Study And Application Of Model Predictive Composite Nonlinear Servo Control Technology

Servo control technology has been widely used in industrial manufacturing and daily life,such as CNC machine tools,industrial automation,robots and other fields.With the development of microprocessor and power electronics technology,the advent of high-performance single-chip and DSP chips has promoted the rapid development of digital control servo system.At the same time,the emergence and development of vector control and direct torque control have greatly simplified the control of AC motor system and laid a solid foundation for the development of AC servo motor control technology.Servo control system is developing toward high performance and high precision,so the study of advanced servo control technology is of great significance.Firstly,for a second-order servo system,the thesis proposes a robust composite nonlinear control(RCNC)approach with disturbance compensation,which can achieve accurate tracking control.The scheme consists of a linear control part for achieving fast response,a nonlinear feedback part for suppressing the overshoot,and a disturbance compensation mechanism for erasing the steady-state error.An extended state observer is adopted to estimate the un-measurable state variables and unknown disturbance.The algorithm is applied to brushless DC motor speed control system.Simulations are carried out in MATLAB/Simulink,followed by real-time experiment using a TMS320F28335DSP.The results confirm that the proposed control scheme can achieve fast,smooth and accurate tracking of target speed,and has good performance robustness against the load disturbance and parameter variations.Secondly,based on the mathematical model of permanent magnet synchronous linear motor(PMSLM)in the dq coordinate system,the space state formulation of position servo system is established.The design of composite nonlinear control is introduced into the discrete-time domain and applied to linear servo position servo system.Then the system model is built on MATLAB/Simulink,using RCNC for position control.The control performance of RCNC at different target positions,different disturbance factors and parameter perturbation is studied.The simulation results show the RCNC scheme has desirable transient performance and steady-state accuracy,with an effective suppression of disturbance,and robustness against parameter perturbation.On the basis,the thesis proceeds to study the strategy for combing model predictive control(MPC)and composite nonlinear control,and put forward a dual-mode control scheme which uses the model predictive control for initial tracking and switches over to composite nonlinear control for smooth settling once the system state enters the specified target neighborhood.The scheme is applied to linear motor position servo control,and simulations conducted in MATLAB/Simulink show that the control scheme can achieve a good tracking control performance for a wide range of target positions.Finally,A PMSLM servo control experimental platform is constructed with a TMS320F28335DSP as the core processor,together with motor drive circuit and external hardware circuits.Servo control system software and hardware are designed.The discrete-time RCNC scheme is used to achieve position control of linear motor.Control algorithms are programmed using the Code Composer Studio(CCS)software system,and experimental results under different position targets verify the effectiveness of RCNC controllers.The results show that discrete-time RCNC scheme can track a target position accurately and quickly,and a good control performance is achieved.