In the hot rolling process, the hydraulic looper device is the key actuator that maintains the dynamic stability of strip tension between stands. Its flow compensation strategy plays a critical role in mitigating tension fluctuations and enhancing control accuracy. To overcome the limitations of conventional hydraulic looper flow compensation methods that rely on empirical parameters and are unsuited to dynamic rolling environments, this paper proposes an adaptive flow compensation algorithm based on servo valve current control for hydraulic cylinders. Initially, a comprehensive model of the hydraulic looper system is developed, encompassing both a servo valve-hydraulic cylinder sub-model and an overall looper system model. This integrated model is then used to perform theoretical calculations of the flow compensation value. Subsequently, to address the impact of varying system parameters due to operational conditions and environmental disturbances, a state-space model is formulated, and a Kalman filtering technique is employed for real-time system state estimation and flow compensation prediction. This approach facilitates the adaptive regulation of the servo valve current. Experimental results demonstrate that the proposed method effectively suppresses strip tension fluctuations and significantly enhances the system's dynamic response and disturbance rejection capabilities.
This research focuses on the state estimation based stabilization of nonlinear semi-Markov jump cyber-physical systems that are exposed to external disturbances, multiple cyberattacks, time-varying delay and gain fluctuations. A proportional integral observer is constructed to reconstruct the immeasurable system states. The stabilization issue is addressed through the design of an appropriate resilient control that can withstand multiple cyberattacks, namely denial-of-service and deception attacks. In particular, the occurrence of multiple cyberattacks is characterized by two independent Bernoulli-distributed random variables. Moreover, a mode dependent Lyapunov-Krasovskii functional is employed along with integral inequalities to derive a set of sufficient conditions in the form of linear matrix inequalities, which ensures stochastic stability and - dissipativity of the addressed system regardless of multiple cyberattacks. Subsequently, the resulting conditions are solved to compute the values of the observer and controller gain matrices. Eventually, two numerical examples are provided to validate the theoretical outcomes.
ABSTRACT In this paper, an adaptive designated‐time output feedback tracking method for a quadrotor unmanned aerial vehicle, capable of handling systems with stochastic disturbances while accounting for unobservable states and unknown nonlinear functions. By integrating stochastic theory with designated‐time strategy, an innovative stochastic designated‐time stability control mechanism suitable for quadrotor unmanned aerial vehicles is introduced for the first time. Subsequently, computational complexity was reduced through dynamic surface control technology, whilst the fuzzy logic system approximated the unknown nonlinear functions within the system. Furthermore, an FLS‐based observer employing adaptive backstepping is designed to estimate unobservable states. The study demonstrates that this control approach ensures probabilistic semi‐global stability and designated time stability for all states in the closed‐loop system. Concurrently, both the system output error and observer error enter a small neighborhood near the origin. Simulation outcomes validate the effectiveness of the proposed approach.
ABSTRACT The article focuses on the adaptive neural fixed‐time tracking control for nonlinear switched systems with asymmetric, time‐varying full‐state constraints. To address the uncertain nonlinear dynamics, radial basis function neural networks (RBF NNs) are adopted for the uncertain function approximation. A fixed‐time command filter is utilized, thereby avoiding the computational complexity associated with the iterative differentiation of the virtual controller. Specially, the state constraints problem is coped by utilizing the nonlinear transformation function directly, which removes the need for feasibility conditions on virtual controllers. An adaptive fixed‐time tracking control approach is proposed by incorporating the command filtering control approach within the backstepping control framework. The proposed control algorithm assures the fixed‐time bounded stability of the considered system, while maintaining full‐states constraint satisfaction. Lastly, the rationality of the proposed control method is illustrated via the simulation section.
ABSTRACT This article presents the fault‐tolerant control (FTC)for a class of uncertain linear systems with disturbances through sliding mode (SM) methodology. By leveraging the property of exponentially decaying barrier Lyapunov function and a modified nonlinear sliding variable, a novel robust SM FTC is developed. Unlike the classic results, the trajectories are confined to a prescribed practical sliding band, by which the SM cannot be lost despite the actuator faults and uncertainties. Within this framework, a reduced‐order SM is established for the concerned dynamic systems without reaching phase. Further, through the Lyapunov direct method, a sufficient condition in terms of LMI is derived such that the uncertain system is uniformly bounded within a performance boundary. Lastly, a numerical simulation of unmanned aircraft system (UAS) is borrowed to testify the effectiveness of the developed findings.
