E6AP dysfunction is associated with Angelman syndrome and Autism spectrum disorder. Additionally, the host hijacked by high-risk HPV E6 to aberrantly ubiquitinate tumor suppressor p53, which linked development of multiple types cancer, including most cervical cancers. Here we show that E6AP/E6 complex exist, respectively, as a monomer dimer protomer. The short α1-helix transforms into longer helical structure when in E6. extended α1-helices intersect symmetrically contribute dimerization....

This paper investigates both robust H/sub /spl infin// analysis and synthesis problems involving observer-based fuzzy control via linear matrix inequality methods for which efficient optimization techniques are available. The observer controller capable of disturbance-rejection in the presence unknown but bounded disturbance. We present results a unified fashion applicable to continuous- discrete-time with or without uncertainty. Finally, validity applicability approach demonstrated by examples.

This article proposes a novel reinforcement learning-based model predictive control (RLMPC) scheme for discrete-time systems. The integrates (MPC) and learning (RL) through policy iteration (PI), where MPC is generator the RL technique employed to evaluate policy. Then obtained value function taken as terminal cost of MPC, thus improving generated advantage doing so that it rules out need offline design paradigm cost, auxiliary controller, constraint in traditional MPC. Moreover, RLMPC...

ABSTRACT This paper addresses the problem of tracking a reference trajectory with high‐accuracy for controlled object unknown system dynamics, subject to input and output constraints. To this end, we propose novel learning‐based data‐enabled predictive control (DeePC) algorithm, which consists two main parts: Off‐line training Gaussian process regression (GPR) model online by using probabilistic information obtained from GPR model. train model, develop method capable predicting an subjected...

In this paper, we investigate the problem of robust H/sub /spl infin// performance and stabilization for a class uncertain fuzzy systems with Frobenius norm-bounded parameter uncertainties in all system matrices. Both continuous- discrete-time are considered under unified treatment called bounded real lemma systems. Unlike linear theory control where necessary sufficient conditions were obtained, only condition based on Lyapunov method is shown. Furthermore, connection between problems...

Summary To address the difficulties of under‐actuation, nonlinearity, strong coupling, disturbances and measurement noise in four‐wheel steering (4WS) vehicle tracking control, this paper presents an innovative control strategy based on differential flatness linear active disturbance rejection controller (LADRC). The property 4WS is derived from a simplified dynamic model that ignores some complicated dynamics external disturbances. impact these neglected components system treated as part...

In this article, resilient strategy design is investigated for a cloud control system (CCS) subject to jamming attack. the presence of jammer, signals, including measurements and inputs between server physical plant may be interfered, which degrades signal-to-interferencelus-noise ratio further leads packet dropout signals. A Stackelberg game applied depict interaction transmitter jammer. On account equilibria two players, controller devised CCS with time-varying delay. novel cross-layer...

In order to reduce the risk of slope stability evaluation due fuzziness calculation parameters, a finite element analysis method based on fuzzy statistics is proposed. Based principle quasi-static and with help software COMSOL multiphysics, this paper studies gravel soil accumulation rock under action different seismic acceleration. By analyzing displacement, plastic zone safety factor slope, analyzed. The research results show that mechanical parameters will lead position displacement...

In order to share the NIRS (near infrared reflectance spectroscopy) calibration model among similar instruments, samples were firstly selected by Kennard Stone algorithm in spectrum. Secondly a BP artificial neural network was established based on host instrument and could be shared slave only when spectra detected processed direct standardization (DS). The results manifest that modeling effect is better latent factor number 9. root mean squared error of prediction (RMSEP) for reduced...

In this note, we will show that the output feedback controller gains K in paper is only an approximated solution K* = QP(-1)C0(dagger), with dagger denoting Moore-Penrose inverse of matrix C0. Consequently not equal to and therefore it may satisfy linear inequality (LMI) constraints aforementioned paper. Instead, iterative LMI approach suggested solve dynamic stabilization problem for fuzzy systems.

The objective of this paper is to increase the accuracy air leak detection through predicting differential pressure using radial basis function(RBF)neural network. Air plays an important role in ensuring excellent performance products. If low, unqualified products may be judged as qualified or otherwise. So it which influenced by temperature, test pressure, chamber volume, balance time and so on. It not easy compensate error directly, for movement status gas being complicated. This applies...

In order to study the dynamic response of Fuel Gas Supply System (FGSS) under complex operating conditions during ship navigation, this paper presents a low-pressure gas supply system designed match WinGD5RT-Flex50DF dualfuel engine. The model FGSS is established using Aspen HYSYS software, with control strategies for pressure, flow rate, and temperature. varying loads, emergency shutdown, loading, fuel conversion simulated. results show that can effectively rapidly adjust pump speed rates...

ABSTRACT This article proposes an online learning‐based event‐triggered model predictive control (OLEMPC) scheme for constrained nonlinear systems with state‐dependent uncertainties. The incorporates both the nominal and learned models to ensure favorable theoretical properties during learning. A composite measurement‐triggering strategy is devised reduce number of state measurements as well solving optimization problems. attenuates conservatism in measurement triggering through combining...

Developed an intelligent test system for the electronic accelerator pedal, and optimized it. The uses three-dimensional motion platform driven by servo motor to realize control movement of pedal automatically least squares method optimize data which is integrated with linear Hall sensors. Carried on experiment double electric potential signal output electron results show that has excellent dynamic static performance, change parameters load disturbances strong robustness. Performance...

Working principle of gas brake valve and performance testing methods tightness, static dynamic characteristics are introduced. Several characteristic parameters, such as initial pressure differential response time, blended into methods. An automatic measurement system the based on virtual instrument is developed, realizes double-position independent inspection one set PC control system, improving test efficiency. It designed by using Labview, graphical programming software. Combining with...

Abstract This paper proposes a novel learning‐based model predictive control (LMPC) scheme for discrete‐time nonlinear systems. It overcomes the challenge of manually designing terminal conditions traditional MPC and enhances performance. The employs value iteration (VI) in reinforcement learning (RL), autonomously designs cost by iteratively performing function policy update under known dynamics constraints. In contrast to existing schemes that combine RL with MPC, proposed explicitly...

The bistable potential function is divided into inner and outer sides. Inside outside functions are both turned to the form of parabola, then symmetric parabolic constructed. Based on Kramers escape theory, ratio SNR different analyzed compared. theoretical analysis numerical simulation manifest that much better than other functions. mechanism explained which can enhance noise effects from perspective dynamics. strength effect related functional inside function. And plays a greater role.

This paper investigates a force-position controller using neural network model free control with time-delay estimation(TDE-MFNNC) for the motion of upper limb exoskeleton. The system establishes muscle force prediction based on scaling principle Hill to estimate torque provided by limb. Then exoskeleton is built in Solidworks as virtual prototype which used instead real model. We performed stability verify effectiveness comparing TDE-iPD and compensation simulation result has more...