Research On Modeling And Fuzzy Control Of Micro Gas Turbine

Micro gas turbine is an important equipment in the field of energy and power since the new century.Technical research on micro gas turbines has broad application prospects in terms of national development.Micro gas turbines are currently the most mature and commercially competitive small distributed power generation devices.This type of power generation method can increase grid mobility,improve power quality and reduce power transmission losses.The development of distributed power generation system provides a good platform for in-depth research and market application of micro gas turbine technology.It is a promising energysaving and environmentally-friendly power supply method.In the field of cogeneration,micro gas turbines can directly compete with internal combustion engines.Micro gas turbines are lighter and smaller,have fewer rotating parts,lower maintenance costs,and reduce pollution emissions.There are some thorny problems in the operation of micro gas turbines,such as low unit safety,unstable air pressure,and more complicated control processes.The research on modeling and control of micro gas turbines is particularly important.In this paper,the WR100 micro gas turbine is the research object,its mechanism is modeled,and the improved particle swarm algorithm is introduced into its control model identification.The fuzzy controller is optimized accordingly,and the optimized fuzzy controller is applied to the control system of the micro gas turbine.The simulation effect proves the effectiveness of the controller optimization.The mechanism of micro gas turbines is studied.Based on the three conservation laws of mass,energy and momentum,the mathematical equations of each component are given,and the mathematical model of the micro gas turbine is established.The complete simulation model of the micro gas turbine is built on the Matlab/Simulink platform,and the dynamic simulation is carried out,which lays the foundation for the identification of the subsequent control model.A particle swarm fusion algorithm is proposed.In the particle swarm algorithm,the compression factor and the crowd search algorithm are introduced to form a particle swarm fusion algorithm,which overcomes the shortcomings of the traditional particle swarm algorithm that it is easy to fall into the local optimal solution in the optimization process.The three test functions prove that the particle swarm fusion algorithm can not only effectively jump out of the local optimal region to obtain the global optimal solution,and has high convergence accuracy,but also can achieve rapid convergence of the optimization problem.The particle swarm fusion algorithm is used to identify the control model parameters of the micro gas turbine,and the comparison with the actual simulation results verifies the accuracy of the identification model.A new T-S fuzzy control system design method is proposed.Traditional fuzzy controllers usually need to combine expert experience to obtain fuzzy control rules.In this paper,the PID controller parameters are used to initialize the fuzzy rules of the T-S fuzzy controller,and the particle swarm fusion algorithm is used to optimize the weights,quantization factors,and scale factors of the fuzzy rules.A new type of T-S fuzzy controller is obtained.The T-S fuzzy controller proposed in this paper is applied to the control system of the micro gas turbine.The PID controller parameters are used to initialize the T-S fuzzy controller.The simulation results show that the controller can have good response speed and stability.The particle swarm fusion algorithm is used to optimize the T-S fuzzy controller,and the optimized fuzzy controller is applied to the micro gas turbine control system.The control curve shows that the optimized fuzzy controller has a faster response speed,stronger anti-interference ability,and more stable control performance than the traditional PID controller.