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.

This article investigates the distributed control of a group of stochastic high-order nonlinear systems in which the subsystems are with unknown and time-varying control coefficients of unknown signs, inherent nonlinear drift and diffusion terms. To solve the control problem with unknown control directions, where traditional available Nussbaum functions are not applicable for the consensus of stochastic nonlinear systems with unknown and time-varying coefficients of unknown signs, a novel type of Nussbaum function is proposed with a new paradigm of stability analysis in probability. Global consensus control of stochastic multiagent systems is achieved by designing distributed controllers which integrate designed distributed filters and novel Nussbaum functions. In addition, it can be proved that all signals in the closed-loop system are bound in probability, and the transient consensus errors of the followers are bounded by positive constants which can be adjusted arbitrarily small. The effectiveness of the proposed control scheme is demonstrated by simulation results.

In this article, the problem of integral sliding mode control (ISMC) for a class of nonlinear systems with stochastic characteristics under cyber-attack is investigated. The control system and the cyber-attack are modeled as an Itô-type stochastic differential equation. The stochastic nonlinear systems are approached by the Takagi-Sugeno fuzzy model. A dynamic ISMC scheme is applied and the states and control input are analyzed within a universal dynamic model. It is demonstrated that trajectory of the system can be confined to the integral sliding surface within finite time, and the stability of closed-loop system under cyber-attack will be guaranteed by using a set of linear matrix inequalities. Following a standard procedure of universal fuzzy ISMC, it is shown that all signals in the closed-loop system will be guaranteed bounded, and the states are asymptotic stochastic stable if some conditions are met. An inverted pendulum is applied to show the effectiveness of our control scheme.

This article investigates the control of underactuated crane systems with unknown system parameters and nonsmooth input nonlinearities. To solve this problem, a novel filter-based adaptive control method is designed for the underactuated crane systems. First, since the backstepping control scheme cannot be directly applied to the crane systems, a group of filters is designed such that the crane systems become a class of strict-feedback nonlinear systems in each step of backstepping. Then, in order to ensure that the swing angle and position error converge to the origin, the variable transformation method is adopted. The result demonstrates that the tracking errors of the underactuated crane systems could be guaranteed to converge to a ball of origin with an arbitrarily small radius. Finally, the simulation results show that the proposed scheme is effective.

In this article, the adaptive control for a class of strict-feedback nonlinear systems with uncertainties under injection and deception attacks is considered. An adaptive control scheme is proposed to deal with the injection and deception attacks meanwhile guarantee that regulation errors could be made arbitrarily small by adjusting control parameters. Compared with existing works whose models are linear or relatively simple, the model we consider in this article is nonlinear with parametric uncertainties. A new type of feedback control scheme is introduced to solve this problem. A simulation example is given to verify the effectiveness of our proposed control scheme.

In this article, the power distribution and tracking problems of the distributed energy storage system (ESS) are addressed by designing a cooperative adaptive terminal sliding mode (CATSM) controller based on a multi-agent network topology for each ESS. First, a novel adaptive power allocation algorithm (APAA) is proposed to achieve a consistent state-of-charge (SOC) for each battery in a distributed ESS. Then, considering the capacity degradation of the battery during long-term charging and discharging, we use real-time current and SOC to estimate the current capacity of the battery, which ensures the accuracy of the algorithm. Then, based on the proposed algorithm, the CATSM controllers are designed for each ESS via a multi-agent network topology for the distributed ESS, and the projection operator is used to guarantee the boundedness of adaptive estimation. Finally, the simulation results are provided to validate the feasibility and effectiveness of the proposed control strategy.

In this article, the event-triggered adaptive output feedback control of multivariable system under nonsmooth actuator nonlinearities, including deadzone, backlash, and hysteresis is investigated. The nonsmooth actuator nonlinearities are handled with a unified framework by modeling them with a time-varying disturbance and a control input. With an event-triggered mechanism and an one-parameter estimation approach, the communication consumption for the control of multivariable system is significantly reduced. It is shown that all signals in the closed loop system are bounded. The Zeno behavior is also avoided. The simulation results demonstrate the effectiveness of the control scheme.