Dry Friction Compensation for Radio Telescope Servo Drive Based on the Model Predictive Control

2019 ◽  
Author(s):  
Tran Huu Phuong ◽  
Mikhail P. Belov ◽  
Nguyen Van Lanh
Keyword(s):  
Model Predictive Control ◽  
Radio Telescope ◽  
Predictive Control ◽  
Dry Friction ◽  
Friction Compensation ◽  
Servo Drive

scholarly journals Research of Mechanical Resonance Analysis and Suppression Control Method of the Servo Drive System

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Wenli Li ◽  
Yongkang Liu ◽  
Shuaishuai Ge ◽  
Daming Liao
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Notch Filter ◽  
Drive System ◽  
Time Varying ◽  
Servo Drive ◽  
Mechanical Resonance ◽  
Meshing Stiffness ◽  
Transmission Mechanisms ◽  
Servo Drive System

Transmission mechanisms of the servo drive system are not a pure rigid body, and the existence of the elastic transmission mechanisms will make the system generate mechanical resonance. Aiming at mechanical resonance of the servo drive system, the resonance generation mechanism is analyzed, the four-mass model considering the time-varying meshing stiffness of the gear is established, and the influence of different stiffness parameters on the mechanical resonance of the system is researched in this paper. The composite controller of Model Predictive Control (MPC) with Notch Filter is used to simulate the mechanical resonance suppression of the four-mass servo system considering time-varying meshing stiffness, and it is compared with the mechanical resonance suppression method based on Model Predictive Control. The simulation results show that when the step speed is 200 r/min, the overshoot is reduced from 11.6 r/min to 1.1 r/min, which is reduced by 90.5%. Under the impact load condition, from 10 Nm to 30 Nm, overshoot is reduced from 34.3 r/min to 12.8 r/min, reduced by 62%, and torque oscillation is reduced by 81.5%. Therefore, the composite controller of Model Predictive Control with Notch Filter can suppress the mechanical resonance problem effectively, caused by elastic transmission, and improve the robustness of servo drive system.

Design and Implementation of Model-Predictive Control With Friction Compensation on an Omnidirectional Mobile Robot

2014 ◽  
Vol 19 (2) ◽  
pp. 467-476 ◽  
Author(s):  
Julio Cesar Lins Barreto S. ◽  
Andre Gustavo Scolari Conceicao ◽  
Carlos E. T. Dorea ◽  
Luciana Martinez ◽  
Edson Roberto de Pieri
Keyword(s):  
Model Predictive Control ◽  
Mobile Robot ◽  
Predictive Control ◽  
Friction Compensation ◽  
Design And Implementation ◽  
Omnidirectional Mobile Robot

scholarly journals Embedded Position Control of Permanent Magnet Synchronous Motor Using Model Predictive Control

2018 ◽  
Vol 198 ◽  
pp. 04007 ◽  
Author(s):  
Agus Ramelan ◽  
Arief Syaichu Rohman ◽  
Allen Kelana
Keyword(s):  
Model Predictive Control ◽  
Embedded System ◽  
Permanent Magnet ◽  
Predictive Control ◽  
Position Control ◽  
Permanent Magnet Synchronous Motor ◽  
Synchronous Motor ◽  
Raspberry Pi ◽  
Servo Drive ◽  
Stability Point

This paper presents an implementation embedded system for position control of Permanent Magnet Synchronous Motor (PMSM). The control system consists of raspberry pi 3 as a microcontroller, ASDA-A2 servo drive, and Delta Servo ECMA type. The software design includes simulation tool and Python included on Raspbian OS. Communication between Raspberry Pi 3 and ASDA-A2 drivers using the ASCII Modbus communication protocol. Raspberry Pi 3 processes the reference data and the actual reading result and calculates the resulting error. The control algorithm used in this research is Model Predictive Control (MPC). As a Linear Quadratic Regulator, MPC aims to design and generate an optimal control signal with the ability to anticipate saturation, receding horizon, future event and take control accordingly In the design of the MPC technique to adjust the speed of the PMSM to take action of reference tracking, performance index optimization is done by adjusting the value of weighting horizon N, Q and R. The simulation and implementation results showed that the PMSM can reach the stability point on each desired setpoint and result in a near-zero steady-state error.

scholarly journals Explicit model predictive control of permanent magnet synchronous motors based on multi-point linearization

2021 ◽  
pp. 014233122110151
Author(s):  
Qian Guo ◽  
Tianhong Pan ◽  
Jinfeng Liu ◽  
Shan Chen
Keyword(s):  
Model Predictive Control ◽  
Permanent Magnet ◽  
Predictive Control ◽  
Block Diagram ◽  
Explicit Model ◽  
Servo Drive ◽  
Permanent Magnet Synchronous Motors ◽  
Synchronous Motors ◽  
Online Computation ◽  
Explicit Model Predictive Control

Permanent magnet synchronous motors (PMSMs) have been broadly applied in servo-drive applications. It is necessary to improve the performance of PMSM. An explicit controller designed for PMSM based on multi-point linearization is proposed to reduce the linearized model error caused by different running status of PMSM. The mathematical model of PMSM system in the synchronous rotating frame and the problem formulation are introduced at first. Then, the preliminaries about explicit model predictive control (MPC) algorithm are presented in this article. Based on this, the multi-point linearization model is created for explicit MPC controller design. Moreover, the block diagram of the proposed method for PMSM system is presented. Finally, the simulation results are provided to demonstrate that the proposed explicit MPC controller based on multi-point linearization achieves better performance than that based on traditional single-point linearization, but requires the same online computation time because of the offline optimization of explicit MPC.

Adaptive model predictive control for an omnidirectional mobile robot with friction compensation and incremental input constraints

2021 ◽  
pp. 014233122110213
Author(s):  
Chao Ren ◽  
Chunli Li ◽  
Liang Hu ◽  
Xiaohan Li ◽  
Shugen Ma
Keyword(s):  
Model Predictive Control ◽  
Mobile Robot ◽  
Predictive Control ◽  
Coulomb Friction ◽  
Friction Compensation ◽  
Adaptive Model ◽  
Input Constraints ◽  
Friction Forces ◽  
Omnidirectional Mobile Robot ◽  
Adaptive Model Predictive Control

In this paper, an adaptive model predictive control (MPC) scheme with friction compensation, subject to incremental control input constraints and parameter uncertainties, is proposed for a three-wheeled omnidirectional mobile robot (OMR). The proposed control framework is in a cascaded structure, wherein the outer-loop is kinematic-based control and the inner-loop is designed based on adaptive linear MPC. First, a complex nonlinear dynamic model of the OMR in the world coordinate frame is transformed and partially linearized into a reduced nonlinear model in the moving coordinate system. The nonlinearity of the reduced model only arises from Coulomb friction. Then an estimated system is established for the reduced nonlinear system, with an adaptive update law estimating the system uncertain parameters. To facilitate the linear MPC design, part of the control efforts is derived by feedback compensation of the Coulomb friction forces, resulting in a linear estimated system. The other part is designed by a constrained linear MPC. Feasibility and stability analyses are given for the proposed adaptive MPC scheme. Finally, experimental comparisons with model-based MPC are carried out to verify the effectiveness of the proposed control scheme.

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