Robust model-free control of a class of uncertain nonlinear systems using BELBIC: stability analysis and experimental validation

2019 ◽  
Vol 41 (8) ◽  
Author(s):  
Saeed Khorashadizadeh ◽  
Seyed Mohammad Hashem Zadeh ◽  
Mohammad Reza Koohestani ◽  
Sajjad Shekofteh ◽  
Selçuk Erkaya
Keyword(s):  
Stability Analysis ◽  
Nonlinear Systems ◽  
Experimental Validation ◽  
Uncertain Nonlinear Systems ◽  
Model Free ◽  
Robust Model ◽  
Model Free Control

Intelligent PD controller design for active suspension system based on robust model-free control strategy

2019 ◽  
Vol 233 (14) ◽  
pp. 4863-4880 ◽  
Author(s):  
Maroua Haddar ◽  
Riadh Chaari ◽  
S Caglar Baslamisli ◽  
Fakher Chaari ◽  
Mohamed Haddar
Keyword(s):  
Controller Design ◽  
Design Method ◽  
Active Suspension ◽  
Vehicle Speed ◽  
Pd Controller ◽  
Suspension Systems ◽  
Model Free ◽  
Robust Model ◽  
Road Disturbance ◽  
Model Free Control

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.

Experimental validation of robot-assisted cardiovascular catheterization: model-based versus model-free control

2018 ◽  
Vol 13 (6) ◽  
pp. 797-804
Author(s):  
Xiaomei Wang ◽  
Kit-Hang Lee ◽  
Denny K. C. Fu ◽  
Ziyang Dong ◽  
Kui Wang ◽  
...  
Keyword(s):  
Experimental Validation ◽  
Robot Assisted ◽  
Model Based ◽  
Model Free ◽  
Versus Model ◽  
Model Free Control

scholarly journals Sliding mode learning control of uncertain nonlinear systems with Lyapunov stability analysis

2018 ◽  
Vol 41 (6) ◽  
pp. 1750-1760
Author(s):  
Erkan Kayacan
Keyword(s):  
Stability Analysis ◽  
Nonlinear Systems ◽  
Lyapunov Stability ◽  
Sliding Mode ◽  
Learning Control ◽  
System Stability ◽  
Uncertain Nonlinear Systems ◽  
System Behaviour ◽  
Lyapunov Stability Analysis ◽  
The Stability

This paper addresses the Sliding Mode Learning Control (SMLC) of uncertain nonlinear systems with Lyapunov stability analysis. In the control scheme, a conventional control term is used to provide the system stability in compact space while a type-2 neuro-fuzzy controller (T2NFC) learns system behaviour so that the T2NFC completely takes over overall control of the system in a very short time period. The stability of the sliding mode learning algorithm has been proven in the literature; however, it is restrictive for systems without overall system stability. To address this shortcoming, a novel control structure with a novel sliding surface is proposed in this paper, and the stability of the overall system is proven for nth-order uncertain nonlinear systems. To investigate the capability and effectiveness of the proposed learning and control algorithms, the simulation studies have been carried out under noisy conditions. The simulation results confirm that the developed SMLC algorithm can learn the system behaviour in the absence of any mathematical model knowledge and exhibit robust control performance against external disturbances.

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