Learning and Near-Optimal Control of Underactuated Surface Vessels With Periodic Disturbances

In this article, we propose a novel learning and near-optimal control approach for underactuated surface (USV) vessels with unknown mismatched periodic external disturbances and unknown hydrodynamic parameters. Given a prior knowledge of the periods of the disturbances, an analytical near-optimal control law is derived through the approximation of the integral-type quadratic performance index with respect to the tracking error, where the equivalent unknown parameters are generated online by an auxiliary system that can learn the dynamics of the controlled system. It is proved that the state differences between the auxiliary system and the corresponding controlled USV vessel are globally asymptotically convergent to zero. Besides, the approach theoretically guarantees asymptotic optimality of the performance index. The efficacy of the method is demonstrated via simulations based on the real parameters of an USV vessel

Prescribed performance control of underactuated surface vessels' trajectory using a neural network and integral time-delay sliding mode

summary:To tackle the underactuated surface vessel (USV) trajectory tracking challenge with input delays and composite disturbances, an integral time-delay sliding mode controller based on backstepping is discussed. First, the law of virtual velocity control is established by coordinate transformation and the position error is caused to converge utilizing the performance function. At the same time, based on the estimation of velocity vector by the high-gain observer (HGO), radial basis function (RBF) neural network is applied to compensate for both the uncertainty of model parameters and external disturbances. The longitudinal and heading control laws are presented in combination with the integral time-delay sliding mode control. Then, on the basis of Lyapunov - Krasovskii functional and stability proof, virtual velocity error is guaranteed to converge to 0 in finite time. Finally, the outcomes of the numerical simulation demonstrate the reliability and efficiency of the proposed approach

Mixed control for trajectory tracking in marine vessels

Este trabajo muestra la estrategia de control de un controlador basado en álgebra lineal para la cinemática y una técnica de control adaptable para la parte dinámica del buque. Que en el primer caso (LABC) es aplicado sobre la cinemática que recibe las referencias de posición deseadas y esto genera otro par de velocidad de referencia para el controlador adaptable (dinámico). El objetivo principal de esta técnica de control combinada (LABC-adaptable) se presenta en el caso de que la masa del buque (u otro parámetro) varíe con su trayectoria (por ejemplo, buque pesquero, buque de reabastecimiento de combustible, etc.) donde el controlador combinado con características adaptables ajusta sus parámetros mediante una ley de sintonía, que a su vez genera una acción de control que compensa las variaciones dinámicas del buque. Además, este trabajo presenta el análisis de estabilidad y la ley de ajuste LABC-adaptable basada en el criterio de estabilidad de Lyapunov. Los resultados obtenidos por simulación demuestran que el sistema marino puede seguir las señales de referencia con pequeños errores aún en presencia de incertidumbres.This work proposes the design of an adaptive controller for a marine vessel; the proposed control strategy applies a controller designed on linear algebra for the kinematics and an adaptive control technique for the dynamic part of the vessel. The linear algebra based controller (LABC) for kinematics receives the desired position references and this generates another reference velocity pair for the adaptive (dynamic) controller. The main goal of the application of the adaptive control technique in this kind of enforcement is presented in the case that the mass of the vessel varies with its trajectory (e.g. fishing vessel, refueling vessel, etc.) where the adaptive controller adjusts its parameters through of adaptation law, which in turn generates a control action that compensates dynamic variations of the ship. Besides, this work presents the stability analysis and adaptive adjustment law based on the Lyapunov theory. And the simulation results that are presented prove that the control can deal with nonlinearities and time-variant dynamics.Fil: Vacca Sisterna, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Serrano, Mario Emanuel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; ArgentinaFil: Scaglia, Gustavo Juan Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigación y Desarrollo en Ingeniería de Procesos, Biotecnología y Energías Alternativas. Universidad Nacional del Comahue. Instituto de Investigación y Desarrollo en Ingeniería de Procesos, Biotecnología y Energías Alternativas; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; ArgentinaFil: Rossomando, Francisco Guido. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentin

Mixed control for trajectory tracking in marine vessels

[EN] This work proposes the design of an adaptive controller for a marine vessel; the proposed control strategy applies a controller designed on linear algebra for the kinematics and an adaptive control technique for the dynamic part of the vessel. The linear algebra based controller (LABC) for kinematics receives the desired position references and this generates another reference velocity pair for the adaptive (dynamic) controller. The main goal of the application of the adaptive control technique in this kind of enforcement is presented in the case that the mass of the vessel varies with its trajectory (e.g. fishing vessel, refueling vessel, etc.) where the adaptive controller adjusts its parameters through of adaptation law, which in turn generates a control action that compensates dynamic variations of the ship. Besides, this work presents the stability analysis and adaptive adjustment law based on the Lyapunov theory. And the simulation results that are presented prove that the control can deal with non-linearities and time-variant dynamics.[ES] Este trabajo muestra el diseño de un controlador adaptable para un buque marino; la estrategia de control que se propone es la aplicación de un controlador basado en álgebra lineal para la cinemática y una técnica de control adaptable para la parte dinámica del buque. El controlador basado en álgebra lineal (LABC) para cinemática recibe las referencias de posición deseadas y esto genera otro par de velocidad de referencia para el controlador adaptable (dinámico). El objetivo principal de la aplicación de la técnica de control adaptable se presenta en el caso de que la masa del buque varíe con su trayectoria (por ejemplo, buque pesquero, buque de reabastecimiento de combustible, etc.) donde el controlador adaptable ajusta sus parámetros mediante la ley de adaptación, que a su vez genera una acción de control que compensa las variaciones dinámicas del buque. Además, este trabajo presenta el análisis de estabilidad y la ley de ajuste adaptable basada en la teoría de Lyapunov. Los resultados de simulación muestran que el sistema puede seguir las señales de referencia con un error muy bajo aún en presencia de incertidumbre.Vacca Sisterna, C.; Serrano, E.; Scaglia, G.; Rossomando, F. (2021). Control mixto para el seguimiento de trayectoria en buques marinos. Revista Iberoamericana de Automática e Informática industrial. 19(1):27-36. https://doi.org/10.4995/riai.2021.15027OJS2736191Cui R, Chen L, Yang C, Chen M. "Extended state observer-based integral sliding mode control for an underwater robot with unknown disturbances and uncertain nonlinearities". IEEE Transactions on Industrial Electronics 2017; 64(8): 6785-6795. https://doi.org/10.1109/TIE.2017.2694410Dai SL, He S, Lin H. "Transverse function control with prescribed performance guarantees for underactuated marine surface vehicles". International Journal of Robust and Nonlinear Control 2019; 29(5): 1577-1596. https://doi.org/10.1002/rnc.4453Do K, Jiang ZP, Pan J. "Universal controllers for stabilization and tracking of underactuated ships". Systems & Control Letters 2002; 47(4): 299-317. https://doi.org/10.1016/S0167-6911(02)00214-1Fossen T. "Marine control systems. Marine cybernetics". Trondhiem, Norway 2002.Fu M,Wang T,Wang C. "Adaptive Neural-Based Finite-Time Trajectory Tracking Control for Underactuated Marine Surface Vessels With Position Error Constraint".IEEE Access 2019; 7: 16309-16322. https://doi.org/10.1109/ACCESS.2019.2895053Ghommam J, Mnif F, Derbel N. "Global stabilization and tracking control of underactuated surface vessels". IET control theory & applications 2010; 4(1): 71-88. https://doi.org/10.1049/iet-cta.2008.0131Ghommam J, Mnif F, Benali A, Derbel N. "Asymptotic backstepping stabilization of an underactuated surface vessel". IEEE Transactions on Control Systems Technology 2006; 14(6): 1150-1157. https://doi.org/10.1109/TCST.2006.880220He W, Yin Z, Sun C. "Adaptive neural network control of a marine vessel with constraints using the asymmetric barrier Lyapunov function".IEEE transactions on cybernetics 2016; 47(7): 1641-1651. https://doi.org/10.1109/TCYB.2016.2554621Hu X, Du J, Zhu G, Sun Y. "Robust adaptive NN control of dynamically positioned vessels under input constraints". Neurocomputing 2018; 318: 201-212. https://doi.org/10.1016/j.neucom.2018.08.056Liao Yl, Wan L, Zhuang Jy. "Backstepping dynamical sliding mode control method for the path following of the underactuated surface vessel". Procedia Engineering 2011; 15: 256-263. https://doi.org/10.1016/j.proeng.2011.08.051Martins, F. N., Celeste, W. C., Carelli, R., Sarcinelli-Filho, M., & BastosFilho, T. F. (2008). An adaptive dynamic controller for autonomous mobile robot trajectory tracking. Control Engineering Practice, 16(11), 1354-1363. https://doi.org/10.1016/j.conengprac.2008.03.004Nie J, Lin X. "Robust Nonlinear Path Following Control of UnderactuatedMSV With Time-Varying Sideslip Compensation in the Presence of Actuator Saturation and Error Constraint". IEEE Access 2018; 6: 71906-71917. https://doi.org/10.1109/ACCESS.2018.2881513Scaglia, Gustavo; Serrano, Emanuel; Albertos, Pedro (2020). Control de Trayectorias Basado en Algebra Lineal. Revista Iberoamericana de Automática e Informática industrial, [S.l.], ago. 2020. ISSN 1697-7920. Disponible en: https://polipapers.upv.es/index.php/RIAI/article/view/13584. https://doi.org/10.4995/riai.2020.13584Scaglia Gustavo, Serrano Mario Emanuel, Albertos Pedro (2020). "Linear Algebra Based Controller - Design and Applications". Publisher: Springer International Publishing. eBook ISBN 978-3-030-42818-1. Hardcover ISBN 978-3-030-42817-4. DOI 10.1007/978-3-030-42818-1.Scaglia, G., Mut, V., Rosales, A., Quintero, O., "Tracking Control of a Mobile Robot using Linear Interpolation", Proceeding of the 3rd International Conference on Integrated Modeling and Analysis in Applied Control and Automation, IMAACA 2007. vol. 1, pp. 11-15, ISBN: 978-2-9520712-7-7 February 8-10, 2007Serrano M.E., Scaglia G.J.E., Auat Cheein F., Mut V. and Ortiz O.A. (2015).Trajectory-tracking controller design with constraints in the control signals: a case study in mobile robots. Robotica, 33, pp 2186-2203, diciembre 2015. https://doi.org/10.1017/S0263574714001325Serrano ME, Godoy SA, Gandolfo D, Mut V, Scaglia G. "Nonlinear Trajectory Tracking Control for Marine Vessels with Additive Uncertainties". Information Technology And Control 2018; 47(1): 118-130. https://doi.org/10.5755/j01.itc.47.1.17782Tee KP, Ge SS. "Control of fully actuated ocean surface vessels using a class of feedforward approximators". IEEE Transactions on Control Systems Technology 2006; 14(4): 750-756. https://doi.org/10.1109/TCST.2006.872507Van M. "Adaptive neural integral sliding-mode control for tracking control of fully actuated uncertain surface vessels". International Journal of Robust and Nonlinear Control 2019; 29(5): 1537-1557. https://doi.org/10.1002/rnc.4455Wang N, Su S F,Yin J, Zheng Z, Er MJ. "Global asymptotic model-free trajectory-independent tracking control of an uncertain marine vehicle: An adaptive universe-based fuzzy control approach". Transactions on Fuzzy Systems 2017; 26(3):1613-1625. https://doi.org/10.1109/TFUZZ.2017.2737405Wang, D., Mu, C., & Liu, D. (2017, May). Neural network adaptive critic control with disturbance rejection. In 2017 29th Chinese Control And Decision Conference (CCDC) (pp. 202-207). IEEE. https://doi.org/10.1109/CCDC.2017.7978092Wondergem M, Lefeber E, Pettersen KY, Nijmeijer H. "Output feedback tracking of ships". 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Comprehensive review on controller for leader-follower robotic system

985-1007This paper presents a comprehensive review of the leader-follower robotics system. The aim of this paper is to find and elaborate on the current trends in the swarm robotic system, leader-follower, and multi-agent system. Another part of this review will focus on finding the trend of controller utilized by previous researchers in the leader-follower system. The controller that is commonly applied by the researchers is mostly adaptive and non-linear controllers. The paper also explores the subject of study or system used during the research which normally employs multi-robot, multi-agent, space flying, reconfigurable system, multi-legs system or unmanned system. Another aspect of this paper concentrates on the topology employed by the researchers when they conducted simulation or experimental studies

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

Control and safety of fully actuated and underactuated nonlinear systems: from adaptation to robustness to optimality

The state-of-the-art quadratic program-based control Lyapunov-control barrier function (QP-CLBF) is a powerful control approach to balance safety and stability in a pointwise optimal fashion. However, under this approach, modeling inaccuracies may degrade the performance of closed-loop systems and cause a violation of safety-critical constraints. This thesis extends the recently-developed QP-CLBF through the derivation of five novel robust quadratic program-based adaptive control approaches for fully actuated and underactuated nonlinear systems with a view toward adapting to unknown parameters, being robust to unmodeled dynamics and disturbances, ensuring the system remains in safe sets and being optimal with respect in a pointwise fashion. Simulation and quantitative results demonstrate the superiority of proposed approaches over the baseline methods.Ph.D

Bio-inspired robotic control in underactuation: principles for energy efficacy, dynamic compliance interactions and adaptability.

Biological systems achieve energy efficient and adaptive behaviours through extensive autologous and exogenous compliant interactions. Active dynamic compliances are created and enhanced from musculoskeletal system (joint-space) to external environment (task-space) amongst the underactuated motions. Underactuated systems with viscoelastic property are similar to these biological systems, in that their self-organisation and overall tasks must be achieved by coordinating the subsystems and dynamically interacting with the environment. One important question to raise is: How can we design control systems to achieve efficient locomotion, while adapt to dynamic conditions as the living systems do? In this thesis, a trajectory planning algorithm is developed for underactuated microrobotic systems with bio-inspired self-propulsion and viscoelastic property to achieve synchronized motion in an energy efficient, adaptive and analysable manner. The geometry of the state space of the systems is explicitly utilized, such that a synchronization of the generalized coordinates is achieved in terms of geometric relations along the desired motion trajectory. As a result, the internal dynamics complexity is sufficiently reduced, the dynamic couplings are explicitly characterised, and then the underactuated dynamics are projected onto a hyper-manifold. Following such a reduction and characterization, we arrive at mappings of system compliance and integrable second-order dynamics with the passive degrees of freedom. As such, the issue of trajectory planning is converted into convenient nonlinear geometric analysis and optimal trajectory parameterization. Solutions of the reduced dynamics and the geometric relations can be obtained through an optimal motion trajectory generator. Theoretical background of the proposed approach is presented with rigorous analysis and developed in detail for a particular example. Experimental studies are conducted to verify the effectiveness of the proposed method. Towards compliance interactions with the environment, accurate modelling or prediction of nonlinear friction forces is a nontrivial whilst challenging task. Frictional instabilities are typically required to be eliminated or compensated through efficiently designed controllers. In this work, a prediction and analysis framework is designed for the self-propelled vibro-driven system, whose locomotion greatly relies on the dynamic interactions with the nonlinear frictions. This thesis proposes a combined physics-based and analytical-based approach, in a manner that non-reversible characteristic for static friction, presliding as well as pure sliding regimes are revealed, and the frictional limit boundaries are identified. Nonlinear dynamic analysis and simulation results demonstrate good captions of experimentally observed frictional characteristics, quenching of friction-induced vibrations and satisfaction of energy requirements. The thesis also performs elaborative studies on trajectory tracking. Control schemes are designed and extended for a class of underactuated systems with concrete considerations on uncertainties and disturbances. They include a collocated partial feedback control scheme, and an adaptive variable structure control scheme with an elaborately designed auxiliary control variable. Generically, adaptive control schemes using neural networks are designed to ensure trajectory tracking. Theoretical background of these methods is presented with rigorous analysis and developed in detail for particular examples. The schemes promote the utilization of linear filters in the control input to improve the system robustness. Asymptotic stability and convergence of time-varying reference trajectories for the system dynamics are shown by means of Lyapunov synthesis

Graph rigidity-based formation control of planar multi-agent systems

A multi-agent system is a network of interacting agents that collectively perform a complex task. This dissertation is concerned with the decentralized formation control of multi-agent systems moving in the plane. The formation problem is defined as designing control inputs for the agents so that they form and maintain a pre-defined, planar geometric shape. The focus is on three related problems with increasing level of complexity: formation acquisition, formation maneuvering, and target interception. Three different dynamic models, also with increasing level of complexity, are considered for the motion of the agents: the single-integrator model, the double-integrator model, and the full mechanical dynamic model. Rigid graph theory and Lyapunov theory are the primary tools utilized in this work for solving the aforementioned formation problems for the three models. The backstepping control technique also plays a key role in the cases of the double-integrator and full dynamic models. Starting with the single-integrator model, a basic formation acquisition controller is proposed that is only a function of the relative position of agents in an infinitesimally and minimally rigid graph. A Lyapunov analysis shows that the origin of the inter-agent distance error system is exponentially stable. It is then shown how an extra term can be added to the controller to enable formation maneuvering or target interception. The three controllers for the single-integrator model are used as a stepping stone and extended to the double-integrator model with the aid of backstepping. Finally, an actuator-level, formation acquisition control law is developed for multiple robotic vehicles that accounts for the vehicle dynamics. Specifically, a class of underactuated vehicles modeled by Euler-Lagrange-like equations is considered. The backstepping technique is again employed while exploiting the structural properties of the system dynamics. Computer simulations are provided throughout the dissertation to show the proposed control laws in action

Lifelong Learning-Based Multilayer Neural Network Control of Nonlinear Continuous-Time Strict-Feedback Systems

In This Paper, We Investigate Lifelong Learning (LL)-Based Tracking Control for Partially Uncertain Strict Feedback Nonlinear Systems with State Constraints, employing a Singular Value Decomposition (SVD) of the Multilayer Neural Networks (MNNs) Activation Function based Weight Tuning Scheme. the Novel SVD-Based Approach Extends the MNN Weight Tuning to (Formula Presented.) Layers. a Unique Online LL Method, based on Tracking Error, is Integrated into the MNN Weight Update Laws to Counteract Catastrophic Forgetting. to Adeptly Address Constraints for Safety Assurances, Taking into Account the Effects Caused by Disturbances, We Utilize a Time-Varying Barrier Lyapunov Function (TBLF) that Ensures a Uniformly Ultimately Bounded Closed-Loop System. the Effectiveness of the Proposed Safe LL MNN Approach is Demonstrated through a Leader-Follower Formation Scenario Involving Unknown Kinematics and Dynamics. Supporting Simulation Results of Mobile Robot Formation Control Are Provided, Confirming the Theoretical Findings