Robust trajectory tracking control of underactuated unmanned surface vehicles with exponential stability: theory and experimental validation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rui Yu ◽  
Hua Zhou

Purpose Trajectory tracking is an important issue to underactuated unmanned surface vehicles (USVs). However, parametric uncertainties and environmental disturbances bring great challenges to the precise trajectory tracking control of USVs. This paper aims to propose a robust trajectory tracking control algorithm with exponential stability for underactuated USVs with parametric uncertainties and unknown environmental disturbances. Design/methodology/approach In this method, the backstepping method and sliding mode control method are combined to ensure that the underactuated USV can track and maintain the desired trajectory. In addition, a modified switching-gain adaptation algorithm is adopted to enhance the robustness and reduce chattering. Besides, the global exponential stability of the closed-loop system is proved by Lyapunov’s direct method. Findings The proposed method in this paper offers a robust trajectory tracking solution to underactuated USVs and it is verified by simulations and experiments. Compared with the traditional proportion-integral-derivative method and several state-of-the-art algorithms, the proposed method has superior performance in simulation and experimental results. Originality/value This paper proposes a robust trajectory tracking control algorithm with exponential stability for underactuated USVs. The proposed method achieves exponential stability with better robustness and transient performance.

Author(s):  
Qijia Yao

Space manipulator is considered as one of the most promising technologies for future space activities owing to its important role in various on-orbit serving missions. In this study, a robust finite-time tracking control method is proposed for the rapid and accurate trajectory tracking control of an attitude-controlled free-flying space manipulator in the presence of parametric uncertainties and external disturbances. First, a baseline finite-time tracking controller is designed to track the desired position of the space manipulator based on the homogeneous method. Then, a finite-time disturbance observer is designed to accurately estimate the lumped uncertainties. Finally, a robust finite-time tracking controller is developed by integrating the baseline finite-time tracking controller with the finite-time disturbance observer. Rigorous theoretical analysis for the global finite-time stability of the whole closed-loop system is provided. The proposed robust finite-time tracking controller has a relatively simple structure and can guarantee the position and velocity tracking errors converge to zero in finite time even subject to lumped uncertainties. To the best of the authors’ knowledge, there are really limited existing controllers can achieve such excellent performance under the same conditions. Numerical simulations illustrate the effectiveness and superiority of the proposed control method.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zafer Bingul ◽  
Oguzhan Karahan

Purpose The purpose of this paper is to address a fractional order fuzzy PID (FOFPID) control approach for solving the problem of enhancing high precision tracking performance and robustness against to different reference trajectories of a 6-DOF Stewart Platform (SP) in joint space. Design/methodology/approach For the optimal design of the proposed control approach, tuning of the controller parameters including membership functions and input-output scaling factors along with the fractional order rate of error and fractional order integral of control signal is tuned with off-line by using particle swarm optimization (PSO) algorithm. For achieving this off-line optimization in the simulation environment, very accurate dynamic model of SP which has more complicated dynamical characteristics is required. Therefore, the coupling dynamic model of multi-rigid-body system is developed by Lagrange-Euler approach. For completeness, the mathematical model of the actuators is established and integrated with the dynamic model of SP mechanical system to state electromechanical coupling dynamic model. To study the validness of the proposed FOFPID controller, using this accurate dynamic model of the SP, other published control approaches such as the PID control, FOPID control and fuzzy PID control are also optimized with PSO in simulation environment. To compare trajectory tracking performance and effectiveness of the tuned controllers, the real time validation trajectory tracking experiments are conducted using the experimental setup of the SP by applying the optimum parameters of the controllers. The credibility of the results obtained with the controllers tuned in simulation environment is examined using statistical analysis. Findings The experimental results clearly demonstrate that the proposed optimal FOFPID controller can improve the control performance and reduce reference trajectory tracking errors of the SP. Also, the proposed PSO optimized FOFPID control strategy outperforms other control schemes in terms of the different difficulty levels of the given trajectories. Originality/value To the best of the authors’ knowledge, such a motion controller incorporating the fractional order approach to the fuzzy is first time applied in trajectory tracking control of SP.


Author(s):  
ZeCai Lin ◽  
Wang Xin ◽  
Jian Yang ◽  
Zhang QingPei ◽  
Lu ZongJie

Purpose This paper aims to propose a dynamic trajectory-tracking control method for robotic transcranial magnetic stimulation (TMS), based on force sensors, which follows the dynamic movement of the patient’s head during treatment. Design/methodology/approach First, end-effector gravity compensation methods based on kinematics and back-propagation (BP) neural networks are presented and compared. Second, a dynamic trajectory-tracking method is tested using force/position hybrid control. Finally, an adaptive proportional-derivative (PD) controller is adopted to make pose corrections. All the methods are designed for robotic TMS systems. Findings The gravity compensation method, based on BP neural networks for end-effectors, is proposed due to the different zero drifts in different sensors’ postures, modeling errors in the kinematics and the effects of other uncertain factors on the accuracy of gravity compensation. Results indicate that accuracy is improved using this method and the computing load is significantly reduced. The pose correction of the robotic manipulator can be achieved using an adaptive PD hybrid force/position controller. Originality/value A BP neural network-based gravity compensation method is developed and compared with traditional kinematic methods. The adaptive PD control strategy is designed to make the necessary pose corrections more effectively. The proposed methods are verified on a robotic TMS system. Experimental results indicate that the system is effective and flexible for the dynamic trajectory-tracking control of manipulator applications.


2017 ◽  
Vol 89 (1) ◽  
pp. 87-98 ◽  
Author(s):  
Rooh ul Amin ◽  
Aijun Li

Purpose The purpose of this paper is to present μ-synthesis-based robust attitude trajectory tracking control of three degree-of-freedom four rotor hover vehicle. Design/methodology/approach Comprehensive modelling of hover vehicle is presented, followed by development of uncertainty model. A μ-synthesis-based controller is designed using the DK iteration method that not only handles structured and unstructured uncertainties effectively but also guarantees robust performance. The performance of the proposed controller is evaluated through simulations, and the controller is also implemented on experimental platform. Simulation and experimental results validate that μ-synthesis-based robust controller is found effective in: solving robust attitude trajectory tracking problem of multirotor vehicle systems, handling parameter variations and dealing with external disturbances. Findings Performance analysis of the proposed controller guarantees robust stability and also ensures robust trajectory tracking performance for nominal system and for 15-20 per cent variations in the system parameters. In addition, the results also ensure robust handling of wind gusts disturbances. Originality/value This research addresses the robust performance of hover vehicle’s attitude control subjected to uncertainties and external disturbances using μ-synthesis-based controller. This is the only method so far that guarantees robust stability and performance simultaneously.


2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Guangli Zhou ◽  
Yongming Yao ◽  
Huiying Liu ◽  
Xupeng Bai ◽  
Jianbo Liu

In this paper, we presented a strategy for accurate trajectory tracking control of a quadrotor with unknown disturbances. To guarantee that the tracking errors of all system state variables converge to zero in finite time and eliminate the chattering phenomenon caused by the switching control action, a control strategy that combines linear prediction model of disturbances and fuzzy sliding mode control (SMC) based on logical framework with side conditions (LFSC) was designed. LFSC was applied for both position and attitude tracking of the quadrotor. Firstly, a linear prediction method was devised to minimize the effects of external disturbances. Secondly, a new fuzzy law was implemented to eliminate the chattering phenomenon. In addition, the stabilities of position and attitude were demonstrated by using Lyapunov theory, respectively. Simulation results and comprehensive comparisons demonstrated the superior performance and robustness of the proposed LFSC scheme in the case of external disturbances.


Electronics ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 22 ◽  
Author(s):  
Xiaojie Sun ◽  
Guofeng Wang ◽  
Yunsheng Fan

To promote the development of military and civilian applications for marine technology, more and more scientific research around the world has begun to develop unmanned surface vehicles (USVs) technology with advanced control capabilities. This paper establishes and identifies the model of vector propulsion USV, which is widely used at present. After analyzing its actuator distribution, we consider that the more realistic vessel model should be an incomplete underactuated system. For this system, a virtual control point method is adopted and an adaptive sliding mode trajectory tracking controller with neural network minimum learning parameter (NNMLP) theory is designed. Finally, in the simulation experiment, the thruster speed and propulsion angle are used as the inputs of the controller, and the linear and circular trajectory tracking tests are carried out considering the delay effect of the actuator, system uncertainty, and external disturbance. The results show that the proposed tracking control framework is reasonable.


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