Fast and accurate trajectory tracking control of an autonomous surface vehicle with unmodeled dynamics and disturbances

In this paper, fast and accurate trajectory tracking control of an autonomous surface vehicle (ASV) with complex unknowns including unmodeled dynamics, uncertainties and/or unknown disturbances is addressed within a proposed homogeneity-based finite-time control (HFC) framework. Major contributions are as follows: (1) In the absence of external disturbances, a nominal HFC framework is established to achieve exact trajectory tracking control of an ASV, whereby global finitetime stability is ensured by combining homogeneous analysis and Lyapunov approach; (2) Within the HFC scheme, a finite-time disturbance observer (FDO) is further nested to rapidly and accurately reject complex disturbances, and thereby contributing to an FDO-based HFC (FDO-HFC) scheme which can realize exactness of trajectory tracking and disturbance observation; (3) Aiming to exactly deal with complicated unknowns including unmodeled dynamics and/or disturbances, a finite-time unknown observer (FUO) is deployed as a patch for the nominal HFC framework, and eventually results in an FUO-based HFC (FUOHFC) scheme which guarantees that accurate trajectory tracking can be achieved for an ASV under harsh environments. Simulation studies and comprehensive comparisons conducted on a benchmark ship demonstrate the effectiveness and superiority of the proposed HFC schemes

Adaptive neural network control of underactuated surface vessels with guaranteed transient performance: Theory and experimental results

In this paper, an adaptive trajectory trackingcontrol algorithm for underactuated unmanned surfacevessels (USVs) with guaranteed transient performance isproposed. To meet the realistic dynamical model of USVs,we consider that the mass and damping matrices are notdiagonal and the input saturation problem. Neural Networks(NNs) are employed to approximate the unknown externaldisturbances and uncertain hydrodynamics of USVs. Moreover,both full state feedback control and output feedbackcontrol are presented, and the unmeasurable velocities ofthe output feedback controller are estimated via a highgainobserver. Unlike the conventional control methods,we employ the error transformation function to guaranteethe transient tracking performance. Both simulation andexperimental results are carried out to validate the superiorperformance via comparing with traditional potential integral(PI) control approaches

NONLINEAR ADAPTIVE HEADING CONTROL FOR AN UNDERACTUATED SURFACE VESSEL WITH CONSTRAINED INPUT AND SIDESLIP ANGLE COMPENSATION

In this paper, a nonlinear adaptive heading controller is developed for an underactuated surface vessel with constrained input and sideslip angle compensation. The controller design is accomplished in a framework of backstepping technique. First, to amend the irrationality of the traditional definition of the desired heading, the desired heading is compensated by the sideslip angle. Considering the actuator physical constrain, a hyperbolic tangent function and a Nussbaum function are introduced to handle the nonlinear part of control input. The error and the disturbance are estimated and compensated by an adaptive control law. In addition, to avoid the complicated calculation of time derivatives of the virtual control, the command filter is introduced to integrate with the control law. It is analysed by the Lyapunov theory that the closed loop system is guaranteed to be uniformly ultimately bounded stability. Finally, the simulation studies illustrate the effectiveness of the proposed control method

Review of sliding mode control application in autonomous underwater vehicles

973-984This paper presents a review of sliding mode control for autonomous underwater vehicles (AUVs). The AUVs are used under water operating in the presence of uncertainties (due to hydrodynamics coefficients) and external disturbances (due to water currents, waves, etc.). Sliding mode controller is one of the nonlinear robust controllers which is robust towards uncertainties, parameter variations and external disturbances. The evolution of sliding mode control in motion control studies of autonomous underwater vehicles is summarized throughout for the last three decades. The performance of the controller is examined based on the chattering reduction, accuracy (steady state error reduction), and robustness against perturbation. The review on sliding mode control for AUVs provides insights for readers to design new techniques and algorithms, to enhance the existing family of sliding mode control strategies into a new one or to merge and re-supervise the control techniques with other control strategies, in which, the aim is to obtain good controller design for AUVs in terms of great performance, stability and robustness

Fuzzy-Based Optimal Adaptive Line-of-Sight Path Following for Underactuated Unmanned Surface Vehicle with Uncertainties and Time-Varying Disturbances

This paper investigates the path following control problem for an underactuated unmanned surface vehicle (USV) in the presence of dynamical uncertainties and time-varying external disturbances. Based on fuzzy optimization algorithm, an improved adaptive line-of-sight (ALOS) guidance law is proposed, which is suitable for straight-line and curve paths. On the basis of guidance information provided by LOS, a three-degree-of-freedom (DOF) dynamic model of an underactuated USV has been used to design a practical path following controller. The controller is designed by combining backstepping method, neural shunting model, neural network minimum parameter learning method, and Nussbaum function. Neural shunting model is used to solve the problem of “explosion of complexity,” which is an inherent illness of backstepping algorithm. Meanwhile, a simpler neural network minimum parameter learning method than multilayer neural network is employed to identify the uncertainties and time-varying external disturbances. In particular, Nussbaum function is introduced into the controller design to solve the problem of unknown control gain coefficient. And much effort is made to obtain the stability for the closed-loop control system, using the Lyapunov stability theory. Simulation experiments demonstrate the effectiveness and reliability of the improved LOS guidance algorithm and the path following controller

A Study on the Automatic Ship Control Based on Adaptive Neural Networks

Recently, dynamic models of marine ships are often required to design advanced control systems. In practice, the dynamics of marine ships are highly nonlinear and are affected by highly nonlinear, uncertain external disturbances. This results in parametric and structural uncertainties in the dynamic model, and requires the need for advanced robust control techniques. There are two fundamental control approaches to consider the uncertainty in the dynamic model: robust control and adaptive control. The robust control approach consists of designing a controller with a fixed structure that yields an acceptable performance over the full range of process variations. On the other hand, the adaptive control approach is to design a controller that can adapt itself to the process uncertainties in such a way that adequate control performance is guaranteed. In adaptive control, one of the common assumptions is that the dynamic model is linearly parameterizable with a fixed dynamic structure. Based on this assumption, unknown or slowly varying parameters are found adaptively. However, structural uncertainty is not considered in the existing control techniques. To cope with the nonlinear and uncertain natures of the controlled ships, an adaptive neural network (NN) control technique is developed in this thesis. The developed neural network controller (NNC) is based on the adaptive neural network by adaptive interaction (ANNAI). To enhance the adaptability of the NNC, an algorithm for automatic selection of its parameters at every control cycle is introduced. The proposed ANNAI controller is then modified and applied to some ship control problems. Firstly, an ANNAI-based heading control system for ship is proposed. The performance of the ANNAI-based heading control system in course-keeping and turning control is simulated on a mathematical ship model using computer. For comparison, a NN heading control system using conventional backpropagation (BP) training methods is also designed and simulated in similar situations. The improvements of ANNAI-based heading control system compared to the conventional BP one are discussed. Secondly, an adaptive ANNAI-based track control system for ship is developed by upgrading the proposed ANNAI controller and combining with Line-of-Sight (LOS) guidance algorithm. The off-track distance from ship position to the intended track is included in learning process of the ANNAI controller. This modification results in an adaptive NN track control system which can adapt with the unpredictable change of external disturbances. The performance of the ANNAI-based track control system is then demonstrated by computer simulations under the influence of external disturbances. Thirdly, another application of the ANNAI controller is presented. The ANNAI controller is modified to control ship heading and speed in low-speed maneuvering of ship. Being combined with a proposed berthing guidance algorithm, the ANNAI controller becomes an automatic berthing control system. The computer simulations using model of a container ship are carried out and shows good performance. Lastly, a hybrid neural adaptive controller which is independent of the exact mathematical model of ship is designed for dynamic positioning (DP) control. The ANNAI controllers are used in parallel with a conventional proportional-derivative (PD) controller to adaptively compensate for the environmental effects and minimize positioning as well as tracking error. The control law is simulated on a multi-purpose supply ship. The results are found to be encouraging and show the potential advantages of the neural-control scheme.1. Introduction = 1 1.1 Background and Motivations = 1 1.1.1 The History of Automatic Ship Control = 1 1.1.2 The Intelligent Control Systems = 2 1.2 Objectives and Summaries = 6 1.3 Original Distributions and Major Achievements = 7 1.4 Thesis Organization = 8 2. Adaptive Neural Network by Adaptive Interaction = 9 2.1 Introduction = 9 2.2 Adaptive Neural Network by Adaptive Interaction = 11 2.2.1 Direct Neural Network Control Applications = 11 2.2.2 Description of the ANNAI Controller = 13 2.3 Training Method of the ANNAI Controller = 17 2.3.1 Intensive BP Training = 17 2.3.2 Moderate BP Training = 17 2.3.3 Training Method of the ANNAI Controller = 18 3. ANNAI-based Heading Control System = 21 3.1 Introduction = 21 3.2 Heading Control System = 22 3.3 Simulation Results = 26 3.3.1 Fixed Values of n and = 28 3.3.2 With adaptation of n and r = 33 3.4 Conclusion = 39 4. ANNAI-based Track Control System = 41 4.1 Introduction = 41 4.2 Track Control System = 42 4.3 Simulation Results = 48 4.3.1 Modules for Guidance using MATLAB = 48 4.3.2 M-Maps Toolbox for MATLAB = 49 4.3.3 Ship Model = 50 4.3.4 External Disturbances and Noise = 50 4.3.5 Simulation Results = 51 4.4 Conclusion = 55 5. ANNAI-based Berthing Control System = 57 5.1 Introduction = 57 5.2 Berthing Control System = 58 5.2.1 Control of Ship Heading = 59 5.2.2 Control of Ship Speed = 61 5.2.3 Berthing Guidance Algorithm = 63 5.3 Simulation Results = 66 5.3.1 Simulation Setup = 66 5.3.2 Simulation Results and Discussions = 67 5.4 Conclusion = 79 6. ANNAI-based Dynamic Positioning System = 80 6.1 Introduction = 80 6.2 Dynamic Positioning System = 81 6.2.1 Station-keeping Control = 82 6.2.2 Low-speed Maneuvering Control = 86 6.3 Simulation Results = 88 6.3.1 Station-keeping = 89 6.3.2 Low-speed Maneuvering = 92 6.4 Conclusion = 98 7. Conclusions and Recommendations = 100 7.1 Conclusion = 100 7.1.1 ANNAI Controller = 100 7.1.2 Heading Control System = 101 7.1.3 Track Control System = 101 7.1.4 Berthing Control System = 102 7.1.5 Dynamic Positioning System = 102 7.2 Recommendations for Future Research = 103 References = 104 Appendixes A = 112 Appendixes B = 11

Defense and Tolerance Technique Against Attacks and Faults on Leader-Following Multi-USVs

This study explores the leader-following consensus tracking control issue of multiple unmanned surface vehicles (multi-USVs) in the presence of malicious connectivity-mixed attacks in the cyber layer, and concurrent output channel noises, sensor/actuator faults, and wave-induced disturbances in the physical layer. Sensor/actuator faults are initially modeled with unified incipient and abrupt features. Additionally, connectivity-mixed attacks are depicted using connectivity-paralyzed and connectivity-maintained topologies through nonoverlapping and switching iterations. The standardization and observer design in multi-USVs are incorporated to decouple the augmented dynamics and estimate unknown state, fault, and noise observations, and then a defense and fault-tolerant consensus tracking control approach is designed to accomplish the robustness to disturbances/noises, resilience to attacks, and tolerance to faults, simultaneously. The criteria for achieving leader-following exponential consensus tracking of multi-USVs with cyber-physical threats can be determined based on activation rate and attack frequency indicators. Comparative simulations outline the effectiveness and economy of the proposed defense and tolerance technique against sensor/actuator faults and cyber-attacks on multi-USVs

Development of Robust Control Strategies for Autonomous Underwater Vehicles

The resources of the energy and chemical balance in the ocean sustain mankind in many ways. Therefore, ocean exploration is an essential task that is accomplished by deploying Underwater Vehicles. An Underwater Vehicle with autonomy feature for its navigation and control is called Autonomous Underwater Vehicle (AUV). Among the task handled by an AUV, accurately positioning itself at a desired position with respect to the reference objects is called set-point control. Similarly, tracking of the reference trajectory is also another important task. Battery recharging of AUV, positioning with respect to underwater structure, cable, seabed, tracking of reference trajectory with desired accuracy and speed to avoid collision with the guiding vehicle in the last phase of docking are some significant applications where an AUV needs to perform the above tasks. Parametric uncertainties in AUV dynamics and actuator torque limitation necessitate to design robust control algorithms to achieve motion control objectives in the face of uncertainties. Sliding Mode Controller (SMC), H / μ synthesis, model based PID group controllers are some of the robust controllers which have been applied to AUV. But SMC suffers from less efficient tuning of its switching gains due to model parameters and noisy estimated acceleration states appearing in its control law. In addition, demand of high control effort due to high frequency chattering is another drawback of SMC. Furthermore, real-time implementation of H / μ synthesis controller based on its stability study is restricted due to use of linearly approximated dynamic model of an AUV, which hinders achieving robustness. Moreover, model based PID group controllers suffer from implementation complexities and exhibit poor transient and steady-state performances under parametric uncertainties. On the other hand model free Linear PID (LPID) has inherent problem of narrow convergence region, i.e.it can not ensure convergence of large initial error to zero. Additionally, it suffers from integrator-wind-up and subsequent saturation of actuator during the occurrence of large initial error. But LPID controller has inherent capability to cope up with the uncertainties. In view of addressing the above said problem, this work proposes wind-up free Nonlinear PID with Bounded Integral (BI) and Bounded Derivative (BD) for set-point control and combination of continuous SMC with Nonlinear PID with BI and BD namely SM-N-PID with BI and BD for trajectory tracking. Nonlinear functions are used for all P,I and D controllers (for both of set-point and tracking control) in addition to use of nonlinear tan hyperbolic function in SMC(for tracking only) such that torque demand from the controller can be kept within a limit. A direct Lyapunov analysis is pursued to prove stable motion of AUV. The efficacies of the proposed controllers are compared with other two controllers namely PD and N-PID without BI and BD for set-point control and PD plus Feedforward Compensation (FC) and SM-NPID without BI and BD for tracking control. Multiple AUVs cooperatively performing a mission offers several advantages over a single AUV in a non-cooperative manner; such as reliability and increased work efficiency, etc. Bandwidth limitation in acoustic medium possess challenges in designing cooperative motion control algorithm for multiple AUVs owing to the necessity of communication of sensors and actuator signals among AUVs. In literature, undirected graph based approach is used for control design under communication constraints and thus it is not suitable for large number of AUVs participating in a cooperative motion plan. Formation control is a popular cooperative motion control paradigm. This thesis models the formation as a minimally persistent directed graph and proposes control schemes for maintaining the distance constraints during the course of motion of entire formation. For formation control each AUV uses Sliding Mode Nonlinear PID controller with Bounded Integrator and Bounded Derivative. Direct Lyapunov stability analysis in the framework of input-to-state stability ensures the stable motion of formation while maintaining the desired distance constraints among the AUVs