Study On Optimal Control Of Unmanned Helicopter For Coal Mines Based On Membrane Computing

With the important measures of energy structure adjustment and coal supply side structural reform,safe and accurate coal mining is the inevitable trend of the future development of the coal industry,safety and intelligence are its important support.In this paper,the unmanned helicopter is introduced to inspect the underground coal mine.In view of the motion characteristics of the helicopter,how to ensure the unmanned helicopter to complete the inspection task in the underground complex environment is an important research topic.Membrane computing has powerful distributed computing and parallel processing capabilities.This paper makes full use of the computational efficiency and versatility of membrane computing to realize the optimal control of unmanned helicopter in the process of coal mine inspection,and further expands the application of membrane computing in the field of optimal control.The research is carried out from the following aspects:1)Attitude control of unmanned helicopter based on cell type membrane computing.Combined with the complex environment of underground coal mine,the air mathematical model of coal mine roadway was established,the kinematics and dynamic attitude models of unmanned helicopter were constructed.The cell membrane system suitable for the attitude control model of the unmanned helicopter under the environment mapping parameters was constructed.A cellular attitude membrane controller with membrane system characteristics and operational rules for unmanned helicopter was designed.The feasibility and tracking effectiveness of the controller are verified by experiments.2)The attitude optimization of unmanned helicopter is realized by using the spiking neural membrane.Based on the invariance of rotation and translation of the system,the extended spiking neural membrane system is constructed;the system and algorithm are designed and optimized to complete the optimization of the extended spiking neural membrane system.It is proved theoretically that the optimal spiking neural membrane system is efective for helicopter attitude performance optimization,and it is verified by experiments.3)SLAM of unmanned helicopter is realized based on probabilistic membrane computing.The IMU,lidar and depth camera sensors are fused,and the probabilistic SLAM is realized based on sparse filtering algorithm.The calculation model of the probabilistic membrane system is further constructed,and the algorithm in the membrane is designed to realize the map construction process.The feasibility of the unmanned helicopter multi-sensor fusion under the probabilistic membrane system to improve the SLAM accuracy is verified by experiments.4)Based on the integration of the spiking functional cell membrane system,the path planning of the unmanned helicopter is realized.Spatiotemporal coding is introduced to represent spatial information in time and realize the encoding of spatial information by temporal information.The spiking neural membrane system algorithm is used to realize global path planning.The cell membrane system with spiking function and local path planning algorithm were designed to realize real-time obstacle avoidance of the unmanned helicopter on the basis of global path planning.Finally,the superiority of the global and the feasibility of the local route planning algorithm are verified by the simulation experiments.Figures[82]tables[9]references[115].