On Trajectory Tracking Model Predictive Control of an Unmanned Quadrotor Helicopter Subject to Aerodynamic Disturbances

2012 ◽  
Vol 16 (1) ◽  
pp. 209-224 ◽  
Author(s):  
K. Alexis ◽  
G. Nikolakopoulos ◽  
A. Tzes
2014 ◽  
Vol 02 (01) ◽  
pp. 39-52 ◽  
Author(s):  
Iman Sadeghzadeh ◽  
Mahyar Abdolhosseini ◽  
Youmin Zhang

Two useful control techniques are investigated and applied experimentally to an unmanned quadrotor helicopter for a practical and important scenario of using an Unmanned Aerial Vehicle (UAV) for dropping a payload in circumstances where search and rescue and delivery of supplies and goods is dangerous and difficult to reach environments such as forest or high building fires fighting, rescue in earthquake, flood and nuclear disaster situations. The two considered control techniques for such applications are the Gain-Scheduled Proportional-Integral-Derivative (GS-PID) control and the Model Predictive Control (MPC). Both the model-free (GS-PID) and model-based (MPC) algorithms show a very promising performance with application to taking-off, height holding, payload dropping, and landing periods in a payload dropping mission. Finally, both algorithms are successfully implemented on an unmanned quadrotor helicopter testbed (known as Qball-X4) available at the Networked Autonomous Vehicles Lab (NAVL) of Concordia University for payload dropping tests to illustrate the effectiveness and performance comparison of the two control techniques.


Robotica ◽  
2018 ◽  
Vol 36 (5) ◽  
pp. 676-696 ◽  
Author(s):  
Tiago P. Nascimento ◽  
Carlos E. T. Dórea ◽  
Luiz Marcos G. Gonçalves

SUMMARYModel predictive control (MPC) theory has gained attention with the recent increase in the processing power of computers that are now able to perform the needed calculations for this technique. This kind of control algorithms can achieve better results in trajectory tracking control of mobile robots than classical control approaches. In this paper, we present a review of recent developments in trajectory tracking control of mobile robot systems using model predictive control theory, especially when nonholonomicity is present. Furthermore, we point out the growth of the related research starting with the boom of mobile robotics in the 90s and discuss reported field applications of the described control problem. The objective of this paper is to provide a unified and accessible presentation, placing the classical model, problem formulations and approaches into a proper context and to become a starting point for researchers who are initiating their endeavors in linear/nonlinear MPC applied to nonholonomic mobile robots. Finally, this work aims to present a comprehensive review of the recent breakthroughs in the field, providing links to the most interesting and successful works, including our contributions to state-of-the-art.


Author(s):  
Mingcong Cao ◽  
Chuan Hu ◽  
Rongrong Wang ◽  
Jinxiang Wang ◽  
Nan Chen

This paper investigates the trajectory tracking control of independently actuated autonomous vehicles after the first impact, aiming to mitigate the secondary collision probability. An integrated predictive control strategy is proposed to mitigate the deteriorated state propagation and facilitate safety objective achievement in critical conditions after a collision. Three highlights can be concluded in this work: (1) A compensatory model predictive control (MPC) strategy is proposed to incorporate a feedforward-feedback compensation control (FCC) method. Based on the definite physical analysis, it is verified that adequate reverse steering and differential torque vectoring render more potentials and flexibility for vehicle post-impact control; (2) With compensatory portions, the deteriorated states after a collision are far beyond the traditional stability envelope. Hence it can be further manipulated in MPC by constraint transformation, rather than introducing soft constraints and decreasing the control efforts on tracking error; (3) Considering time-varying saturation on input, input rate, and slip ratio, the proposed FCC-MPC controller is developed to improve faster deviation attenuation both in lateral and yaw motions. Finally two high-fidelity simulation cases implemented on CarSim-Simulink conjoint platform have demonstrated that the proposed controller has the advanced capabilities of vehicle safety improvement and better control performance achievement after severe impacts.


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