International Journal of Robust and Nonlinear Control最新文献

This article addresses robust output regulation for systems affected by disturbances generated by an uncertain exosystem as well as matched external disturbances. The robustness of the feedback loop is achieved by combining internal model based control with sliding mode control, resulting in a structurally simple controller. The design of the proposed controller is presented first for the full information problem, that is, the disturbances generated by the exosystem and the state-information is available for the control algorithm. This requirement is relaxed in the second step of the controller design, where the observer-based robust output feedback-loop structure is developed. Results from a comparative simulation study are presented to illustrate the advantages and the effectiveness of the proposed controller concept.

In this work, an adaptive fast terminal sliding mode control (AFSMC) approach based on joint torque estimation and friction compensation is proposed to enhance the trajectory tracking accuracy of robotic manipulators under variable load conditions. The joint torque estimation utilizes an improved harmonic drive compliance model and adaptive low-pass filtering, and friction compensation employs a hybrid model accounting for velocity and load torque effects. These compensations reduce the upper bound of the uncertainty, while AFSMC further reduces dependency on upper uncertainty bounds and minimizes the chattering. The stability analysis using the Lyapunov method confirms the effectiveness of this approach. Experimental results demonstrate that the proposed controller achieves smaller root mean square and maximum error of trajectory tracking, thus significantly improving trajectory tracking accuracy under variable load conditions.

Path tracking plays a critical role in autonomous driving for autonomous ground vehicle (AGV). However, AGV faces challenges in accurate tracking and chatter reduction due to external disturbances, making it difficult to meet the tracking performance requirements. Currently, sliding mode control (SMC) and disturbances observer are primarily employed for disturbance estimation. However, ensuring finite-time robust control remains a significant challenge. To ensure rapid convergence of tracking errors and effective disturbance rejection, this paper proposed a novel non-singular fast terminal sliding mode (NFTSM) control scheme based on finite-time disturbance observation (FDO). First, a novel NFTSM controller based on AGV dynamic model is developed to achieve fast convergence of tracking errors. Then, to mitigate disturbances effects and suppress chatter, an innovative FDO method is employed. Finally, based on FDO, the NFTSM-FDO establishes a control scheme that enhances disturbances suppression and accelerates convergence. The simulation and experimental results demonstrate the innovation of the proposed method. Compared with other SMC methods, the results validate the effectiveness and advantages of the proposed approach, exhibiting fast convergence and superior tracking performance.

The event-triggered control of Markov jump systems has attracted more and more interest in field control. However, the problem of how to design a transition probability-dependent event-triggered mechanism and controller has not been fully considered. This paper investigates the problem of event-triggered control for Lipschitz nonlinear Markov jump systems. Through Taylor series expansion, a linear auxiliary system is constructed to obtain the approximate state, whose system matrices are described by the probability-weighted matrices of nonlinear Markov jump systems. By redefining the measurement error as the difference between the current state and the approximate state, a probability-dependent event-triggered mechanism is designed for Markov jump systems. The effectiveness of the developed approach is illustrated by two comparison examples.

This article presents an asynchronous event-triggered scheme for switched Takagi–Sugeno (T–S) fuzzy systems against dual-channel hybrid cyber attacks. Different from existing results, both sensor and controller channels are subjected to aperiodic denial-of-service attacks and random false data injection attacks. To efficiently utilize dual-channel network communication resources while resisting hybrid attacks, two resilient event-triggered mechanisms (ETMs) are constructed. Considering asynchronous ETMs and hybrid cyber attacks, the time-delay switched T–S fuzzy system is derived by utilizing model transformation methods. Thereby, the stability conditions are derived by utilizing multiple Lyapunov functions technique, and slack matrices are introduced to further relax the conditions. Finally, two examples are given to demonstrate the effectiveness of the developed event-based security control strategy.

This paper presents a method for calculating the Region of Attraction (ROA) of nonlinear dynamical systems, both with and without control. The ROA is determined by solving a hierarchy of semidefinite programs (SDPs) defined on a splitting of the time and state space. Previous works demonstrated that this splitting could significantly enhance approximation accuracy, although the improvement was highly dependent on the ad-hoc selection of split locations. In this work, we eliminate the need for this ad-hoc selection by introducing an optimization-based method that performs the splits through conic differentiation of the underlying semidefinite programming problem. We provide the differentiability conditions for the split ROA problem, prove the absence of a duality gap, and demonstrate the effectiveness of our method through numerical examples.