Article
Engineering, Electrical & Electronic
Jianheng Lin, Mei Su, Yao Sun, Dongsheng Yang, Shiming Xie
Summary: This article presents a recursive single-input single-output (SISO) impedance modeling framework for power-converter-based single-phase ac systems. The method greatly simplifies the modeling procedure and obtains accurate impedance models by extending the linear-time invariant modeling method and using mathematical induction.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2022)
Article
Automation & Control Systems
Wei Lin, Jiwei Sun
Summary: In this study, a semiglobal method without invoking the dynamic extension technique is proposed to prove the semiglobal asymptotic stabilizability of certain nonaffine systems with input delay in the single-input-single-output (SISO) case, using n-dimensional memoryless output feedback. A dynamic output compensator is constructed, consisting of an n-dimensional nonlinear observer and an observer-based controller, both with saturated states. As a result, an affine system in a lower triangular form with input delay is shown to be semiglobally asymptotically stabilizable via n-dimensional memoryless output feedback. These results address the open question of designing delay-free, n-dimensional semiglobal asymptotically stabilizable output feedback controllers for a significant class of SISO nonaffine systems raised in (Wang and Lin, 2022).
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Engineering, Electrical & Electronic
Xianfu Lin, Ruoxue Yu, Jingrong Yu, He Wen
Summary: In this paper, a SISO theory-based stability analysis method for weak grids with a three-phase grid-connected inverter is proposed in dq-frame and sequence domain, incorporating asymmetrical control. The paper presents decomposed models for MIMO systems and compares the proposed method with existing techniques. The proposed method enables separate design of asymmetrical control in the dq-frame and accurately identifies the system's frequency-coupled resonances in the sequence domain.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Energy & Fuels
Mengting Jiang, Michel Speetjens, Camilo Rindt, David Smeulders
Summary: This study develops a data-based compact model for predicting fluid temperature in district heating pipeline networks. The model, called reduced-order model (ROM), is obtained by reducing the energy conservation law for each pipe segment to an input-output relation between pipe temperatures, which can be determined from training data. The ROM is applicable to various pipe configurations involving 3D unsteady heat transfer and 3D steady flow as long as heat-transfer mechanisms are linearly dependent on temperature. The study demonstrates the successful identification and accurate prediction capability of the ROM using computational training data for both single-pipe configurations and realistic systems.
Article
Automation & Control Systems
Bruno M. C. Silva, Joao Y. Ishihara, Eduardo S. Tognetti
Summary: This work proposes new conditions for consensus of homogeneous multi-agent systems subjected to exogenous disturbances in directed communication graphs by dynamic output feedback protocols. The authors describe the agents as linear dynamics and consider communication networks where each agent only receives the output of its neighbors as information. They rewrite the synchronization problem as an output feedback stabilization problem without requiring the Laplacian matrix to be diagonalizable. The paper introduces new necessary and sufficient conditions for designing dynamic output feedback controllers of arbitrary order and provides sufficient Linear Matrix Inequalities (LMIs) for H infinity consensus. Numerical experiments demonstrate the effectiveness of the proposed approach.
Article
Computer Science, Artificial Intelligence
Senkui Lu, Xiang Li, Ke Lu, Zhengzhong Wang, Yujie Ma
Summary: This paper proposes an adaptive fuzzy control approach for addressing the control problem of incommensurate fractional-order MIMO systems with unknown nonlinearities and input saturation. By introducing fuzzy logic systems to identify the nonlinear terms of the system and using adaptive compensating control to estimate the approximation errors, the complexity explosion issue in typical backstepping is effectively solved through an improved command filter. The influence of filtered error is avoided by constructing error compensation laws, and the input saturation problem is addressed using fractional-order auxiliary equations.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Yan Zhang, Mohammed Chadli, Zhengrong Xiang
Summary: In this article, the adaptive fuzzy predefined-time tracking control problem for a class of nonlinear systems with output hysteresis is investigated. An inverse model is utilized to capture the output hysteresis phenomenon, and the Nussbaum-type function technique is utilized to overcome the difficulty of unknown time-varying control gain caused by output hysteresis. An adaptive fuzzy control scheme under the backstepping framework is developed using the predefined-time stability criterion. The feasibility of the developed scheme is verified by an example of an electromechanical system.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Environmental Sciences
Bo Lin, Yubing Yuan, Yicai Ji, Chao Li, Xiaojun Liu, Guangyou Fang
Summary: This article proposes a novel three-dimensional (3-D) imaging method based on the range decomposing algorithm (RDA) for millimeter wave imaging. The theoretical formulation of RDA applied to single-input-single-output (SISO)/multiple-input-multiple-output (MIMO) array is derived, and its computational complexity and computational error are analyzed. Compared to classical Fourier algorithms, the proposed algorithm offers a more efficient approach by replacing time-consuming operations with approximations and transformations, while maintaining image quality. Additionally, a method based on RDA is proposed to enhance the processing efficiency for the transformation between MIMO and SISO. Proof-of-principle simulation and experimental results demonstrate the higher efficiency and better reconstruction performance of the proposed algorithm.
Article
Engineering, Electrical & Electronic
Jingxi Yang, Chi K. Tse, Dong Liu
Summary: An islanded microgrid consisting of grid-forming converters exhibits rich nonlinear dynamical phenomena. Reduced-order models are capable of describing the system behavior without excessive computational resources, offering useful insights into the system dynamics.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2022)
Article
Automation & Control Systems
R. Almeida, S. Hristova, S. Dashkovskiy
Summary: In this study, the BIBO stability of a nonlinear Caputo fractional system with time-varying bounded delay and nonlinear output was investigated. New stability criteria were derived using the Razumikhin method, Lyapunov functions, and fractional derivatives of Lyapunov functions. The effectiveness of these theoretical results was demonstrated through numerical simulations of the system's dynamic response.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Automation & Control Systems
Ines Righi, Sabrina Aouaouda, Mohammed Chadli, Khaled Khelil
Summary: This article proposes a method for designing robust controller laws for a class of uncertain nonlinear parameter varying (NLPV) descriptor systems under input saturation and external disturbances. The stability conditions are derived using polytopic parameter-dependent (PD) nonquadratic Lyapunov functions and L2 gain performance is used to attenuate the effect of the external disturbance signals. The largest domain of attraction (DoA) for the system is estimated and solved as an optimization problem, demonstrating the effectiveness of the proposed design methods through two examples.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Engineering, Mechanical
William Anderson, Mohammad Farazmand
Summary: This study investigates the reduced-order modeling of nonlinear dispersive waves described by nonlinear Schrodinger (NLS) equations. Two nonlinear reduced-order modeling methods are compared: the reduced Lagrangian approach based on the variational formulation of NLS, and the recently developed method of reduced-order nonlinear solutions (RONS). The surprising result is that, despite their apparent differences, these two methods can be obtained from the real and imaginary parts of a single complex-valued master equation. The study also reveals that the reduced Lagrangian method fails to predict the correct group velocity of waves in the NLS equation, while RONS accurately predicts the correct group velocity.
NONLINEAR DYNAMICS
(2022)
Article
Mathematics, Applied
Bulent Karasozen, Gulden Mulayim, Murat Uzunca, Suleyman Yildiz
Summary: In this study, reduced-order models (ROMs) were developed for a nonlinear cross-diffusion problem involving the SKT equation with Lotka-Volterra kinetics. By separating time into two intervals, more accurate reduced-order solutions were computed, outperforming global proper orthogonal decomposition solutions. The use of proper orthogonal decomposition in a tensorial framework accelerated the computation of reduced-order solutions independently of full-order solutions, showing prediction capabilities for one- and two-dimensional patterns. Additionally, the decrease in entropy by the reduced solutions played a crucial role in ensuring the global existence of solutions for nonlinear cross-diffusion equations like the SKT equation.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Acoustics
Majid Shahbazzadeh, Homa Salehifar, S. Jalil Sadati
Summary: This study investigates the problem of optimal guaranteed cost control for nonlinear systems under input saturation. The goal is to design a dynamic output feedback controller that ensures asymptotic stability of the closed-loop system and minimizes the upper bound of the cost function. The designed controller also guarantees that the control signals stay within their permissible range. The paper formulates the problem as an optimization problem with bilinear matrix inequality constraints, which are converted into linear matrix inequality conditions using technical lemmas. Simulation results demonstrate the effectiveness and advantages of the proposed theoretical results.
JOURNAL OF VIBRATION AND CONTROL
(2023)
Article
Engineering, Mechanical
Shanwu Li, Yongchao Yang
Summary: This study presents a hierarchical deep learning approach to identify reduced-order models of nonlinear dynamical systems from measurement data only, including nonlinear normal modal subspace and associated dynamics. The approach is validated on unforced and forced nonlinear systems, demonstrating efficient dimensional truncation for optimal low-dimensional ROM. Performance and applicability of this approach are discussed in detail.
NONLINEAR DYNAMICS
(2021)
Article
Automation & Control Systems
Mario Sassano, Thulasi Mylvaganam, Alessandro Astolfi
Summary: The study investigates open-loop Nash equilibrium strategies for differential games described by nonlinear, input-affine systems with quadratic cost functionals. The computation of such strategies relies on solving a system of nonlinear, time-varying partial differential equations, leading to feedback synthesis of the underlying open-loop strategy.
Article
Automation & Control Systems
Mario Sassano, Thulasi Mylvaganam, Alessandro Astolfi
Summary: This article investigates optimal control problems for continuous-time systems with time-dependent dynamics, focusing on nonlinear input-affine systems. The results show that while not all features from the linear case are preserved in the nonlinear setting, several structural claims can still be proven.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Computer Science, Artificial Intelligence
A. G. Giannari, A. Astolfi
Summary: We propose a novel modular, scalable and adaptable modelling framework for accurately modelling neuronal networks with different dynamic properties and firing patterns. By separating the neuronal dynamics from the network dynamics, we have developed a flexible feedback structure and verified its accuracy, flexibility and scalability.
Article
Automation & Control Systems
Alexey Bobtsov, Bowen Yi, Romeo Ortega, Alessandro Astolfi
Summary: This paper addresses the problem of estimating constant parameters from a standard vector linear regression equation in the absence of sufficient excitation in the regressor. It proposes transforming the equation into a set of scalar ones and generating new scalar exciting regressors. The superior performance of a classical gradient estimator using the new regressor is illustrated through comprehensive simulations.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Automation & Control Systems
Enrico Franco, Alessandro Astolfi
Summary: Energy shaping is an effective control strategy, but current research often neglects actuator dynamics, which may impact the performance of fluidic actuators. This paper presents a new energy shaping control method that considers the pressure dynamics of an ideal fluid, and validates it through numerical simulations.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Automation & Control Systems
Ali Ahmadi Dastjerdi, Alessandro Astolfi, Niranjan Saikumar, Nima Karbasizadeh, Duarte Valerio, S. Hassan HosseinNia
Summary: This article presents a closed-loop frequency analysis tool for reset control systems. It provides sufficient conditions for the existence of steady-state response and shows that the steady-state response for periodic inputs is periodic with the same period as the input. The framework presented in this article allows for the computation of steady-state response and defines a notion of closed-loop frequency response, including high order harmonics.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Mario Sassano, Thulasi Mylvaganam, Alessandro Astolfi
Summary: This paper studies the infinite-horizon optimal control problem for nonlinear systems. In the context of model-based, iterative learning strategies, the authors propose an alternative definition and construction of the temporal difference error in policy iteration strategies. The error is obtained through two subsequent steps: steering the dynamics of the costate variable in the Hamiltonian system to make the stable invariant manifold externally attractive, and then measuring the distance-from-invariance of the manifold for policy evaluation. The theory is validated through a numerical simulation involving an automatic flight control problem.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Enrico Franco, Alessandro Astolfi
Summary: In this work, we propose a new energy shaping control method for underactuated mechanical systems with high-order actuator dynamics. We extend the Interconnection and damping assignment Passivity based control methodology to account for actuator dynamics. This brings two alternative controllers based on potential and kinetic energy shaping and damping assignment, as well as a potential energy shaping and damping assignment for a narrower class of underactuated mechanical systems. Numerical simulations on three examples demonstrate the effectiveness of the proposed approach.
EUROPEAN JOURNAL OF CONTROL
(2023)
Article
Automation & Control Systems
Adnan Tahirovic, Alessandro Astolfi
Summary: We propose a novel strategy for constructing optimal controllers for continuous-time nonlinear systems using linear-like techniques. Instead of solving the difficult or impossible nonlinear partial differential equation, the strategy replaces it with an easy solvable state-dependent Lyapunov matrix equation. By exploiting linear-like factorization and policy-iteration algorithm, the control strategy solves optimal nonlinear control problems in a linear-like manner and proves the optimality of the resulting solution.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Proceedings Paper
Energy & Fuels
Mingxuan Mao, Alcssandro Astolfi
Summary: This paper proposes an innovative solution based on PMP for the day-ahead optimal dynamic economic dispatch problem. Numerical simulations demonstrate the effectiveness and competitiveness of the proposed method.
2023 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, PESGM
(2023)
Proceedings Paper
Automation & Control Systems
Joel D. Simard, Alessandro Astolfi
Summary: This article considers the Loewner functions associated with four behaviorally equivalent differential-algebraic systems in order to simplify the partial differential equation defining the tangential generalized observability function. Although the systems may have different tangential generalized observability functions, it is shown that all four systems yield the exact same family of Loewner equivalent interpolants provided that solutions to the PDEs exist.
2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC)
(2022)
Proceedings Paper
Automation & Control Systems
Lorenzo Tarantino, Mario Sassano, Sergio Galeani, Alessandro Astolfi
Summary: This paper studies a class of nonlinear finite-horizon optimal control problems and proposes a solution based on an iterative strategy that linearizes the nonlinear dynamics and constructs the corresponding time-varying Hamiltonian dynamics. Unlike existing methods, this strategy relies on the solution to a linear initial value problem and does not require the numerical solution of a two-point boundary value problem or a time-varying Riccati equation.
2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC)
(2022)
Proceedings Paper
Automation & Control Systems
Kaiwen Chen, Alessandro Astolfi, Thomas Parisini
Summary: This paper presents a decentralized adaptive control scheme for cyber-physical systems under sensor and coordinated actuator attacks. It proposes partially adaptive and fully adaptive controllers to ensure boundedness and convergence properties of the system.
2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC)
(2022)
Proceedings Paper
Automation & Control Systems
Jianli Gao, Balarko Chaudhuri, Alessandro Astolfi
Summary: The paper presents an analytical control solution for the transient stabilization problem in lossy multi-machine power systems. A new form of control Lyapunov function candidates with a flexible potential-energy-like term is proposed by introducing an auxiliary state that contributes to the derivation of a cross-term. A new control law based on the Lyapunov function candidates is proposed to ensure the asymptotic stability of the desired closed-loop operating equilibrium. The effectiveness of the proposed control solution is demonstrated through a case study on a two-machine system model.
2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC)
(2022)
Proceedings Paper
Automation & Control Systems
Joel D. Simard, Alessandro Astolfi
Summary: This study presents an approach to regularize underconstrained interpolants in the Loewner framework for nonlinear descriptor systems. By constructing a family of systems that preserve the property of Loewner equivalence, it is shown that a subfamily of wellposed interpolants exists if the Loewner function is surjective.
2022 EUROPEAN CONTROL CONFERENCE (ECC)
(2022)
