Fault tolerant control of UMV based on sliding mode output feedback
Introduction
With the development of global marine resources and the increasingly fierce competition of military equipment, the control of unmanned marine vehicle (UMV) systems is attracting more and more attention from research domestic and overseas. Critical technology topics of UMV include propulsion, power, positioning and software, and each issue is still under research [1]. UMV is divided into unmanned surface vehicle (USV) and unmanned underwater vehicle (UUV) [2], [3], which includes autonomous underwater vehicle (AUV) [4], [5] and remotely operated vehicle (ROV) [6], [7].
The marine vehicles are subject to breakdown, meanwhile the thruster is one of the most malfunctioning sources [8], so some different forms of fault recovery/fault tolerance exist in the control system [9]. When the UMV carry out tasks, the oscillation of yaw velocity error and yaw angle arised by external disturbances is undesired in applications [10]. For the fault tolerant control problems in different fields, the establishment of FDI mechanism [11] or fault model [12], [13] is usually considered in the basic work, and developing the fault mode for control systems is a more intuitive way by contrast. In terms of the UMV, how to establish the fault model is essential to FTC systems, and how to design a satisfactory control strategy to attenuate above oscillation amplitudes is significative and attractive.
It is well-known that the sliding mode control is an effective method of handling nonlinear systems such as the chaotic system [14], [15] and the Lur’s systems [16], [17] with unexpected faults due to its features including ease of implementation, prompt response and excellent robust ability to system uncertainties and external disturbances in practical situations [7], [18], [19]. For example, Soylu, et al. [20], [21] work on a sliding mode controller with fault-tolerant thruster allocation for ROVs, and the propeller is assumed to fail completely and partially; an actuator FTC strategy applied different techniques such as PID, backstepping and sliding mode approaches has been studied in fault-free and fault conditions for a ROV [22]. Among the most existing FTC methods of UMV [23], [24], [25], thrusters with non-fault, complete fault, and partial fault are frequently considered. However, the time-varying stuck fault is easy to occur as well and has a severe influence on the efficiency of thrusters. Therefore, when thrusters encounter different faults, the fault model is the key of FTC systems. The first motivation is to build a comprehensive and unified fault model including the time-varying stuck fault for UMV thrusters.
Since the marine environment is full of wind, waves, and current, external disturbances against the marine vehicle system may cause the vibration of yaw velocity error and yaw angle. A passive fault tolerant control allocation for small UUVs is discussed without external disturbances in [2]. On the contrary, the FTC system includes the external disturbance term all the time to handle the robust problem of the control system in this paper. Some researches depending on conditions where state feedback information can be obtained directly or indirectly address the FTC and other problems of UMV systems [26], [27], [28]. It is noted that the surge velocity, sway velocity, and yaw velocity of a UMV are not always obtainable in applications, particularly the yaw velocity. Thus, dynamic output feedback is a reasonable solution for UMV systems. For instance, an output feedback controller for a UMV in network environments is proposed in [10]. Besides, there is a common assumption in current sliding mode control methods that the dimension of measured output is not less than that of control input [29], [30], [31]. In this paper, the assumption is eliminated by utilizing input matrix full-rank decomposition technique. This technique has been studied in robust adaptive FTC of uncertain linear systems based on sliding mode output feedback [32], but it has not been applied to ship nonlinear systems. The LMI framework is a common means to ensure that the designed controller satisfies the existence conditions in linear systems [33], [34] and nonlinear systems [35], [36], [37]. Based on input matrix full-rank decomposition technique and H∞ technique, a sufficient condition of sliding mode in the form of LMIs is given [38]. From the above, relatively little attention has been focused on research into FTC for UMV systems comprising the two classes of methods, namely sliding mode control and output feedback. As a result, the second motivation is to develop a UMV fault tolerant control method based on sliding mode output feedback to reduce the amplitudes of yaw velocity error and yaw angle, where the situation is more complicated than the existing strategies.
This paper is concerned with the fault tolerant controller of UMV with thruster faults based on sliding mode output feedback. The main contributions are twofold: (1) a comprehensive fault model is established for UMV thrusters with non-fault, partial fault, complete fault and stuck fault for the first time; (2) a fault tolerant controller of UMV with thruster faults and external disturbances based on sliding mode output feedback is put forward.
The rest of this paper is arranged as follows: Section 2 presents some useful definitions and lemmas; Section 3 states UMV and fault model, and describes the system with thruster fault model; Section 4 presents the stability analysis at first, then gives the design of the output feedback controller and sliding surface; Section 5 shows the comparative simulation results, and Section 6 concludes the paper.
Section snippets
Definition of adaptive H∞ performance
Definition 1 [39] Consider the following closed-loop systemwhere ξ(t) ∈ Rn is the state vector, ω(t) is an external disturbance in z(t) ∈ Rr is the controlled output, a is parameter vector and is the time-varying vector to be estimated. and are time-varying matrices that depend on a and . For a positive constant γ, if the system (1) has the following properties: (1) The system is
UMV and fault model
The kinematics and dynamics model of a nonlinear anchored marine vehicle in [44] is in 6 degrees of freedom and the environmental disturbances involve waves, wind, and current. For a UMV, the positions xp, yp and the yaw angle ψ are presented in the earth-fixed reference frame, while the surge velocity, sway velocity and yaw velocity (q, v, r) are presented in the body-fixed reference frame. First:
Stability analysis
First, suppose the input matrix E can be decomposed intowhere and have the same rank l0 ≤ p. There is an important lemma given as follows. Lemma 5 [45] For matrix decomposition (18) and all j ∈ I(1, L), there is a positive constant μ which makes the following inequality true Remark 4 The matrix full-rank decomposition technique is utilized to decompose input matrix E into E2dN, which guarantees m > l0 and the matrix is nonsingular. This technique has been studied
Simulation results
Simulation results are represented to demonstrate the effectiveness and feasibility of the proposed FTC method of unmanned marine vehicles with thruster faults based on the sliding mode output feedback. The continuous-time system (13) parameters areIn the simulation,
Conclusions
A fault tolerant controller based on sliding mode output feedback for UMV has been studied to deal with thruster faults during missions. It is utilized to reduce the oscillation of yaw velocity error and yaw angle. Compared with the state feedback control and incomprehensive fault types, the proposed approach concludes a unified fault model including non-fault, complete fault, partial fault and stuck fault, which is more in line with the actual situations of UMV thrusters. Via adaptive sliding
Acknowledgement
This work is supported by the National Natural Science Foundation of China (Grant nos. 61503055, 61602077, 71831002), Dalian Innovative Support Scheme for High-level Talents (2017RQ072), Program for Innovative Research Team in University of Ministry of Education of China and the Fundamental Research Funds for the Central University (3132019104, 3132019501, 31322019502).
References (46)
- et al.
A nonlinear fault-tolerant thruster allocation architecture for underwater remotely operated vehicles
IFAC Papersonline
(2016) - et al.
Network-based modelling and dynamic output feedback control for unmanned marine vehicles in network environments
Automatica
(2018) - et al.
Sensor fault detection and estimation for switched power electronics systems based on sliding mode observer
Appl. Math. Comput.
(2019) - et al.
Improved criteria for sampled-data synchronization of chaotic Lur’s systems using two new approaches
Nonlinear Anal. Hybrid Syst.
(2017) - et al.
Simulation and tracking control based on neural-network strategy and sliding-mode control for underwater remotely operated vehicle
Neurocomputing
(2009) - et al.
A chattering-free sliding-mode controller for underwater vehicles with fault-tolerant infinity-norm thrust allocation
Ocean Eng.
(2008) - et al.
Dynamic surface fault tolerant control for underwater remotely operated vehicles
ISA Trans.
(2018) - et al.
Adaptive neural network-based backstepping fault tolerant control for underwater vehicles with thruster fault
Ocean Eng.
(2015) - et al.
Delayed adaptive output feedback sliding mode control for offshore platforms subject to nonlinear wave-induced force[j]
Ocean Engineering
(2015) - et al.
An output feedback controller with improved transient response of marine vessels in dynamic positioning
IFAC PapersOnLine
(2016)
Network-based h∞ state estimation for neural networks using imperfect measurement
Appl. Math. Comput.
Identification of dynamically positioned ships
Model. Identif. Control
Unmanned maritime vehicles 20 years of commercial and technical evolution
OCEANS 2016 MTS/IEEE Monterey
Passive fault tolerant control allocation for small unmanned underwater vehicle
J. Marin. Eng. Technol.
Modeling of underwater vehicles
Encyclopedia of Robotics
Design of autonomous underwater vehicle motion control using sliding mode control method
Proceedings of the 2015 International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA), IEEE
Optimal control of an autonomous underwater vehicle equipped with the collective and cyclic pitch propeller
Proceedings of the 2017 11th Asian Control Conference (ASCC), IEEE
Stabilizing control based observer for a remotely operated vehicle (ROV-observer)
Proceedings of the 2015 3rd International Conference on Control, Engineering & Information Technology (CEIT). IEEE
A strategy for thruster fault-tolerant control applied to an AUV
International Conference on Methods and MODELS in Automation and Robotics
Fault-tolerant control of an autonomous underwater vehicle
Oceans
Transmission-dependent fault detection and isolation strategy for networked systems under finite capacity channels
IEEE Trans. Cybern.
Finite frequency fault detection for a class of nonhomogeneous Markov jump systems with nonlinearities and sensor failures
Nonlinear Dyn.
The influence ranking for testers in bug tracking systems
Int. J. Softw. Eng. Knowl. Eng.
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2022, Ocean EngineeringCitation Excerpt :The problems to be overcome in the control system are uncertain or unknown USV parameters, environmental disturbances, and actuator saturation. The most widely used controller methods are dynamic surface control (DSC) (Chwa, 2011; Liu et al., 2017), sliding mode control (SMC) (Hao et al., 2019), adaptive control (Zhang and Zhang, 2015; Do and Pan, 2004; Do et al., 2004), fuzzy control (Nie and Lin, 2019), and backstepping control (Xu et al., 2021; Zheng and Zou, 2016). However, for a USV model with nonlinearity and uncertainty, such a controller will be complicated and difficult to apply.