Research On Suppression Algorithm Of Unknown Frequency Periodic Disturbance Signal

In the industrial production design,there is a widespread problem of unknown frequency periodic interference.Continuous periodic interference will cause the control system to become unstable or even collapse,and will bring errors to the system,thereby causing unnecessary economic losses.In order to solve this kind of problem,research on the suppression of periodic interference signals becomes necessary.In view of this problem,this thesis has designed and improved the algorithm,and conducted in-depth research and analysis on the proposed algorithm.The main contents include:First,the research background and significance of the topic of periodic interference signal identification and suppression are analyzed.Explained the research status of the periodic interference problem at home and abroad,and analyzed the development process and main characteristics of each algorithm for the mainstream algorithms at home and abroad to solve the problem of identification and suppression of periodic interference signals.Secondly,the periodic interference signal suppression algorithm using the internal model controller is introduced.The structure and content of the non-adaptive internal model controller algorithm and the adaptive internal membrane controller algorithm are analyzed,and their application limitations are explained respectively.Again,this thesis takes linear stationary control system as the research object,and proposes an improved adaptive internal model controller algorithm,which consists of a traditional stable controller and an adaptive internal model controller in parallel.The adaptive internal model controller algorithm is processed by normalization and time-scale transformation,and then integrated with the state equation of the control system to obtain a new system state equation.In this thesis,the tie value theorem analysis method and the slow integration prevalence are used to analyze the convergence of the frequency and amplitude estimation of the control algorithm,the suppression effect of the unknown frequency periodic interference,and the progressive stability of the control system.The main advantages of the control algorithm in this thesis include the asymptotic convergence elimination of low-frequency interference,the asymptotic stability of the entire error feedback system independent of the controlled object parameters,and the robust applicability in engineering.Through simulation experiments,the algorithm's good transient convergence characteristics,steady-state anti-noise performance,and the influence of parameters in the controlalgorithm on the algorithm's convergence speed and noise are verified,which provides a useful reference for practical engineering applications.Finally,the algorithm's discretization method and specific implementation steps are provided.Next,a hardware platform based on the algorithm proposed in this thesis is built.The hardware part of the experimental platform mainly includes two parts: experimental object and controller.The experimental object is based on the STM32 single-chip microcomputer,including signal generation,signal conditioning and the structure of the controlled object.The controller is based on DSP and includes signal conditioning circuit,A / D conversion circuit and D / A conversion circuit..After giving the hardware design schematic diagram of each hardware part,the corresponding software design flow chart is given.The construction of the hardware platform laid a certain foundation for the engineering application of the adaptive internal model controller algorithm.Finally,the results of the research and analysis in this thesis are summarized and analyzed,and the deficiencies in the algorithm are proposed,which points out the direction for the next research and analysis.