Model Free Control vs Sliding Mode Control: Application to a coupled Three-Tank System

Author(s):  
Zahraa Serhan ◽  
Hassan Noura
Author(s):  
Radu-Emil Precup ◽  
Raul-Cristian Roman ◽  
Elena-Lorena Hedrea ◽  
Emil M. Petriu ◽  
Claudia-Adina Bojan-Dragos

The paper presents the combination of the model-free control technique with two popular nonlinear control techniques, sliding mode control and fuzzy control. Two data-driven model-free sliding mode control structures and one data-driven model-free fuzzy control structure are given. The data-driven model-free sliding mode control structures are built upon a model-free intelligent Proportional-Integral (iPI) control system structure, where an augmented control signal is inserted in the iPI control law to deal with the error dynamics in terms of sliding mode control. The data-driven model-free fuzzy control structure is developed by fuzzifying the PI component of the continuous-time iPI control law. The design approaches of the data-driven model-free control algorithms are offered. The data-driven model-free control algorithms are validated as controllers by real-time experiments conducted on 3D crane system laboratory equipment.


Electronics ◽  
2021 ◽  
Vol 10 (19) ◽  
pp. 2424
Author(s):  
Yong Yang ◽  
Yunbing Yan ◽  
Xiaowei Xu

It is difficult to model and determine the parameters of the steer-by-wire (SBW) system accurately, and the perturbation is variable with complex and changeable tire–road conditions. In order to improve the control performance of the vehicle SBW system, an adaptive fast super-twisting sliding mode control (AFST-SMC) scheme with time-delay estimation (TDE) is proposed. The proposed scheme uses TDE to acquire the lumped dynamics in a simple way and establishes a practical model-free structure. Then, a fractional order (FO) sliding mode surface and a fast super-twisting sliding mode control structure were designed on the basic super-twisting sliding mode to ensure fast convergence and high control accuracy. Since the uncertain boundary information of the actual system is unknown, a novel adaptive algorithm is proposed to regulate the control gain based on the control errors. Theoretical analysis concerning system stability is given based on the Lyapunov theory. Finally, the effectiveness of the method is verified through comparative experiments. The results show that the proposed TDE-AFST-FOSMC control scheme has the advantages of model-free, fast response and high accuracy.


Author(s):  
Kumar Pakki. Bharani Chandra ◽  
Hemnath Srikanthan ◽  
Da-Wei Gu ◽  
Bijnan Bandyopadhyay ◽  
Ian Postlethwaite

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