scholarly journals Development of Model Predictive Controller for a Tail-Sitter VTOL UAV in Hover Flight

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2859 ◽  
Author(s):  
Boyang Li ◽  
Weifeng Zhou ◽  
Jingxuan Sun ◽  
Chih-Yung Wen ◽  
Chih-Keng Chen
Keyword(s):  
High Efficiency ◽  
Position Control ◽  
State Space Model ◽  
Nonlinear Dynamic Model ◽  
Model Predictive Controller ◽  
Position Controller ◽  
Predictive Controller ◽  
Hover Flight ◽  
Disturbance Model ◽  
Six Degree Of Freedom

This paper presents a model predictive controller (MPC) for position control of a vertical take-off and landing (VTOL) tail-sitter unmanned aerial vehicle (UAV) in hover flight. A ‘cross’ configuration quad-rotor tail-sitter UAV is designed with the capabilities for both hover and high efficiency level flight. The six-degree-of-freedom (DOF) nonlinear dynamic model of the UAV is built based on aerodynamic data obtained from wind tunnel experiments. The model predictive position controller is then developed with the augmented linearized state-space model. Measured and unmeasured disturbance model are introduced into the modeling and optimization process to improve disturbance rejection ability. The MPC controller is first verified and tuned in the hardware-in-loop (HIL) simulation environment and then implemented in an on-board flight computer for real-time indoor experiments. The simulation and experimental results show that the proposed MPC position controller has good trajectory tracking performance and robust position holding capability under the conditions of prevailing and gusty winds.

Effect of Short-Term Weather Predictions on Model Predictive Trajectory Tracking Performance of Unmanned Surface Vessels

2020 ◽  
Author(s):  
Benjamin Armentor ◽  
Joseph Stevens ◽  
Nathan Madsen ◽  
Andrew Durand ◽  
Joshua Vaughan
Keyword(s):  
Trajectory Tracking ◽  
Wind Waves ◽  
Tracking Error ◽  
Tracking Performance ◽  
Model Predictive Controller ◽  
Prediction Horizon ◽  
Surface Vessels ◽  
Waves And Currents ◽  
Predictive Controller ◽  
Disturbance Model

Abstract For mobile robots, such as Autonomous Surface Vessels (ASVs), limiting error from a target trajectory is necessary for effective and safe operation. This can be difficult when subjected to environmental disturbances like wind, waves, and currents. This work compares the tracking performance of an ASV using a Model Predictive Controller that includes a model of these disturbances. Two disturbance models are compared. One prediction model assumes the current disturbance measurements are constant over the entire prediction horizon. The other uses a statistical model of the disturbances over the prediction horizon. The Model Predictive Controller performance is also compared to a PI-controlled system under the same disturbance conditions. Including a disturbance model in the prediction of the dynamics decreases the trajectory tracking error over the entire disturbance spectrum, especially for longer horizon lengths.

An Automatic Insulin Infusion System Based on Kalman Filtering Model Predictive Control Technique

2020 ◽  
Vol 143 (2) ◽  
Author(s):  
Akshaya Kumar Patra ◽  
Anuja Nanda
Keyword(s):  
Kalman Filtering ◽  
Type I Diabetes ◽  
Artificial Pancreas ◽  
State Space Model ◽  
Control Technique ◽  
Type I ◽  
Model Predictive Controller ◽  
Clinical Disorders ◽  
Predictive Controller ◽  
Result Analysis

Abstract During the past few decades, optimal control of blood glucose (BG) concentration with adequate feedback loop has been of ample importance for Type-I diabetes mellitus (TIDM) patients as far as an artificial pancreas realization is concerned. Now-a-days, in addition to the BG control, the design of the micro-insulin dispenser (MID) with a robust control algorithm to regulate the other chronic clinical disorders based on prolonged medications is also quite indispensable. A novel Kalman filtering model predictive controller (KFMPC) has been proposed in this work to solve the aforementioned problem. For designing of the KFMPC, a ninth-order state-space model of the TIDM patient with MID is considered. In this control strategy, the conventional model predictive controller is re-formulated with a state estimator based on the Kalman filtering methodology to improve the control execution. The justification of enhanced control performance of KFMPC is demonstrated by comparative result analysis with other published control techniques. The simulations are carried out through matlab/simulink environment, and the results indicate comparatively better control ability of the suggested algorithm to control the BG level within the normoglycemic range (70–120 mg/dl) as far as accuracy, stability, quick damping, and robustness.

SENSORLESS POSITION CONTROL OF DC MOTOR USING MODEL PREDICTIVE CONTROLLER

2015 ◽  
Vol 77 (12) ◽  
Author(s):  
Amir A. Bature ◽  
Salinda Buyamin ◽  
Mohamad N. Ahmad ◽  
Mustapha Muhammad ◽  
Auwalu M. Abdullahi
Keyword(s):  
Position Control ◽  
Dc Motor ◽  
Black Box ◽  
Horizontal Position ◽  
Model Predictive Controller ◽  
Identification Scheme ◽  
Practical Experiment ◽  
Predictive Controller ◽  
Control Application

Sensors like rotary encoders are widely used in measuring the speed and position of DC motor in applications. Due to expensiveness, calibration complexities of these type of encoders, sensorless methods for measurements were used alternatively. This paper presents sensorless position control of a wheeled DC motor using system identified model. This approach overcome some conventional sensorless techniques that uses some approximations. The model is developed using black box identification scheme, based on the identified model, a model predictive controller was designed to track a desired horizontal position of the wheel. Practical experiment shows the concept gives a very good estimation of the position and speed and can be used in control application. 

Designing an Embedded Motion Controller Using a 16-Bit Microprocessor Motion Chip and ARM

2012 ◽  
Vol 468-471 ◽  
pp. 418-421 ◽  
Author(s):  
Shi Chun Chi ◽  
Ming Yang Zhao
Keyword(s):  
Communication Networks ◽  
High Efficiency ◽  
Position Control ◽  
Design Method ◽  
Low Cost ◽  
Flow Diagram ◽  
Motion Controller ◽  
Design And Implementation ◽  
Host Machine ◽  
Position Controller

This paper describes the design and implementation of a high efficiency motion controller system consisting of host machine and teach pendant. The host machine performs some of the position control processing tasks and receives the processed data from Teach Pendant. Starting with introduction to existing excellent 4-axismotion controller PCL6045B, It describes the overall structure of the system and the hardware that make up the motion controller. Then, this paper discusses the design method of software system, and the motion control chip PCL6045B driver in WindowsCE. Besides, the flow diagram of the use of industrial communication networks transmission about CC_LINK is showed in detail. After testing the system, it has implemented the high precision position controller. Moreover, it has the advantages of low cost, easy use.

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