The Design And Realization Of The Model Predictive Controller Based On Disturbance Observer

Model predictive control(MPC)has been adopted in the slow dynamic industrial field owing to characters of predictive model,online optimization and feedback correction.However,MPC can't be applied in the fast dynamic nonlinear system because of the long solution time of nonlinear MPC and the limited control effect of linear MPC because of the intrinsic nonlinearity of actual system.Especially when the predictive horizon is too long,the long solution time would limit the application of MPC in the dynamic system(like automotive electronic control system).This paper designed a MPC controller based on disturbance observer to solve the problem of long solution time.Firstly,linearize the nonlinear model and get the linear model with disturbance d caused by linearizing.Then design the disturbance observer and linear MPC controller according to the liner model,and choose the extend state observer(ESO)as the disturbance observer.The controller assigned the value of disturbance d from the estimated result of ESO.This paper used the linear MPC to replace the nonlinear MPC.At last,the control scheme designed in this paper was accelerated by the FPGA platform.In this paper the single input single output(SISO)system and multiple input multiple output(MIMO)system were used to verify the linear MPC controller based on the disturbance observer.Choose a DC motor as the example of SISO system and 7 degree of freedom vehicle model as the example of MIMO system.A nonlinear MPC controller was designed to compare the control effect with the controller designed in this paper,the result of the off-line experiment showed the effectiveness.At last,the FPGA was used to accelerate the solution speed of the controller by transforming the C/C++ to the HDL.The soft Vivado gave the reports of time latency and used resource,in which the solution time was about 1.6 ms.This paper mainly includes the following aspects:1.The linear MPC controller based on disturbance observer was applied for a SISO nonlinear system-the DC motor system.An ESO was designed according to the linear model linearized by the nonlinear system to assign the disturbance d in the linear predictive model,then a MPC controller was designed to solve the speed tracking problem of the DC motor system.And in order to verify the control effect,a nonlinear MPC controller was designed.The result shown that the control effect of linear controller was satisfactory as well as the nonlinear controller.2.The linear MPC controller based on disturbance observer was applied for a MIMO nonlinear system-the DC motor system-7 degree of freedom vehicle model.Firstly,a multivariable ESO was designed for the MIMO system and verified by an numerical example.2 degree of freedom nonlinear vehicle model was built for the controller and observer by linearizing the lateral force of tire.And in order to verify the control effect,a nonlinear MPC controller was designed.By analysing the statics of MATLAB experiments,we can get a conclusion that the more complicated of the system,the more time that controller can save meantime keeping the same control effect as the nonlinear controller.3.Finally,a hardware accelerate experiment was applied on the FPGA platform to verify the effectiveness of the controller in the field of actual industry.The parallel block was introduced in detail,in order to take full use of parallel operation of FPGA.The C/C++ was transformed to HDL by the soft-Vivado HLS,and then the time latency was given by the hardware simulation experiments.The FPGA controller had a identical output as well as m controller,which shown the good performance of the controller designed in this paper.