A model free control design approach for a semi-active suspension of a passenger car

Author(s):  
C. Lauwerys ◽  
J. Swevers ◽  
P. Sas
2007 ◽  
Vol 21 (3) ◽  
pp. 1422-1436 ◽  
Author(s):  
J. Swevers ◽  
C. Lauwerys ◽  
B. Vandersmissen ◽  
M. Maes ◽  
K. Reybrouck ◽  
...  

Author(s):  
Maroua Haddar ◽  
Riadh Chaari ◽  
S Caglar Baslamisli ◽  
Fakher Chaari ◽  
Mohamed Haddar

A novel active suspension control design method is proposed for attenuating vibrations caused by road disturbance inputs in vehicle suspension systems. For the control algorithm, we propose an intelligent PD controller structure that effectively rejects online estimated disturbances. The main theoretical techniques used in this paper consist of an ultra-local model which replaces the mathematical model of quarter car system and a new algebraic estimator of unknown information. The measurement of only input and output variables of the plant is required for achieving the reference tracking task and the cancellation of unmodeled exogenous and endogenous perturbations such as roughness road variation, unpredictable variation of vehicle speed and load variation. The performance and robustness of the proposed active suspension algorithm are compared with ADRC control and LQR control. Numerical results are provided for showing the improvement of passenger comfort criteria with model-free control.


2020 ◽  
Vol 53 (2) ◽  
pp. 1575-1580
Author(s):  
Thomas Gellrich ◽  
Yi Min ◽  
Stefan Schwab ◽  
Soeren Hohmann

Author(s):  
Sunil Kumar Rajendran ◽  
Feitian Zhang

Bioinspired robotics takes advantage of biological systems in nature for morphology, action and perception to build advanced robots of compelling performance and wide application. This paper focuses on the design, modeling and control of a bioinspired robotic fish. The design utilizes a recently-developed artificial muscle named super coiled polymer for actuation and a soft material (silicone rubber) for building the robot body. The paper proposes a learning based speed control design approach for bioinspired robotic fish using model-free reinforcement learning. Based on a mathematically tractable dynamic model derived by approximating the robotic fish with a three-link robot, speed control simulation is conducted to demonstrate and validate the control design method. Exampled with a three-link reduced-order dynamic system, the proposed learning based control design approach is applicable to many and various complicated bioinspired robotic systems.


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