scholarly journals Model-Free High Order Sliding Mode Control with Finite-Time Tracking for Unmanned Underwater Vehicles

2021 ◽  
Vol 11 (4) ◽  
pp. 1836
Author(s):  
Josué González-García ◽  
Néstor Alejandro Narcizo-Nuci ◽  
Luis Govinda García-Valdovinos ◽  
Tomás Salgado-Jiménez ◽  
Alfonso Gómez-Espinosa ◽  
...  
Keyword(s):  
Neural Network ◽  
Power Consumption ◽  
Finite Time ◽  
Sliding Mode ◽  
Underwater Vehicles ◽  
High Order ◽  
Time Base ◽  
Unmanned Underwater Vehicles ◽  
Finite Time Convergence ◽  
Model Free

Several strategies to deal with the trajectory tracking problem of Unmanned Underwater Vehicles are encountered, from traditional controllers such as Proportional Integral Derivative (PID) or Lyapunov-based, to backstepping, sliding mode, and neural network approaches. However, most of them are model-based controllers where it is imperative to have an accurate knowledge of the vehicle hydrodynamic parameters. Despite some sliding mode and neural network-based controllers are reported as model-free, just a few of them consider a solution with finite-time convergence, which brings strong robustness and fast convergence compared with asymptotic or exponential solutions and it can also help to reduce the power consumption of the vehicle thrusters. This work aims to implement a model-free high-order sliding-mode controller and synthesize it with a time-base generator to achieve finite-time convergence. The time-base was included by parametrizing the control gain at the sliding surface. Numerical simulations validated the finite-time convergence of the controller for different time-bases even in the presence of high ocean currents. The performance of the obtained solution was also evaluated by the Root Mean Square (RMS) value of the control coefficients computed for the thrusters, as a parameter to measure the power consumption of the vehicle when following a trajectory. Computational results showed a reduction of up to 50% in the power consumption from the thrusters when compared with other solutions.

scholarly journals Experimental Validation of a Model-Free High-Order Sliding Mode Controller with Finite-Time Convergence for Trajectory Tracking of Autonomous Underwater Vehicles

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 488
Author(s):  
Josué González-García ◽  
Alfonso Gómez-Espinosa ◽  
Luis Govinda García-Valdovinos ◽  
Tomás Salgado-Jiménez ◽  
Enrique Cuan-Urquizo ◽  
...  
Keyword(s):  
Trajectory Tracking ◽  
Finite Time ◽  
Experimental Validation ◽  
Sliding Mode ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Convergence Time ◽  
Sliding Mode Controller ◽  
Finite Time Convergence ◽  
Model Free

Several control strategies have been proposed for the trajectory tracking problem of Autonomous Underwater Vehicles (AUV). Most of them are model-based, hence, detailed knowledge of the parameters of the robot is needed. Few works consider a finite-time convergence in their controllers, which offers strong robustness and fast convergence compared with asymptotic or exponential solutions. Those finite-time controllers do not permit the users to predefine the convergence time, which can be useful for a more efficient use of the robot’s energy. This paper presents the experimental validation of a model-free high-order Sliding Mode Controller (SMC) with finite-time convergence in a predefined time. The convergence time is introduced by the simple change of a time-base parameter. The aim is to validate the controller so it can be implemented for cooperative missions where the communication is limited or null. Results showed that the proposed controller can drive the robot to the desired depth and heading trajectories in the predefined time for all the cases, reducing the error by up to 75% and 41% when compared with a PID and the same SMC with asymptotic convergence. The energy consumption was reduced 35% and 50% when compared with those same controllers.

scholarly journals Robust Adaptive Full-Order TSM Control Based on Neural Network

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 726 ◽  
Author(s):  
Qianlei Cao ◽  
Chongzhen Cao ◽  
Fengqin Wang ◽  
Dan Liu ◽  
Hui Sun
Keyword(s):  
Neural Network ◽  
Sliding Mode ◽  
A Priori ◽  
System Model ◽  
A Priori Knowledge ◽  
Control Methods ◽  
Terminal Sliding Mode ◽  
Finite Time Convergence ◽  
Model Free ◽  
Robust Adaptive

Existing full-order terminal sliding mode (FOTSM) control methods often require a priori knowledge of the system model. To tackle this problem, two novel neural-network-based FOTSM control methods were proposed. The first one was model based but did not require knowledge of the uncertainties’ bounds. The second one was model free and did not require knowledge of the system model. Finite-time convergence of the two schemes was verified by theoretical analysis and simulation cases. Meanwhile, the designed methods avoided singularity as well as chattering.

scholarly journals Sliding Mode Self-Sensing Control of Synchronous Machine Using Super Twisting Interconnected Observers

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4199
Author(s):  
Mohamed R. Kafi ◽  
Mohamed A. Hamida ◽  
Hicham Chaoui ◽  
Rabie Belkacemi
Keyword(s):  
Finite Time ◽  
Sliding Mode ◽  
External Perturbation ◽  
High Order ◽  
Synchronous Machines ◽  
Permanent Magnet Synchronous Machines ◽  
Finite Time Convergence ◽  
Twisting Algorithm ◽  
Stator Resistance ◽  
Measured State

The aim of this study is to propose a self-sensing control of internal permanent-magnet synchronous machines (IPMSMs) based on new high order sliding mode approaches. The high order sliding mode control will be combined with the backstepping strategy to achieve global or semi global attraction and ensure finite time convergence. The proposed control strategy should be able to reject the unmatched perturbations and reject the external perturbation. On the other hand, the super-twisting algorithm will be combined with the interconnected observer methodology to propose the multi-input–multi-output observer. This observer will be used to estimate the rotor position, the rotor speed and the stator resistance. The proposed controller and observer ensure the finite-time convergence to the desired reference and measured state, respectively. The obtained results confirm the effectiveness of the suggested method in the presence of parametric uncertainties and unmeasured load torque at various speed ranges.

scholarly journals A New Control Method for Second-Order Multiple Models Control System Based on Global Sliding Mode

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Dan-xu Zhang ◽  
Yang-wang Fang ◽  
Peng-fei Yang ◽  
You-li Wu ◽  
Tong-xin Liu
Keyword(s):  
Control System ◽  
Sliding Mode Control ◽  
Finite Time ◽  
Sliding Mode ◽  
Second Order ◽  
Multiple Models ◽  
Finite Time Convergence ◽  
Mode Control ◽  
Global Sliding Mode Control ◽  
Control Scheme

This paper proposed a finite time convergence global sliding mode control scheme for the second-order multiple models control system. Firstly, the global sliding surface without reaching law for a single model control system is designed and the tracking error finite time convergence and global stability are proved. Secondly, we generalize the above scheme to the second-order multimodel control system and obtain the global sliding mode control law. Then, the convergent and stable performances of the closed-loop control system with multimodel controllers are proved. Finally, a simulation example shows that the proposed control scheme is more effective and useful compared with the traditional sliding mode control scheme.

Time-varying sliding-mode control for finite-time convergence

2010 ◽  
Vol 92 (7-8) ◽  
pp. 257-268 ◽  
Author(s):  
Yu-Sheng Lu ◽  
Chien-Wei Chiu ◽  
Jian-Shiang Chen
Keyword(s):  
Sliding Mode Control ◽  
Finite Time ◽  
Sliding Mode ◽  
Time Varying ◽  
Finite Time Convergence ◽  
Mode Control
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