Font Size: a A A

Research And Implementation Of EMA Digital Servo Drive Adaptive Control System

Posted on:2020-06-12Degree:MasterType:Thesis
Country:ChinaCandidate:B ChenFull Text:PDF
GTID:2392330590472402Subject:Mechanical and electrical engineering
Abstract/Summary:PDF Full Text Request
Electromechanical actuator(EMA)is a kind of mechatronic device with high integration,power density and transmission efficiency,which is being increasingly used in aircraft airfoil control system,weapon follow-up system and electric retractable system.High performance EMA requires good dynamic response and environmental adaptability.The application of adaptive control is studied in this thesis in response to these requirements.An EMA digital servo drive platform is also built with IPM and DSP.Firstly,the overall design of the EMA is introduced and the mathematical model is established,which includes two parts: the servo motor and the mechanical transmission mechanism.Based on the mathematical model,the advantages and disadvantages of existing current control strategy in decoupling accuracy,dynamic response and robustness to parameter changes are discussed.A model reference adaptive(MRAC)based current control strategy is proposed.The disturbance in EMA speed regulation is observed and compensated by a disturbance observer(DOB).In addition,a self-tuning speed control strategy based on recursive least square method(RLS)is proposed.Afterwards,the hardware platform and embedded software system of EMA are designed.The hardware platform includes a power board and a control board.The former is based on intelligent power module(IPM)and adopts a three-phase half-bridge structure.The latter combines the powerful operational capability of DSP and the flexibility and convenience of CPLD.The embedded software system is also designed and debugged.Finally,the feasibility and effectiveness of the proposed adaptive control algorithm are tested and verified on the EMA digital servo drive platform.
Keywords/Search Tags:EMA, Model Reference Adaptive Control, Self-tuning Control, Parameter Identification, Recursive Least Square Method
PDF Full Text Request
Related items