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This study introduces a novel robust finite-time adaptive sliding mode control (FTSMC) strategy, emphasizing its contributions to the synchronized deployment of hydraulically actuated multi-arm systems in confined environments, such as coal bunker cleaning. Key innovations include the integration of adaptive sliding mode control with guaranteed finite-time convergence, a distributed leader–follower framework, and a graph-theoretical communication topology for localized interactions. Specifically, we developed a dynamic model for a multi-agent system comprising one leader and multiple followers, incorporating nonlinear dynamics and unknown external disturbances. The proposed controller ensures rapid finite-time convergence of tracking errors while maintaining robustness against parameter uncertainties, frictional forces, and external perturbations. The theoretical analysis, based on Lyapunov stability, rigorously proves the boundedness and convergence of all system states. Simulation results on a three-arm robotic platform validate the method’s superiority, demonstrating higher tracking accuracy, faster convergence, and stronger disturbance rejection compared with baseline controllers, including SMC, ETASMC, PID, Fixed-Time Consensus Control (FTCC), Disturbance Observer-Based Control (DOBC), and Adaptive Sliding Mode Control (ASMC). This research provides a practical and scalable solution for multi-arm coordination in unstructured environments, significantly advancing the autonomy and reliability of industrial robotic systems.

This research paper tackles the complexities of achieving global fuzzy consensus in leader-follower systems in robotic systems, focusing on robust control systems against an advanced signal attack that integrates sensor and actuator disturbances within the dynamics of follower robots. Each follower robot has unknown dynamics and control inputs, which expose it to the risks of both sensor and actuator attacks. The leader robot, described by a second-order, time-varying nonlinear model, transmits its position, velocity, and acceleration information to follower robots through a wireless connection. To handle the complex setup and communication among robots in the network, we design a robust hybrid distributed adaptive control strategy combining the effect of sensor and actuator attack, which ensures asymptotic consensus, extending beyond conventional bounded consensus results. The proposed framework employs fuzzy logic systems (FLSs) as proactive controllers to estimate unknown nonlinear behaviors, while also effectively managing sensor and actuator attacks, ensuring stable consensus among all agents. To counter the impact of the combined signal attack on follower dynamics, a specialized robust control mechanism is designed, sustaining system stability and performance under adversarial conditions. The efficiency of this control strategy is demonstrated through simulations conducted across two different directed communication topologies, underscoring the protocol’s adaptability, resilience, and effectiveness in maintaining global consensus under complex attack scenarios.

In this paper, the strong structural controllability of the leader-follower framework is discussed. Firstly, the authors analyze different edge augmentation methods to preserve the strong structural controllability of the path-bud topology. The following four cases are considered: Adding edges from the path to the bud; adding edges from the bud to the path; adding the reverse or forward edges to the path or bud; and adding both the reverse and forward edges to the path or bud. Then sufficient conditions are derived for the strong structural controllability of the new topologies which are generated by adding different edges. In addition, it is proved that rank[ A B ] = n is a necessary condition for the strong structural controllability. Finally, three examples are given to verify the effectiveness of the main results.

This paper addresses the difficulties with connected vehicle systems (CVSs), particularly with vehicle platooning, are examined in this paper. For leader and follower-connected vehicles, the control protocol (which includes artificial delays, disturbances and proportional gains) is implemented. With tracking error systems, system dynamics are modelled while taking outside influences into consideration. Using creative thinking, a centralized event-triggered control system is implemented to maximize fleet wide communication updates. System stability is guaranteed by this centralized method in combination with quadratic form Lyapunov stability analysis. The risk of zeno behaviour is reduced by an event-triggered communication condition that is activated when a threshold is exceeded. The effectiveness of the centralized event-triggered system in improving stability and resilience in connected vehicle platooning scenarios is evaluated numerically through simulations.

This paper presents an adaptive leader-follower formation control strategy for second-order nonlinear multi-agent systems with unknown dynamics. To handle system uncertainties, we used neural networks (NNs) to approximate and compensate for nonlinear effects. A key feature of our approach is its ability to deal with Byzantine attacks and time delays, which can disrupt coordination among agents. Unlike existing methods, our control strategy actively accounts for these challenges while ensuring stable formation tracking. Using Lyapunov stability theory, we proved that all system errors remain within a bounded range. Numerical simulations confirmed the effectiveness of our approach, showing that it successfully maintains formation control even in the presence of adversarial attacks and delays.

In this paper, we present a decentralized event-triggered control strategy designed for leader-follower vehicle systems dealing with input delays, disturbances, and combined sensor and actuator attacks. The primary objective is to achieve asymptotic consensus among vehicles while significantly reducing inter-agent communication and ensuring security against sensor and actuator attacks. This approach leverages local state estimates from neighbouring vehicles, updating them only when specific events are triggered. These events are governed by a decentralized stability-driven condition that ensures robust leader-follower consensus through intermittent communication. We also establish a definitive lower bound on the minimum inter-event interval, demonstrating its effectiveness in reducing communication overhead. Rigorous analysis confirms the strategy's ability to prevent Zeno behaviour under switched dynamics, while Lyapunov-based convergence analysis supports its capability to achieve stable leader-follower dynamics. Finally, simulation results highlight the strategy's effectiveness, showcasing its potential to enhance coordination and efficiency in dynamic vehicle environments.

In this paper, by using the concept of Conditional Value at Risk (CVaR), a Leader-Follower game (LFG) based multi-objective optimization model is developed to determine the optimum 12-month operation policy of a reservoir in potential future dry periods. The minimization of CVaRs of storage loss and agricultural and environmental deficits along with maximization of planned allocation to agricultural sector are considered as leader’s objectives, while the followers try to maximize their share of water rights using Nash bargaining (NB) method. This framework is then used to model the operation policy of Dorudzan basin in Fars province, southwestern Iran. Water demand and daily climate data in the period of 2003 to 2015 for this basin, as well as future projections from fifteen IPCC-AR4 global circulation models (GCMs) for 2018–2030 under A2, B1 and A1B emission scenarios are considered to evaluate future dam operation policies. Future projections are downscaled using the LARS-WG model, which then feeds the HMETS watershed model to simulate the corresponding reservoir inflow time-series. Thereafter, three-hundred 12-month rainfall, evaporation and inflow time series with least inflow volume are used as input for the optimization model, which is solved using NSGA-II and GA algorithms. The results show while the model can determine the operation policy that keeps the associated risks in the acceptable range, it can satisfy the followers demands with respect to the available resources. The results also show that the agricultural sector of the study area can be hugely affected by potential future droughts.

This paper presents a new leader-follower decision-making framework for the automatic assessment and comparison of different water resources management scenarios and selection of the best one. WEAP (Water Evaluation and Planning) model is used to simulate different management scenarios, which are reasonable from the viewpoint of the leader decision-maker, and evaluate the response of water users (followers). A number of management scenarios are developed for water pricing and allocation to followers in the agricultural, industrial, and fishery sectors. The results are evaluated by a novel sustainability index considering economic performance, water allocation efficiency, and social equity criteria. The economic performance is evaluated by two indices assessing the profit of the basin’s leader and followers. The efficiency of water allocation policies is analyzed by an index using the Evidential Reasoning approach. Social equity is inspected by an index evaluating the distribution of incomes among followers using the Gini coefficient concept. The Gorganrud-Qaresou basin in Iran is used as a case study to demonstrate the applicability and efficiency of the proposed framework and the sustainability index. Sustainable water allocation policies and water prices for agricultural, industrial, and fishery sectors in the basin are the main findings of this paper. The results show that current water tariffs are low, particularly for the agricultural sector, and it could lead to inefficient use of water by followers, which has been the case in many regions in Iran.

In this paper, we obtain an existence theorem of general strong noncooperative equilibrium point of vector-valued games, in which every player maximizes all goals. We also obtain an existence theorem of strong equilibrium point of vector-valued games with single-leader–multi-follower framework by using the upper semicontinuous of parametric strong noncooperative equilibrium point set of the followers. Moreover, we obtain some results on the generic stability of general strong noncooperative equilibrium point vector-valued games.