Path tracking design based on Davidson–Cole prefilter using a centralized CRONE controller applied to multivariable systems

2012 ◽  
Vol 71 (4) ◽  
pp. 701-712 ◽  
Author(s):  
Najah Yousfi ◽  
Pierre Melchior ◽  
Chokri Rekik ◽  
Nabil Derbel ◽  
Alain Oustaloup
2013 ◽  
Vol 76 (1) ◽  
pp. 447-457 ◽  
Author(s):  
Najah Yousfi ◽  
Pierre Melchior ◽  
Patrick Lanusse ◽  
Nabil Derbel ◽  
Alain Oustaloup

Author(s):  
P. Melchior ◽  
C. Inarn ◽  
A. Oustaloup

The aim of this paper concerns motion control and robust path tracking. An approach based on fractional prefilter synthesis was already developed. It allows tracking optimization according to the fractional derivation order, the actuators physical constraints and the control loop frequency bandwidth. The purpose of this paper is the extension of this approach to multivariable systems. A non integer prefilter synthesis methodology for square MIMO systems (Multi-Input, Multi-Output) is presented. It is based on the MIMO-QFT robust synthesis methodology, taking into account of the plant uncertainties. MIMO-QFT robust synthesis methodology is based on multiple SISO (MISO systems) synthesis by considering the loop couplings. The SISO-QFT synthesis methodology can be then used for each SISO synthesis. Then the prefilters are synthesized. The prefilter parameter optimization is founded on the prefilter output error integral minimization, taking into account of the actuators physical constraints and the tracking performance specifications. An application example is given.


Author(s):  
X. Wu ◽  
Y. Yang

This paper presents a new design of omnidirectional automatic guided vehicle based on a hub motor, and proposes a joint controller for path tracking. The proposed controller includes two parts: a fuzzy controller and a multi-step predictive optimal controller. Firstly, based on various steering conditions, the kinematics model of the whole vehicle and the pose (position, angle) model in the global coordinate system are introduced. Secondly, based on the modeling, the joint controller is designed. Lateral deviation and course deviation are used as the input variables of the control system, and the threshold value is switched according to the value of the input variable to realise the correction of the large range of posture deviation. Finally, the joint controller is implemented by using the industrial PC and the self-developed control system based on the Freescale minimum system. Path tracking experiments were made under the straight and circular paths to test the ability of the joint controller for reducing the pose deviation. The experimental results show that the designed guided vehicle has excellent ability to path tracking, which meets the design goals.


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