IET Control Theory and Applications最新文献

A platoon must ensure the security of conducting missions due to the susceptibility of the vehicles to cyber-attacks. The deception attack is a common type of cyber-attack that might be introduced during data exchange through communication channels. Therefore, it can divert each vehicle by injecting uncertainty into the communication link between the agents in the cyber domain. This paper employs a leader–follower consensus system as a reference model to control the platoon vehicles. Accordingly, each agent in the reference model sends its information as a reference trajectory to its corresponding vehicle within the platoon. The vehicles are equipped with a robust local controller, enabling them to follow their desired trajectory in the presence of external disturbances. Furthermore, each vehicle employs an unknown input observer to detect a deception attack while decoupling it from external disturbances. Moreover, by introducing a switching strategy based on mode-dependent average dwell time to the leader–follower consensus system, a novel resilient control strategy against the deception attack is implemented in the cyber domain. The resultant resilient leader–follower consensus system in the platoon retrieves and restores the attacked vehicle in the platoon to its associated states. The applicability of the proposed method is shown via simulation.

This article addresses the challenge of adaptive neural-based asynchronous control for nonhomogeneous Markov jumping systems with input dead zones. Time-varying transition probabilities are precisely characterized using a two-layer nonhomogeneous Markov process. A hidden Markov model is employed to detect system modes and resolve the asynchronous issues of controllers. Based on the detected modes and a neural network strategy, an adaptive asynchronous control strategy is proposed. The Lyapunov stability theory is used to prove that the system remains probabilistically bounded under this control law. Finally, the effectiveness of the control strategy is demonstrated through a simulation example.

This paper addresses the issue of observer-based proportional–integral–derivative control for Takagi–Sugeno fuzzy dynamic systems using a memory triggering protocol. To tackle the challenges of managing nonlinear systems, the Takagi–Sugeno fuzzy approach is employed to approximate these systems with a series of local linear models. A novel memory event-triggering mechanism is introduced, utilizing a computer's storage unit to store historical data and adjust the triggering threshold based on this data, thereby reducing unnecessary network resource usage. Given that the system state can be affected by external disturbances and become unpredictable, an observer-based proportional–integral–derivative controller is designed to manage these uncertainties. Finally, a car-damper-spring model is presented to validate the proposed methodology.

This article investigates the state geometric adjustability for interval max-plus linear systems, which means that the state vector sequence is transformed into a geometric vector sequence by using the state feedback control. It is pointed out that the geometric state vector sequence and its common ratio are closely related to the eigenvectors and eigenvalues of the special interval state matrix, respectively. Such an interval state matrix is determined by the eigen-robust interval matrix, which has a universal eigenvector relative to a universal eigenvalue. The state geometric adjustability is characterized by the solvability of interval max-plus linear equations, and a necessary and sufficient condition for the adjustability is given. A polynomial algorithm is provided to find the state feedback matrix. Several numerical examples and simulations are presented to demonstrate the results. At the same time, the proposed method is applied for the regulation of battery energy storage systems to optimize the start time of executing tasks for all processing units in each activity.

The command and control (C2) network is a complete organizational system that connects operational units at all levels based on command relationships. Its purpose is to ensure that the C2 system can fully perform its command functions, achieving high precision and efficiency in decision-making. As warfare models evolve rapidly from network-centric warfare to multi-domain operations, traditional C2 networks, which utilize a tree structure for connectivity, exhibit only a single hierarchical relationship, making it challenging for different operational units at the same level to interconnect. Furthermore, with the diversification of warfare, the three types of nodes in traditional C2 network models are insufficient to encompass all operational units. In response, this paper proposes a method for edge weighting in C2 networks based on a combination of node attributes and network attributes described by complex network theory. The node attributes mainly include node information transmission capacity, task coordination ability between nodes, node distance, and response time. The network attributes are primarily represented by hierarchy and betweenness centrality. Additionally, the traditional C2 network model's three types of nodes are expanded to five types of nodes. Based on the edge weighting method, internal command edges, inter-network collaborative edges, and cross-level command edges are generated within the C2 network. Simulation results demonstrate that the constructed C2 network model's characteristic parameters are superior to those of traditional C2 networks and collaborative C2 networks. This improvement enhances command and coordination abilities, aligns more closely with real-world scenarios, and effectively improves network command and control efficiency.

In this study, a high robust control—second-order sliding-mode control (SOSMC) scheme is proposed to improve the DC-link voltage dynamic performance of the grid-side converter (GSC) for the doubly-fed induction generator (DFIG) system under the wind turbine power disturbance and DC-link capacitance parameter disturbance. In general, the wind speed is change with the environment and further has an effect on the power generation of the DFIG system. Besides, the capacitance of DC-link capacitor may change with the working condition. To address this issue, a SOSMC scheme is proposed to replace the conventional proportional integral (PI) control for the DC-link voltage controller of the GSC for the DFIG system in this study. By using the non-linear SOSMC controller, the DFIG system is robust to the disturbance of the wind speed and the parameter of DC-link capacitance. Compared with the conventional PI control scheme, the DFIG system with the proposed SOSMC scheme is much more robust, which has been verified in the MATLAB/Simulink platform.

During aircraft operations, pilots rely on human-machine interaction platforms to access essential information services. However, the development of a highly usable aerial assistant necessitates the incorporation of two interaction modes: active-command and passive-response modes, along with three input modes: voice inputs, situation inputs, and plan inputs. This research focuses on the design of an aircraft human-machine interaction assistant (AHMIA), which serves as a multimodal data processing and application framework for human-to-machine interaction in a fully voice-controlled manner. For the voice mode, a finetuned FunASR model is employed, leveraging private aeronautical datasets to enable specific aeronautical speech recognition. For the situation mode, a hierarchical situation events extraction model is proposed, facilitating the utilization of high-level situational features. For the plan mode, a multi-formations double-code network plan diagram with a timeline is utilized to effectively represent plan information. Notably, to bridge the gap between human language and machine language, a hierarchical knowledge engine named process-event-condition-order-skill (PECOS) is introduced. PECOS provides three distinct products: the PECOS model, the PECOS state chart, and the PECOS knowledge description. Simulation results within the air confrontation scenario demonstrate that AHMIA enables active-command and passive-response interactions with pilots, thereby enhancing the overall interaction modality.

This article presents an innovative approach for distinguishing replay attacks from faults in hybrid systems. To develop the idea at first, a novel technique for replay attack detection, which differentiates it from typical system faults, is introduced. This is achieved through a tactical combination of stochastic coding and a window-based comparison mechanism, setting a new standard in hybrid system security. In the realm of fault detection, robust L₂-L_∞ adaptive observers are employed for precise mode detection, allowing for an accurate assessment of the system's operational state. Additionally, robust H_∞ Sliding Mode Observers are utilized to identify abnormal behaviours in the system's output, further solidifying the fault detection capabilities. A significant enhancement in the proposed approach is the integration of a Luenberger observer with the Butterworth low-pass filter. This novel addition not only refines the filtering process but also contributes to the overall reliability and accuracy of the system. The efficiency and versatility of these methods are demonstrated through their application to a four-tank hybrid system. This practical simulation showcases the adaptability of the approach to real-world scenarios, highlighting its potential in diverse applications within the field of hybrid systems.

Aiming at cooperative navigation of multi-aircrafts, an adaptive EKF-SLAM algorithm for non-fixed landmark is proposed. First, the aircraft motion model and angle measurement model are established. Second, the fixed landmark cooperative EKF-SLAM algorithm is established. Furthermore, a distributed EKF-SLAM algorithm is designed. Then, the adaptive EKF-SLAM algorithm with non-fixed landmark is proposed. Finally, simulation results verify the effectiveness of the proposed algorithm.

This article discusses finite-time lag bipartite (FETLB) synchronization of double-layer networks with non-linear coupling strength and multiple time delays. The cooperative and competitive interactions between nodes are considered based on signed graphs. To address the non-linear couplings strength, the T-S fuzzy logic theory is used. An intermittent control approach is introduced to achieve FETLB synchronization, effectively minimizing control costs. Moreover, by the Lyapunov functional method, we derive criteria for achieving FETLB synchronization and provide estimations for the synchronization settling time. In addition, numerical simulation affirms the validity of the theoretical findings, showcasing the practical application of the synchronization results in secure communication.