Output Regulation Research Articles

Epigenetic silencing of miR-125a-3p promotes the progress of human cholangiocarcinoma via increasing CAC1 expression

We aimed to investigate the dysregulation of the microRNAs(miRNAs) in cholangiocarcinoma (CCA), including its impact on the homeostasis of the transcriptome and cellular behavior. MiRNAs serve as potent epigenetic regulators of transcriptional output, targeting various signaling pathways. This study aimed to investigate the expression level, epigenetic mechanism and function of miR-125a-3 in CCA. The study data showed that the expression level of miR125a-3p was decreased in CCA tissue samples and cell lines, and it was closely related to lymph node metastasis, tissue differentiation and TNM stage. The data demonstrate a strong association between decreased miR-125a-3p expression and poorer prognosis in cholangiocarcinoma patients. miR-125a-3p acts as a tumor suppressor by inhibiting the viability, migration and invasion of CCA cells. There are CpG islands in the promoter region of miR-125a-3p gene, and the methylation of the promoter region of miR-125a-3p gene leads to the transcriptional repression of miR-125a-3p. In addition, miR125a-3p can target and regulate CAC1 mRNA and protein expression in the downstream mechanism, and the high expression of CAC1 can promote the proliferation, migration and invasion of cholangiocarcinoma cells. These data demonstrate that miR-125a-3p promoter methylation leads to silencing of its expression. Mechanically, miR-125a-3p acts as a tumor suppressor and participates in the occurrence and development of CCA through targeting CAC1 gene expression. Therefore, miR-125a-3p may serve as a new target for the diagnosis, prognostic assessment or molecular therapy of CCA.

Fuzzy Cooperative Output Regulation for Open Nonlinear Multiagent Systems

Fuzzy Cooperative Output Regulation for Open Nonlinear Multiagent Systems

Robust Output Regulation of a Class of Minimum-Phase Linear Uncertain Systems by Event-Triggered Control

Robust Output Regulation of a Class of Minimum-Phase Linear Uncertain Systems by Event-Triggered Control

Quantized cooperative output regulation of continuous-time multi-agent systems over switching graph

Quantized cooperative output regulation of continuous-time multi-agent systems over switching graph

Smart optimization in battery energy storage systems: An overview

The increasing drive towards eco-friendly environment motivates the generation of energy from renewable energy sources (RESs). The rising share of RESs in power generation poses potential challenges, including uncertainties in generation output, frequency fluctuations, and insufficient voltage regulation capabilities. As a solution to these challenges, energy storage systems (ESSs) play a crucial role in storing and releasing power as needed. Battery energy storage systems (BESSs) provide significant potential to maximize the energy efficiency of a distribution network and the benefits of different stakeholders. This can be achieved through optimizing placement, sizing, charge/discharge scheduling, and control, all of which contribute to enhancing the overall performance of the network. In this paper, we provide a comprehensive overview of BESS operation, optimization, and modeling in different applications, and how mathematical and artificial intelligence (AI)-based optimization techniques contribute to BESS charging and discharging scheduling. We also discuss some potential future opportunities and challenges of the BESS operation, AI in BESSs, and how emerging technologies, such as internet of things, AI, and big data impact the development of BESSs.

A Blocking Method for Overload-Dominant Cascading Failures in Power Grid Based on Source and Load Collaborative Regulation

Adjusting generator output and cutting off load can effectively solve the problem of continuous overload and disconnection of power lines caused by power flow transfer. To suppress large-scale power outages caused by overload-dominant cascading failures, a blocking method for overload-dominant cascading failures in the power grid based on source and load collaborative regulation is proposed. The shortest path algorithm was used to identify loads and generators with shorter electrical distances from overloaded lines. Under the premise of meeting the static safety constraints of the power grid, considering the regulation of generator output and the removal of interruptible loads, a multiobjective cascading failure blocking model is established with the minimum overall control cost of the system and the minimum probability coefficient of line failure. Use the NSGA-II algorithm to solve the model and obtain the optimal plan for adjusting generator output and cutting off load. Through example verification, the proposed method can effectively alleviate the phenomenon of line overload, thereby blocking the continuation of overload-dominant cascading failures.

Concurrent Learning Robust Adaptive Fault Tolerant Boundary Regulation of Hyperbolic Distributed Parameter Systems.

This article develops a robust adaptive boundary output regulation approach for a class of complex anticollocated hyperbolic partial differential equations subjected to multiplicative unknown faults in both the boundary sensor and actuator. The regulator design is based on the internal model principle, which amounts to stabilize a coupled cascade system, which consists of a finite-dimensional internal model driven by a hyperbolic distributed parameter system (DPS). To this end, a systematic sliding mode equipped with a backstepping approach is developed such that the robust state feedback control can be realized. Moreover, since the available information is a faulty boundary measurement at the right side point, state estimation is required. However, due to the presence of boundary unknown faults, we need to solve an issue of joint fault-state estimation. Restrictive persistent excitation conditions are usually required to guarantee the exact estimation of faults but are unrealistic in practice. To this end, a novel concurrent learning (CL) adaptive observer is proposed so that exponential convergence is obtained. It is the first time that the spirit of CL is introduced to the field of DPSs. Consequently, the observer-based adaptive boundary fault tolerant control scheme is developed, and rigorous theoretical analysis is given such that the exponential output regulation can be achieved. Finally, the effectiveness of the proposed methodology is demonstrated via comparative simulations.

Resilient Output Containment Control of Heterogeneous Multiagent Systems Against Composite Attacks: A Digital Twin Approach.

This article delves into the distributed resilient output containment control of heterogeneous multiagent systems against composite attacks, including Denial-of-Service (DoS) attacks, false-data injection (FDI) attacks, camouflage attacks, and actuation attacks. Inspired by digital twin technology, a twin layer (TL) with higher security and privacy is employed to decouple the above problem into two tasks: 1) defense protocols against DoS attacks on TL and 2) defense protocols against actuation attacks on the cyber-physical layer (CPL). Initially, considering modeling errors of leader dynamics, distributed observers are introduced to reconstruct the leader dynamics for each follower on TL under DoS attacks. Subsequently, distributed estimators are utilized to estimate follower states based on the reconstructed leader dynamics on the TL. Then, decentralized solvers are designed to calculate the output regulator equations on CPL by using the reconstructed leader dynamics. Simultaneously, decentralized adaptive attack-resilient control schemes are proposed to resist unbounded actuation attacks on the CPL. Furthermore, the aforementioned control protocols are applied to demonstrate that the followers can achieve uniformly ultimately bounded (UUB) convergence, with the upper bound of the UUB convergence being explicitly determined. Finally, we present a simulation example and an experiment to show the effectiveness of the proposed control scheme.

Fully Data-Driven Robust Output Formation Tracking Control for Heterogeneous Multiagent System With Multiple Leaders and Actuator Faults.

This article investigates a fully data-driven method to solve the robust output formation tracking control problem for the multiagent system (MAS) under actuator faults. The outputs of the followers are controlled to track those of multiple leaders with respect to a convex point while achieving an expected time-varying formation. To obviate the requirement of various system prior knowledge in typical MAS control, a hierarchical frame is developed with three learning and control stages using the online measured data. First, a distributed adaptive observer is designed to coordinate the state convex of multiple leaders while estimating unknown dynamics. The adaptive mechanism relaxes the demand for global topology. Second, by collecting and reusing the online system data, an off-policy reinforcement learning (RL) method is proposed in a continuous form to acquire nominal feedback gains from partial observations of the followers. Essential system models are learned along with the RL process, while solutions to the output regulation equations are implicitly obtained. Third, a comprehensive robust controller is further presented based on the previous learning results. To address the actuator faults with efficiency loss and bias, the adaptive neural networks and robust compensations are utilized in a model-free manner. The output formation tracking is achieved under a derived feasibility condition while stabilities of the learning and control methods are analyzed. Finally, simulation results demonstrate the validity of this fully data-driven control frame.

Preface

Hosted by Nanjing Tech University, China, the 2023 2nd International Conference on Aerospace and Control Engineering (ICoACE 2023) was held from 15th to 17th December 2023 in Nanjing, China. With ICoACE 2023, the conference series International Conference on Aerospace and Control Engineering (ICoACE) completed its second edition.The general topics of ICoACE 2023 fall into mainly four categories: 1) Aerospace Materials; 2) Aerospace Science and Technology; 3) Control Engineering; 4) Aerospace and Mechanics. Apart from the general topics, ICoACE 2023 attracted a number of papers related to aerospace and control engineering. Topics at the Conference include but are not limited to: Materials Failure Analysis and Prediction Prevention, Spacecraft Thermal Control Technology, Aerospace Computing, Combustion and Energy Conversion, Electric Automation, Drive Motor and Control Technology, etc.All papers were exhaustively reviewed by program committee members and peer-reviewers, who took into account the breadth and depth of the research topics that fall under the scope of ICoACE. The most promising and ICoACE mainstream-relevant contributions were selected from all the submissions for presentation and inclusion in this volume, which presents innovative original ideas or results of general significance supported by clear and rigorous reasoning and compelling new evidence, as well as methods.The Conference included three days of technical parts consisting mainly of keynote speeches, oral presentations, poster presentations and academic discussion. We were delighted and honored to invite Prof. Yan Wang (Nanjing University of Aeronautics and Astronautics, China), Prof. Mouquan Shen (Nanjing Tech University, China), and Prof. Wenfeng Hu (Central South University, China) to share their insightful ideas and mind-blowing researches as keynote speakers. Based on the research The Cooperative Control of Multi-Agent Systems with High Comprehensive Performance, Prof. Wenfeng Hu first introduced the event-triggered control strategies for multi-agent systems to reduce the communication burden among agents and talked about the brought challenging issues. Then, he addressed the consensus of homogeneous multi-agent systems and cooperative output regulation of heterogeneous multi-agent systems with event-triggering communication. Moreover, he presented the developed reset control strategies for multi-agent systems with second-order dynamics. Finally, an outlook on the new topics and trend for the cooperative control of networked control systems theory and techniques were given.We would like to thank all the keynote speakers, authors, program committee members and anonymous reviewers for their efforts in making ICoACE 2023 a Conference of the highest standard. We are also grateful to Journal of Physics: Conference Series, for its help in publishing this Proceedings of the Conference.The Committee of ICoACE 2023List of Committee Member is available in this pdf.

Output Regulation for a Wave Equation With Unknown Exosystem

Output Regulation for a Wave Equation With Unknown Exosystem

Optical Parametric Amplification in Crossed Fabry‐Perot Cavities

AbstractOptical parametric amplification (OPA) is a promising method of producing extremely intense light. A new OPA scheme with comprehensively high performance is urgently required for future development. In this study, an amplification scheme known as crossed‐Fabry‐Perot‐cavity OPA (XOPA) is proposed. It is based on the principle of periodic idler elimination, which prevents energy back‐conversion among the three coupling waves, resulting in a monotonically increasing overall conversion efficiency. Using a signal at 808 nm and a pump at 532 nm, a chirped pulse XOPA is experimentally demonstrated with a conversion efficiency of 56.28% and a gain bandwidth of 120 nm. The measured pulse duration after compression is 19.2 fs, which is comparable to the Fourier‐transform‐limited 16.8 fs. Further investigations revealed several advantages. Stable pulse shaping in spatial, temporal, and frequency domains is realized by a spatiotemporally modulated pump. Pulse contrast adjustability on the front edge of the signal is verified in the XOPA of different Fabry‐Perot cavity lengths. These results indicate astringency and precise regulation of output in nonlinear processes. Considering numerous crystals suitable for noncollinear configurations from the near‐infrared to mid‐infrared regions, XOPA has a universal potential application in laser systems with extreme intensity, few‐cycle duration, and internal confinement fusion drivers.

Adaptive optimal tracking control of networked linear systems under two-channel stochastic dropouts

This work investigates the adaptive optimal tracking control problem for networked discrete-time linear systems by directly using the data transmitted via communication networks. It is shown that the concerned problem can be addressed by solving two sub-problems: an adaptive optimal control one and an adaptive output regulation one. Two novel online reinforcement learning based policy iteration and value iteration algorithms are developed, which constitute an integrated framework to learn the optimal feedback control gain and the solutions to regulator equations by directly using the data transmitted via communication networks. Furthermore, it is shown that the tracking error of the closed-loop control system is mean square asymptotically stable even in the case of network packet stochastic dropouts. Simulation results demonstrate the efficacy of the proposed approaches.

Fixed-time cooperative output regulation for second-order nonlinear multiagent systems with an unknown exosystem

This paper investigates the fixed-time cooperative output regulation (FTCOR) problem with unknown exosystem of second-order nonlinear multiagent systems. To solve this problem, it is necessary to ensure that each agent can obtain the reference trajectory originating from an unknown exosystem and reconstruct the solution of the regulator equation containing the exogenous signal and unknown parameter vectors within a fixed time, and the unknown exosystem makes it difficult to solve these two problems with existing tools. By using auxiliary filtering variables, we propose a fixed-time adaptive distributed observer (FTADO) and design a fixed-time distributed internal model (FTDIM) based on this FTADO. These two new tools ensure the solvability of the two problems just mentioned. Then, based on these two tools, we transform the problem into a fixed-time stabilization problem of a so-called augmented system. Through the backstepping technique, we propose a distributed controller that solves this fixed-time stabilization problem while relaxing the assumptions of similar references.

Adaptive bipartite output containment control of heterogeneous multi‐agent systems against FDI attacks

AbstractThis paper researches the adaptive bipartite output containment control of heterogeneous multi‐agent systems (HMASs) against false data injection (FDI) attacks. The malicious adversaries could inject attacks on the actuator to maximize damage to the HMASs, which in turn causes the compromised followers to be unable to track the output states of the leaders. To address this issue, a resilient layer is introduced that prevents attack signals from affecting the states. Moreover, an adaptive compensator is ingeniously devised to counteract these attacks, thereby ensuring that both cooperative and antagonistic agents adhere to distinct convex hulls. Leveraging the output regulation approach, conducting Lyapunov stability analysis, and drawing upon other pertinent methodologies, we have systematically constructed a robust framework for the realization of bipartite output containment control. Ultimately, the validity of the analytical findings is confirmed through a series of rigorous numerical simulations.

Event‐triggered cooperative robust output regulation of minimum‐phase linear uncertain multi‐agent systems

AbstractIn this article, we investigate the event‐triggered cooperative robust output regulation problem of a class of minimum‐phase linear uncertain multi‐agent systems. In particular, we first propose a dynamic event‐triggered mechanism and an event‐triggered distributed output feedback control law. Then, by the internal model, the event‐triggered cooperative robust output regulation problem is converted into the event‐triggered cooperative robust stabilization problem of an augmented system composed of the distributed internal model and the original multi‐agent system. Next, we show that the event‐triggered cooperative robust stabilization problem can be solved by the proposed event‐triggered distributed output feedback control law together with a dynamic event‐triggered mechanism, and thus the event‐triggered cooperative robust output regulation problem is solved exactly in the sense that the tracking error of each subsystem converges to zero asymptotically while preventing the Zeno behavior from happening. Finally, we provide an example to illustrate the proposed control approach.

Robust output regulation of a class of uncertain nonlinear minimum phase systems perturbed by unknown external disturbances

This paper addresses the problem of robust output regulation for uncertain nonlinear minimum phase systems affected by an unknown external disturbance. We present a novel unknown input observer (UIO)-embedded high-gain stabilizer to completely reconstruct the disturbance in a finite time. A new saturation function is introduced to prevent finite time escape of the closed-loop trajectories. This allows us to achieve a semi-globally exponential regulation of the regulated output. The proposed method features the exact cancellation rather than approximate cancellation, for both structured and/or unstructured external disturbance. The presented controller is finite-dimensional and does not require the nominal model of the plant. Finally, a numerical experiment is conducted to demonstrate the effectiveness of the proposed method.

Active disturbance rejection control approach to the output tracking of PDEs with general disturbances: A new perspective

In recent years, significant progress has been made in output regulation for systems described by partial differential equations (PDEs) through the active disturbance rejection control approach (ADRC). However, in all these studies, the disturbance typically manifests in a single channel and requires estimation, often necessitating additional measured signals. This is because the disturbance must be identified through the output. In this paper, we approach this problem from a novel perspective: disturbances occur in all channels, yet few measured signals are required. In most cases, only the tracking error is utilized as the measured signal. This marks a significant advancement in the application of ADRC to PDEs. We primarily demonstrate this approach by addressing the output tracking problem for a multi-dimensional heat equation, considering general disturbances across all possible channels. Additionally, we briefly discuss some other one-dimensional problems studied in the literature, such as the one-dimensional wave equation.

Improved Event-Triggered Prescribed-Time Cooperative Output Regulation for Nonlinear Multiagent Systems

Improved Event-Triggered Prescribed-Time Cooperative Output Regulation for Nonlinear Multiagent Systems

Finite-Time Time-Varying Formation Tracking for Heterogeneous Nonlinear Multiagent Systems Using Adaptive Output Regulation.

The finite-time output time-varying formation tracking (TVFT) problem for heterogeneous nonlinear multiagent system (MAS) is investigated in this article, where the dynamics of the agents can be nonidentical, and leader's input is unknown. The target of this article is that the outputs of followers need to track leader's output and realize the desired formation in finite time. First, for removing the assumption that all agents are required to know the information of leader's system matrices and the upper boundary of its unknown control input in previous studies, a kind of finite-time observer is constructed by exploiting the neighboring information, which can estimate not only the leader's state and system matrices but also can compensate for the effects of unknown input. On the basis of the developed finite-time observers and adaptive output regulation method, a novel finite-time distributed output TVFT controller is proposed with the help of the technique of coordinate transformation by introducing an extra variable, which removes the assumption that the generalized inverse matrix of follows' input matrix needs to be found in the existing results. By means of the Lyapunov and finite-time stability theory, it is proven that the expected finite-time output TVFT can be realized by the considered heterogeneous nonlinear MASs within a finite time. Finally, simulation results demonstrate the efficacy of the proposed approach.