This paper addresses co-design control strategies for continuous-time Markov jump systems where subsets of transition rate matrices are fixed a priori, challenging conventional co-design methodologies. A synchronously mode-dependent parametric framework is developed to address partial transition rate optimization alongside output feedback controller synthesis. Novel criterion is derived to guarantee mean-square stability by reconstructing adjustable switching parameters while preserving fixed system transitions. Stability analysis and controller design are unified through hybrid control principles. A numerical case studies validate the proposed approach, demonstrating enhanced feasibility compared to existing methods.

This paper presents a universal and adaptive control framework for reconfigurable vehicles subject to composite motion disturbances, incorporating a collaborative fault-tolerant mechanism. A model-based cascaded control architecture is developed based on the vehicle’s kinematic and dynamic models. To ensure safety, an improved adaptive geofencing strategy is proposed which integrates capability constraints with barrier functions in the kinematic loop. For dynamic feedback, an adaptive gain-filtered extended state observer enables accurate disturbance estimation from noisy outputs and improves robustness via feedforward compensation. Meanwhile, a collaborative fault-tolerant mechanism further allocates control inputs to mitigate actuator faults. Finally, experimental results validate the proposed method’s effectiveness under complex interference scenarios.

Six-wheel skid-steer vehicles are widely used in the real world because of their special steering structure and load-carrying capacity. In this article, we aim to study the event-triggered fuzzy yaw control of six-wheel skid-steer vehicles. The nonlinear lateral dynamics of a six-wheel skid-steer vehicle is modeled using the Takagi-Sugeno (T-S) fuzzy system with irregular fuzzy rules, in which more membership function information can be captured. Considering the high-frequency transmission mode used in vehicle motion systems due to high-precision control requirements, an event-triggered scheme with a dynamic threshold is proposed to ensure control accuracy while reducing the data transmission. Then, a flexible yaw control scheme is constructed in which two adjustable weighting factors are introduced to improve the flexibility of the fuzzy yaw controller. By combining the flexible yaw control scheme and dynamic event-triggered scheme, we design a set of event-triggered fuzzy yaw controllers that satisfy the finite-time stability of lateral motion tracking for six-wheel skid-steer vehicles. The advantages and effectiveness of the proposed method are verified by conducting the TruckSim-MATLAB joint simulation.

The reduced model-based coordinated design of fault detectors and controllers for discrete-time switching fuzzy systems is examined. First, the mean-square exponential stabilization of switching Takagi–Sugeno fuzzy systems is performed using the average dwell time method under an arbitrary switching law. Next, using segmented Lyapunov function techniques, a dynamic full- and reduced-order fault detector and controller is designed to ensure that the overall dynamic residual system is mean-square exponentially stable with a balanced$\mathcal {H}_{\infty }$performance level$(\xi, \beta)$. The solvability conditions for the fault detector and controller are derived using a linearization method, and the relevant parameters can be determined using the mathematical linear matrix solver toolbox. Two examples including a switching Chua’s circuit system are presented to demonstrate the effectiveness of the proposed fault detector and controller.

This article concerns the event-triggered fault detection filtering problem for nonlinear networked control systems. First, an event-triggered scheme with two trigger matrices is proposed by considering limited network resources; a fuzzy fault detection filter with a general structure is chosen as the residual generator. Then, we introduce a new event-based residual system by taking into consideration the interval time-varying delays. Sufficient conditions are obtained to guarantee that the event-based residual system is asymptotically stable and satisfies a prescribedH∞performance with the help of a reciprocally convex technique. Furthermore, some new relaxation matrices are introduced such that the corresponding solvability conditions can be established by means of a linearization procedure. Finally, examples are given to illustrate the effectiveness and advantages of the proposed new fault detection filtering techniques.

In this paper, the problem of event-triggered fuzzy-rule-dependent filter design for networked system is investigated. For the original system, our focus is on establishing a new fuzzy filtering error system, considering the event-triggered scheme, the network-induced delays. Then, constructing a desired Lyapunov-Krasovskii function, sufficient stability conditions can be obtained to ensure that the new fuzzy filtering error system is mean-square asymptotically stable with H∞ performance. Finally, transform these stability criteria into convex optimization problems, which can be calculated by the standard optimization toolbox.