Research On Fuzzy Dynamic High-type Control Method Of Photoelectric Servo Tracking Systems

The photoelectric tracking system is a precision observation instrument that is widely used in land or moving platforms for real-time tracking of relative moving targets.Its tracking accuracy is an important indicator of system performance.Due to the complex application environment and the non-linear friction of the tracking equipment,the tracking system has greater uncertainty.At the same time,as the tracking object of the tracking system becomes more mobile and smaller in size,it is more difficult to achieve target tracking.The traditional control method cannot meet the fast and high-precision tracking requirements at the same time.Dynamic high-type control technology can dynamically change the type of system according to the system state,while avoiding integral saturation,improving the steady-state accuracy and response speed,and significantly suppressing system oscillation.There are two difficult problems in the implementation of dynamic high-type control technology,namely,the problem of timing judgment for type switching and the problem of jitter caused by instantaneous switching.Fuzzy control technology,as a kind of intelligent control technology,can transform natural language through mathematical formulas,and output accurate values ??under the guidance of human expert experience.It is especially suitable for nonlinear systems and systems with large uncertainties.In the real unstructured dynamic environment and many specific applications,the traditional first-order fuzzy controller will face many uncertainties.The emergence of the second-order fuzzy controller improves the system’s ability to deal with uncertainties.Based on the above two technologies and combining their respective advantages,this paper puts forward a fuzzy-dynamic high-type control technology,which combines the fuzzy controller with the integrator in series and parallel to the forward path of the classical double-closed-loop feedback system,takes the system error and its rate of change as the input of the fuzzy controller,and takes the output of the fuzzy controller as the gain of the integrator.A multi-population genetic algorithm is introduced to iteratively optimize the two inputs and one output of the fuzzy controller with three scaling factors.The optimal control parameters are obtained without the classical genetic algorithm falling into local extremes easily.Two difficult problems of dynamic high-type control technology are overcome,and a stable Fuzzy-Dynamic high-type control system is constructed.The membership function parameters of traditional fuzzy controllers depend too much on human experience,and it is difficult to achieve ideal control results when facing more uncertain controlled objects.In order to solve this problem,the structure of the second-order fuzzy controller is studied,and the three-dimensional membership function is adjusted to include the uncertainty of the input variables,which optimizes the ability of the control system to deal with the uncertainty.Due to the introduction of three-dimensional variables,the computational complexity of the second-order fuzzy controller is doubled.A new reduction algorithm is also proposed in this paper.Weighting is performed on the basis of the traditional Nie-Tan reduction algorithm,avoiding iterative calculation,and improving the speed and accuracy of defuzzification calculation,and the practicality of the weighted NT algorithm is proved through experiments.This article first analyzes the structure of the classic photoelectric tracking system,then conducts theoretical and simulation analysis on the fuzzy-dynamic high-type control system,and finally builds an experimental platform for verification.The experimental results show that the proposed method achieves the goal of dynamic high-type switching system type.The adjustment time is only 0.069 seconds,and the steady-state error is only 0.0005 arc seconds.Compared with the traditional double closed-loop feedback control system,it significantly improves the response speed and steady-state accuracy of the system.The mean square error is 1.2038 arc seconds,and the error time integration criterion value is 979.6,which obviously improves the dynamic stability and robustness of the system.