Recent advancements in Intelligent Connected Vehicle (ICV) systems highlight the critical importance of cybersecurity within these complex networks, yet they still face challenges such as difficulties in precise modeling and poor adaptability to dynamic environments. This paper introduces an innovative control approach by integrating an event-triggered Intermittent Control (IC) strategy within a Zero-Trust Framework (ZTF). This methodology selectively triggers events for vehicle identities and data that meet a predefined trust threshold during each control interval, significantly enhancing the dynamic response capability of the platoon control system. By optimizing resource allocation, this strategy ensures secure and reliable signal transmission and effectively safeguards the platoon against potential malicious node attacks. Consequently, this research offers a novel solution for achieving both security and efficiency in ICV platoon control.

This paper investigates the problem of distributed state monitoring for intelligent connected vehicle (ICV) fleets based on embedded trust levels within a zero-trust network architecture (ZTNA) while considering the impact of unknown input disturbances. The ZTNA significantly enhances the overall security performance of the vehicle fleet. To implement the “never trust, always verify” principle, we first analyze the effects of zero-trust architecture on the communication relationships among intelligent connected vehicles (ICVs). Drawing inspiration from human trust dynamics, rules for establishing and reducing trust levels between vehicles are formulated. A variable-directed graph is employed to represent the communication topology of the entire vehicle fleet. Next, a distributed unknown input monitor structure is proposed using known information and verified global state monitoring results from neighboring vehicles with embedded trust levels. By utilizing selectable matrices to process local and global control inputs, any individual vehicle can monitor the state of the entire fleet. Finally, a simulation analysis of a fleet of six vehicle nodes demonstrates the correctness and effectiveness of the proposed method.

This article investigates the problem of removing the peaking phenomenon in the stabilization of a class of nonlinear cascaded systems using linear partial state feedback within a quadratic program (QP) framework. By appropriately designing the QP and selecting its parameters, the inter-subsystem cascaded input terms are effectively constrained within a desirable control-invariant set, thereby eliminating undesirable transient peaks. Semi-global stabilization of the overall system is achieved through only minimal modifications to the nominal linear feedback controllers. Owing to the simplicity of the resulting controller structure and the real-time efficiency of QP solvers, the proposed method is readily applicable to practical systems. Numerical examples from previous studies are revisited to demonstrate the effectiveness and robustness of the proposed control strategy.

Local nonlinear fuzzy systems are useful for control solutions due to their ability to handle unmeasurable/inexact premise variables and reduce computational complexity. However, their estimation problems still require further development. This article addresses this issue by investigating set-membership estimation for a class of discrete-time local nonlinear uncertain Takagi–Sugeno fuzzy systems with guaranteed performance. We propose a new observer architecture that solves partially decouplable unknown inputs and converts nonlinear error dynamics into a linear parameter-varying type. Using the systematic$\ell _\infty$-technique, the design conditions in the form of linear matrix inequalities ensure stability and output performance of the state estimation. We also derive a straightforward and effective zonotopic analysis method, considering the fuzzy and local nonlinear context, for less conservative results without using any specific interval set computation. Furthermore, a fast fault detection logic is proposed as an application of the set-membership estimation. Finally, we demonstrate the feasibility and advantages of our approach through three compelling examples, showcasing its efficacy in different scenarios.

Considering disturbances, noise, and sensor faults, this article investigates interval estimation for discrete-time Takagi–Sugeno fuzzy systems. To obtain precise estimation results and attenuate disturbances and noise in the system simultaneously, we integrate robust observers based on the$ H_{\infty }$technique and reachability analysis. Two novel observer gain computation methods are proposed for different purposes. The time-invariant method relaxes the original design conditions by transforming the parameterized linear matrix inequality (LMI) into a series of LMIs to increase computational speed, while the time-varying method employs the parameterized LMI directly and conducts calculation online. Furthermore, reachable set representations for error dynamics are formulated by making use of both time-invariant observer gain and time-varying observer gain. An inverted pendulum system simulation and a comparative numerical simulation are studied to illustrate the effectiveness and superiority of the developed methods.

This paper is devoted to solve the problems on simultaneous actuator and sensor fault estimations as well as the nonfragile fault-tolerant control (FTC) for a kind of Markovian jump systems with faults and disturbances. First, the considered system is converted to an augmented system by putting the sensor fault into the new state. Then, an adaptive observer is designed for the descriptor system with the actuator fault adjusted by the designed adaptive law. Based on the estimated actuator faults, an output-feedback-based FTC strategy is proposed to stabilize the closed-loop system against actuator and sensor faults, and disturbances, while showing robustness for the control gain perturbations. Sufficient conditions for the existences of the observer and controller are provided in forms of linear matrix inequalities. Finally, a practical application is given to express the validation and effectiveness of the proposed method.

This correspondence paper is concerned with observer design problems for a class of unknown input switched descriptor systems under average dwell time switching signals. The switched descriptor system under consideration is first transformed into a general switched linear system, and then a switched reduced-order observer that can asymptotically estimate the system state without suffering the influence from the unknown inputs is developed. Besides, a high-order sliding mode observer is introduced to obtain the estimations of the output derivatives by using the system measured outputs. On the basis of estimations of the states and output derivatives, an unknown input reconstructing method is provided. Finally, two examples are presented to verify the effectiveness of the proposed approaches.