，实现集气管压力系统的神经网络逆解耦复合控制。仿真结果表明该方法实现了系统解耦，具有一定的应用性。
침대집기관압력계통구유강간우、강우합、비선성、다삼수등특성，의거역계통해우원리，분석료집기관압력계통수학모형적가역성；채용대비선성구유교강핍근능력적BP 신경망락，핍근집기관압력계통적역계통；신경망락역계통여원계통구성위선성해우복합계통，실현집기관압력계통적신경망락역해우복합공제。방진결과표명해방법실현료계통해우，구유일정적응용성。
For collectors'pressure system strong interference,coupled,nonlinear,multi-parameter and oth-er characteristics,based on the inverse system decoupling principle,the reversibility of the mathematical model of the gas collectors'pressure system is analyzed.BP neural network which has strong nonlinear ap-proximation ability is applied,to approximate inverse system of gas collectors'pressure system.Neural net-work inverse system with the original system composes of the pseudo linear decoupling composite system. The neural network inverse decoupling control of gas collectors'pressure system is implemented.The simu-lation results show that this method realizes decoupling,has a certain application.