Article
Automation & Control Systems
Zhen-Guo Liu, Hongli Dong, Weixing Chen, Weidong Zhang
Summary: This article investigates the adaptive regulation problem of uncertain delayed nonlinear systems and presents two unified adaptive control methods to achieve global asymptotic stability by introducing dynamic gain transformation and using homogeneous domination method.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Automation & Control Systems
Ania Adil, Abdelghani Hamaz, Ibrahima N'Doye, Ali Zemouche, Taous-Meriem Laleg-Kirati, Fazia Bedouhene
Summary: In this paper, a high-gain observer design method is proposed for nonlinear systems with time-varying delayed output measurements. The HG/LMI observer allows for a larger bound of the time-delay compared to the standard high-gain methodology, and it adopts a lower tuning parameter value. The proposed methodology provides more general synthesis conditions and can be applied to systems with nonlinear outputs.
Article
Engineering, Mechanical
Mohammad Al Janaideh, Almuatazbellah M. Boker, Micky Rakotondrabe
Summary: This study proposes a new output-feedback tracking control scheme for a class of precision motion systems with unknown hysteresis nonlinearity and linear dynamics. The effectiveness of the method is demonstrated through simulation and experimental results.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Automation & Control Systems
Yanjie Chang, Tongjun Sun, Xianfu Zhang, Xiandong Chen
Summary: This paper investigates the output feedback stabilization problem for a class of cascade nonlinear ODE-PDE systems, where the unstable diffusion equation is considered and the stability of the closed-loop system is analyzed using Lyapunov theorem. It proposes a control strategy based on low gain observer and proper gain parameters design. Two numerical examples are provided to demonstrate the effectiveness of the proposed approach.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2021)
Article
Automation & Control Systems
Yu Zeng, Tianrui Chen, Cong Wang
Summary: In this paper, a fault diagnosis approach based on the deterministic learning approach is proposed for a class of nonlinear uncertain systems. An adaptive learning observer is constructed using neural networks to approximate the unknown system dynamics under normal and fault modes. The convergence of state estimation is guaranteed based on the strictly positive real condition. Through the deterministic learning approach, the partial persistent excitation condition is satisfied, allowing for accurate identification of the unknown dynamics and fault detection. The analytical result demonstrates the importance of both observer gain matrix and PE level of the regressor subvector of the neural network in the exponential convergence condition of the learning observer. Simulation results verify the effectiveness of the proposed scheme.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2023)
Article
Automation & Control Systems
Jin Zhang, Lu Liu, Xinghu Wang, Haibo Ji
Summary: This article proposes a novel observer-based output feedback control approach to address the distributed optimal coordination problem of uncertain nonlinear multi-agent systems in the normal form over unbalanced directed graphs. The main challenges of the concerned problem lie in unbalanced directed graphs and nonlinearities of multi-agent systems with their agent states not available for feedback control. Based on a two-layer controller structure, a distributed optimal coordinator is first designed to convert the considered problem into a reference-tracking problem. Then a decentralized output feedback controller is developed to stabilize the resulting augmented system. A high-gain observer is exploited in controller design to estimate the agent states in the presence of uncertainties and disturbances so that the proposed controller relies only on agent outputs. The semi-global convergence of the agent outputs toward the optimal solution that minimizes the sum of all local cost functions is proved under standard assumptions. A key feature of the obtained results is that the nonlinear agents under consideration are only required to be locally Lipschitz and possess globally asymptotically stable and locally exponentially stable zero dynamics.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Maopeng Ran, Juncheng Li, Lihua Xie
Summary: A new ESO design technique based on cascading a series of ESOs is proposed in this paper to limit the maximal implemented gain by inserting saturations into the observer internal variables. It is shown that adopting appropriate nonlinear gain mechanisms improves measurement noise tolerance. The new ESO based output feedback control has stronger uncertainty estimation and compensation capability compared to the standard ESO based output feedback control.
Article
Automation & Control Systems
Xincheng Zhuang, Haoping Wang, Sofiane Ahmed-Ali, Yang Tian
Summary: This article proposes a joint adaptive high-gain observer design method for a class of nonlinear systems subject to sampled output data measurements. The proposed method overcomes the difficulty caused by the coupling between the nonlinear term and unknown parameters. By introducing a closed-loop output predictor and a decoupling method, the proposed observer achieves exponential convergence of the estimation for both the unknown state and parameter.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Automation & Control Systems
Zhi-Liang Zhao, Ruonan Yuan, Bao-Zhu Guo, Zhong-Ping Jiang
Summary: This paper considers the finite-time stabilization problem for a class of multi-input multi-output nonlinear systems composed of several different subsystems. It presents a novel decentralized, continuous finite-time output-feedback control algorithm by compensating the unknown nonlinear couplings and applying a saturation technique. The effectiveness of the proposed design is validated through rigorous mathematical analysis and numerical simulations.
SIAM JOURNAL ON CONTROL AND OPTIMIZATION
(2023)
Article
Engineering, Mechanical
Yingying Shen, Junyong Zhai
Summary: The article introduces a dynamic output feedback controller for high-order nonlinear systems with uncertain output function. The controller first globally stabilizes the nominal system and then addresses the nonlinear terms by introducing a well-designed gain. This control scheme can be applied to stabilize a family of high-order nonlinear upper-triangular systems, as demonstrated by three examples.
NONLINEAR DYNAMICS
(2021)
Article
Automation & Control Systems
Ahlem Dorgham, Mohamed Ali Hammami
Summary: This paper investigates the problem of global practical tracking control for a family of uncertain nonlinear systems with unknown output function. A high-gain observer is used to reconstruct the unmeasured system states and handle the unknown output function. An adaptive output feedback controller is designed based on the observer to guarantee reference trajectory tracking. The effectiveness of the proposed design scheme is illustrated with a practical example.
INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING
(2023)
Article
Engineering, Mechanical
Chunting Ji, Zhengqiang Zhang
Summary: This article investigates state and parameter estimation problems for ODE-PDE coupled systems, where the parabolic PDE sensor includes nonlinear dynamics and parameter uncertainty. The main challenge is the inconvenient measurability of the link point between the ODE part and the PDE part. The objective of the paper is to build an adaptive observer that provides online estimates of states and unknown parameters based on only boundary state measurement. The effectiveness of the theoretical results is confirmed through a simulation example.
NONLINEAR DYNAMICS
(2023)
Article
Automation & Control Systems
Yize Mi, Jianyong Yao
Summary: This article presents an output feedback control scheme for a class of SISO nonlinear systems, addressing the uncertainties and disturbances to guarantee tracking accuracy and steady-state performance.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Automation & Control Systems
Yize Mi, Jianyong Yao
Summary: This article addresses the tracking control problem of a class of control-affine nonlinear systems subject to input saturation, parametric uncertainties, and unmodeled uncertainties. A nested-saturation-function-based controller integrated with feedforward model compensation is proposed. A saturated linear extended state observer (SLESO) and parameter adaptation law are used to compensate for unmodeled uncertainties and parametric uncertainties respectively. The proposed scheme guarantees steady-state tracking performance through uncertainty compensation and effectively addresses the conservativeness issue in the input saturation problem by online-updating the available unsaturated region, improving transient performance. The proposed scheme ensures asymptotic stability under constant unmodeled uncertainties and ultimate boundedness under time-varying unmodeled uncertainties. Simulation studies are presented to demonstrate the effectiveness of the proposed approach.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Zhiliang Liu, Peng Shi, Bing Chen, Chong Lin
Summary: This paper discusses the adaptive neural output feedback control for uncertain nonlinear switched systems, presenting a robust observer design scheme using convex combination approach, and developing an observer-based output feedback control strategy.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Automation & Control Systems
Boubekeur Targui, Omar Hernandez-Gonzalez, Carlos-Manuel Astorga-Zaragoza, Gerardo-Vicente Guerrero-Ramirez, Maria-Eusebia Guerrero-Sanchez
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2019)
Article
Automation & Control Systems
Omar Hernandez-Gonzalez, Maria-Eusebia Guerrero-Sanchez, Mondher Farza, Tomas Menard, Mohammed M'Saad, Rogelio Lozano
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2019)
Article
Mathematics
Maria-Eusebia Guerrero-Sanchez, Omar Hernandez-Gonzalez, Rogelio Lozano, Carlos-D Garcia-Beltran, Guillermo Valencia-Palomo, Francisco-R Lopez-Estrada
Article
Automation & Control Systems
O. Hernandez-Gonzalez, F. Ramirez-Rasgado, C. M. Astorga-Zaragoza, M. E. Guerrero-Sanchez, G. Valencia-Palomo, A. E. Rodriguez-Mata
Summary: This paper introduces a new approach of continuous-discrete observer design for uncertain state-affine non-linear systems, developing and analyzing a high-gain observer redesign under insightful conditions. The proposed observer estimates the state vector using system output measurements with long sampling times, achieved by considering a persistent excitation condition that can be validated online. The algorithm's performance is evaluated under time-varying sampled measurements to estimate the friction factor of a pipeline, taking into account noisy sampled output measurements.
IET CONTROL THEORY AND APPLICATIONS
(2021)
Article
Automation & Control Systems
B. Targui, O. Hernandez-Gonzalez, C. M. Astorga-Zaragoza, M. E. Guerrero-Sanchez, G. Valencia-Palomo
Summary: This paper introduces a novel chain observer for Lipschitz nonlinear systems with multiple time-varying long delays, expanding the application to a wider class of systems. The observer design utilizes a chain of state observers with a consistent structure and includes proportional-integral dynamical terms to compensate for the time-delay effect. The observer gains are obtained from less restrictive LMI synthesis conditions, ensuring convergence to zero observation error as demonstrated by a Lyapunov-Krasovskii functional analysis.
ASIAN JOURNAL OF CONTROL
(2022)
Article
Mathematics, Applied
Boubekeur Targui, Omar Hernandez-Gonzalez, Carlos-Manuel Astorga-Zaragoza, Maria-Eusebia Guerrero-Sanchez, Guillermo Valencia-Palomo
Summary: The paper proposes a novel disturbance observer based on a cascade structure for a class of Lipschitz nonlinear systems. The observer is designed to handle model uncertainties and external disturbances, as well as multiple time-varying delays. The observation scheme consists of a cascade of state observers, each tasked with estimating the state over a short time interval. The proposed approach involves less-restrictive Lipschitz inequalities for describing the nonlinear system, and the convergence analysis demonstrates the observer's ability to attenuate observation error.
COMPUTATIONAL & APPLIED MATHEMATICS
(2022)
Article
Engineering, Mechanical
P. Aguilar-Alvarez, G. Valencia-Palomo, J. Enriquez-Zarate, J. Morales-Valdez, O. Hernandez-Gonzalez
Summary: This paper presents an active tuned mass damper control approach for vibration reduction in a shear frame. The approach utilizes a combination of modified positive position feedback control law and model predictive controller to drive the tuned mass damper. The inner control loop compensates for low frequency vibrations and pre-stabilizes the structure, while the outer loop ensures constraint satisfaction and softens the control action. The proposed scheme significantly reduces control effort and can be easily applied to multi-story arrangements.
JOURNAL OF VIBRATION ENGINEERING & TECHNOLOGIES
(2023)
Article
Computer Science, Information Systems
Felipe Ramirez-Rasgado, Carlos-Manuel Astorga-Zaragoza, Omar Hernandez-Gonzalez, Maria-Eusebia Guerrero-Sanchez, Gloria-Lilia Osorio-Gordillo, Juan Reyes-Reyes
Summary: This article presents a novel observer synthesis for nonuniform observable uncertain nonlinear systems with sampled and disturbed delayed output. The proposed observer with a cascade structure improves the performance by continuously estimating the delayed state vector and reducing the convergence time. The observer's performance is evaluated by estimating the state of an uncertain chaotic system with delayed measurements under different scenarios.
IEEE SYSTEMS JOURNAL
(2022)
Article
Acoustics
Rene Galaz-Palma, Boubekeur Targui, Omar Hernandez-Gonzalez, Guillermo Valencia-Palomo, Adrian Espinoza-Molina, Maria-Eusebia Guerrero-Sanchez
Summary: This paper develops a robust observer for linear systems in building structures, which provides simultaneous estimation of displacements, velocities, and seismic force acceleration. The proposed observer helps reduce the displacements of building structure systems, and its convergence analysis is based on Lyapunov theory with a simple set of Linear Matrix Inequalities. An example of a two-story building-like structure demonstrates the effectiveness of the proposed observer.
JOURNAL OF VIBRATION AND CONTROL
(2022)
Article
Engineering, Aerospace
J. R. Montoya-Morales, M. E. Guerrero-Sanchez, G. Valencia-Palomo, O. Hernandez-Gonzalez, F. R. Lopez-Estrada, J. A. Hoyo-Montano
Summary: This paper focuses on the autonomous trajectory-tracking problem of a UAV using Sliding Mode Control algorithms. The control system stabilizes a commercial AR.Drone 2.0 quadrotor in real-time using monocular vision. The under-actuated mathematical model is based on the Newton-Euler formulation. The proposed controller shows effectiveness and robustness in experimental tests and numerical simulations.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING
(2023)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Fernando J. Ramirez-Coronel, Oscar M. Rodriguez-Elias, Madain Perez-Patricio, Edgard Esquer-Miranda, Julio Waissman-Vilanova, Mario I. Chacon-Murguia, Omar Hernandez-Gonzalez
Summary: A new methodology based on the chord length function is proposed to analyze the shape of shrimps and count them. This method generates histograms and statistical parameters that can be useful in identifying shrimps, estimating their sizes, and finding a relationship between morphometric measures and biomass.
RECENT TRENDS IN IMAGE PROCESSING AND PATTERN RECOGNITION, RTIP2R 2022
(2023)
Article
Automation & Control Systems
Xiaoyu Luo, Chengcheng Zhao, Chongrong Fang, Jianping He
Summary: This paper investigates the problem of false data injection attacks in multi-agent dynamical systems and proposes FDI attack set selection algorithms to maximize the convergence error by finding the optimal subset of compromised agents.
Article
Automation & Control Systems
Nitin K. Singh, Abhisek K. Behera
Summary: In this paper, a twisting observer is proposed for robustly estimating the states of a second-order uncertain system. The observer approximates the unknown sign term for the non-measurable state with a delayed output-based switching function, and achieves the desired steady-state accuracy by controlling the delay parameter. The application of the observer to output feedback stabilization is also discussed.
Article
Automation & Control Systems
Alexander Aleksandrov
Summary: This paper investigates the absolute stability problem for positive Persidskii systems with delay, proposes a special construction method for diagonal Lyapunov-Krasovskii functionals, and derives a criterion for the existence of such functionals guaranteeing the absolute stability, as well as obtaining sufficient conditions for a family of time-delay Persidskii systems to construct a common diagonal Lyapunov-Krasovskii functional. The efficiency of the developed approaches is demonstrated through four examples.
Article
Automation & Control Systems
Noureddine Toumi, Roland Malhame, Jerome Le Ny
Summary: This paper addresses large multi-agent dynamic discrete choice problems using a linear quadratic mean field games framework. The model incorporates the features where agents have to reach a predefined set of possible destinations within a fixed time frame and running costs can become negative to simulate crowd avoidance. An upper bound on the time horizon is derived to prevent agents from escaping to infinity in finite time. The existence of a Nash equilibrium for infinite population and its epsilon-Nash property for a large but finite population are established. Simulations are conducted to explore the model behavior in various scenarios.
Article
Automation & Control Systems
Philippe Schuchert, Vaibhav Gupta, Alireza Karimi
Summary: This paper presents the design of fixed-structure controllers for the As2 and Asw synthesis problem using frequency response data. The minimization of the norm of the transfer function between the exogenous inputs and performance outputs is approximated through a convex optimization problem involving Linear Matrix Inequalities (LMIs). A general controller parametrization is used for continuous and discrete-time controllers with matrix transfer function or state-space representation. Numerical results show that the proposed data-driven method achieves performance equivalent to model-based approaches when a parametric model is available.
Correction
Automation & Control Systems
Zhijun Guo, Gang Chen
Article
Automation & Control Systems
Matteo Della Rossa, Thiago Alves Lima, Marc Jungers, Raphael M. Jungers
Summary: This paper presents new stabilizability conditions for switched linear systems with arbitrary and uncontrollable underlying switching signals. The study focuses on two specific settings: the robust case with completely unknown and unobservable active mode, and the mode-dependent case with controller depending on the current active switching mode. The technical developments are based on graph-theory tools and path-complete Lyapunov functions framework, enabling the design of robust and mode-dependent piecewise linear state-feedback controllers using directed and labeled graphs.
Article
Automation & Control Systems
Elena Petri, Romain Postoyan, Daniele Astolfi, Dragan Nesic, W. P. M. H. (Maurice) Heemels
Summary: This study investigates a scenario where a perturbed nonlinear system transmits its output measurements to a remote observer via a packet-based communication network. By designing both the observer and the local transmission policies, accurate state estimates can be obtained while only sporadically using the communication network.
Article
Automation & Control Systems
Jonas Krook, Robi Malik, Sahar Mohajerani, Martin Fabian
Summary: This paper proposes a method to synthesise controllers for cyber-physical systems subjected to disturbances, such that the controlled system satisfies specifications given as linear temporal logic formulas. The approach constructs a finite-state abstraction of the original system and synthesises a controller for the abstraction. It introduces the robust stutter bisimulation relation to account for disturbances and uncertainty, ensuring that related states have similar effects under the same controller. The paper demonstrates that the existence of a controller for the abstracted system implies the existence of a controller for the original system enforcing the linear temporal logic formula.
Article
Automation & Control Systems
Clement Chahbazian, Karim Dahia, Nicolas Merlinge, Benedicte Winter-Bonnet, Aurelien Blanc, Christian Musso
Summary: The paper derives a recursive formula of the Fisher information matrix on Lie groups and applies it to nonlinear Gaussian systems on Lie groups for testing. The proposed recursive CRLB is consistent with state-of-the-art filters and exhibits representative behavior in estimation errors. This paper provides a simple method to recursively compute the minimal variance of an estimator on matrix Lie groups, which is fundamental for implementing robust algorithms.
Article
Automation & Control Systems
Yiheng Fu, Pouria Ramazi
Summary: This study investigates the characteristics of decision fluctuations in heterogeneous populations and explores the uncertainties in imitation behavior. The findings are important for understanding the bounded rationality nature of imitation behaviors.
Article
Automation & Control Systems
Lars A. L. Janssen, Bart Besselink, Rob H. B. Fey, Nathan van de Wouw
Summary: This paper introduces a mathematical relationship between the accuracy of reduced-order linear-time invariant subsystem models and the stability and accuracy of the resulting reduced-order interconnected linear time-invariant model. This result can be used to directly translate the accuracy characteristics of the reduced-order subsystem models to the accuracy properties of the interconnected reduced-order model, or to translate accuracy requirements on the interconnected system model to accuracy requirements on subsystem models.
Article
Automation & Control Systems
Piyush Gupta, Vaibhav Srivastava
Summary: We study the optimal fidelity selection for a human operator servicing tasks in a queue, considering the trade-off between high-quality service and penalty due to increased queue length. By modeling the operator's cognitive dynamics and task fidelity, we determine the optimal policy and value function numerically, and analyze the structural properties of the optimal fidelity policy.
Article
Automation & Control Systems
Lukas Schwenkel, Alexander Hadorn, Matthias A. Mueller, Frank Allgoewer
Summary: In this work, the authors study economic model predictive control (MPC) in periodic operating conditions. They propose a method to achieve optimality by multiplying the stage cost by a linear discount factor, which is easy to implement and robust against online changes. Under certain assumptions, they prove that the resulting linearly discounted economic MPC achieves optimal asymptotic average performance and guarantees practical asymptotic stability of the optimal periodic orbit.
Article
Automation & Control Systems
Taher Ebrahim, Sankaranarayanan Subramanian, Sebastian Engell
Summary: We propose a robust nonlinear model predictive control algorithm for dynamic systems with mixed degrees of freedom. This algorithm optimizes both continuous and discrete manipulated variables, enhancing closed-loop performance. Our approach relies on a computationally efficient relaxation and integrality restoration strategy and provides sufficient conditions to establish recursive feasibility and guarantee robust closed-loop stability. The effectiveness of the approach is demonstrated through two nonlinear simulation examples.
