Lingchen Zhu

In this article, the problem of improved full-error constrained control for unknown interconnected nonlinear time-delay systems with input saturation is investigated. To address this issue, auxiliary systems and a filter are constructed to generate modified signals, which are added to the constraint boundaries to prevent full dynamic errors (tracking error and virtual errors) from violating flexible boundaries and causing singularity problems during input saturation or drastic changes in the reference signal. To enhance the dynamic performance of all system errors, the error-driven nonlinear feedback technique is applied to all transform errors, enabling them to possess self-tuning characteristics. Furthermore, a decentralized adaptive learning constrained control strategy is proposed by employing fuzzy logic systems with an incremental adaptive mechanism to approximate complex uncertainties. The stability analysis demonstrates that the proposed control scheme guarantees the semi-global uniform ultimate boundedness of all signals in the closed-loop system, and the full dynamic errors are constrained within self-adjustable performance boundaries in the presence of input saturation. Finally, simulation results demonstrate the efficacy of the presented control strategy.

This article investigates decentralized adaptive control for a class of unknown parameter-varying interconnected time-delay nonlinear systems subject to asymmetric full-state constraints. By innovatively constructing an exponential scaling function on system states and an asymmetric integral barrier Lyapunov function (AIBLF), the states of the system can be directly constrained to predesigned bounds of exponential rate convergence. Based on the congelation of variables method, different unknown time-varying parameters of interconnected time-delay nonlinear systems with a mild requirement are well addressed, and the asymptotic stability of the whole system is proved with our proposed control strategy. Furthermore, the proposed decentralized adaptive controller guarantees that all system states can converge to zero with the exponential rate while maintaining within the asymmetric constraints. Finally, the validity of the presented control scheme is demonstrated by the simulation results.

This brief investigates the problem of fixed-time state observer-based output feedback control design for nonlinear systems with full-state constraints. First, a fixed-time state observer is constructed to estimate the unknown states, which can accurately estimate the system states within a fixed settling time. Then, by combining the integral barrier Lyapunov function with the backstepping method, the full-state constraints are realized after the fixed time. Meanwhile, the proposed control strategy can directly constrain the states rather than impose constraints on errors, which reduces the conservativeness of the constraint satisfaction condition. The proposed control method ensures that all signals in the closed-loop system are bounded and symmetric state constraints are strictly maintained after the fixed settling time. Finally, simulation results prove the effectiveness of the proposed method.

In this article, the problem of adaptive decentralized control is investigated for a class of interconnected time-delay uncertain nonlinear systems with different unknown control directions and deferred asymmetric time-varying (DTV) full-state constraints. By constructing the novel time-varying asymmetric integral barrier Lyapunov function (TVAIBLF), the conservative limitation of constant integral barrier Lyapunov function (IBLF) or symmetric IBLF is reduced and the need on the prior knowledge of control gains is also avoided, while the deferred constraints directly imposed on the states of system are achieved by introducing the shifting function into the controller design. Furthermore, based on the Nussbaum-type functions, a new adaptive decentralized control strategy for interconnected time-delay nonlinear systems with subsystems having different control directions is proposed via backstepping method. And it is proven that the proposed control method can guarantee that all signals in closed-loop system are bounded and the transform errors asymptotically converge to zero. Finally, the effectiveness of the proposed control strategy is illustrated through the simulation results.

In this work, we present the development of a compositional simulator accelerated by proxy flash calculation. We aim to speed up the compositional modeling of unconventional formations by stochastic training. We first developed a standalone vapor-liquid flash calculation module with the consideration of capillary pressure and shift of critical properties induced by confinement. We then developed a fully connected network with 3 hidden layers using Keras. The network is trained with Adam optimizer. 250,000 samples are used as training data, while 50,000 samples are used as testing data. Based on the trained network, we developed a forward modeling (prediction) module in a compositional simulator. Therefore, during the simulation run, the phase behavior of the multicomponent system within each grid block at each iteration is obtained by simple interpolation from the forward module. Our standalone flash calculation module matches molecular simulation results well. The accuracy of the trained network is up to 97%. With the implementation of the proxy flash calculation module, the CPU time is reduced by more than 30%. In the compositional simulator, less than 2% of CPU time is spent in the proxy flash calculation. The novelty of this work lies in two aspects. We have incorporated the impacts of both capillary pressure and shift of critical properties in the flash calculation, which matches molecular simulation results well. We developed a proxy flash calculation module and implemented it in a compositional simulator to replace the traditional flash calculation module, speeding the simulation by 30%.

Once an oil and gas wellbore has been drilled, steel casings and cement slurry are placed to ensure structural support, protection from fluid invasion, and most importantly to provide zonal isolation. The actual wellbore and string structure is rarely concentric but rather is often an eccentric one, especially in deviated boreholes. The term “eccentricity” is used to describe how off-center a casing string is within another pipe or the open-hole. In a typical double-string configuration, the inner casing is eccentered with respect to the outer string which itself is also eccentered within the cylindrical hole. The annuli may or may not be filled with solid cement, and the cement may have liquid-filled channels or be disbonded over localized azimuthal ranges. The complexity of wave propagation along axial intervals is significant in that multiple modes can be excited and detected with characteristics that are affected by the various parameters, including eccentering, in a non-linear fashion. A successful diagnosis of cement flaws largely relies on a thorough understanding of the complex acoustic modal information. The present study employs both modeling and experiments to fully understand the acoustic wave propagation in the complex, fluid-solid nested, cylindrically layered structures, with geometric eccentricities. The experimental results show excellent agreement with the theoretical predictions from newly developed, borehole acoustic modeling approaches. As such, it provides the basis for better understanding the operative wave physics and providing the means for effective inspection methodologies to assess well integrity and zonal isolation of oil wells.