Abstract This paper explores a class of unbounded distributed delayed inertial neural networks. By introducing some new differential inequality analysis and abandoning the traditional order reduction technique, assertions are derived to verify global exponential stability addressed networks, which improve generalize recently published articles. Finally, two cases numerical examples simulations given illustrate these analytical conclusions.

Current challenge for dynamic pathway control in metabolic engineering is enabling the components of artificial regulatory system to be tunable. Here, we designed and built a heme-responsive containing heme biosensor HrtR CRISPRi regulate chemicals production while maintaining intracellular homeostasis. A series engineered biosensors with varied sensitivity threshold were obtained by semi-rational design site saturated mutation HrtR. The modified metabolite-binding affinity was confirmed...

To explore the complexity of locally active memristor and its application circuits, a tristable is proposed applied in periodic, chaotic, hyperchaotic circuits. The quantitative numerical analysis illustrated steady-state switching mechanism using power-off plot dynamic route map. For any pulse amplitude that can achieve successful switching, there must be minimum width enables state variable to move beyond attractive region equilibrium point. As local activity origin complexity, oscillate...

SUMMARY This paper is concerned with the globally stabilizing control design for a class of high‐order nonholonomic systems. Compared existing literature, systems under investigations have more uncertainties and unknowns, such as neither lower nor upper bound known each coefficient renders methods highly difficult to problems or even inapplicable. In this paper, by defining two new unknown parameters whose dynamic updating laws are properly chosen also using discontinuous coordinates...

This paper investigates the problem of global stabilization via partial‐state feedback and adaptive technique for a class high‐order stochastic nonlinear systems with more uncertainties/unknowns zero dynamics. First all, two stability concepts are slightly extended to allow than one solution. To solve problem, lot substantial technical difficulties should be overcome since presence severe uncertainties/unknowns, unmeasurable dynamics, noise. By introducing suitable updated law an unknown...

This paper considers the global adaptive stabilisation for a class of uncertain stochastic nonlinear systems. Comparing with existing relevant literature, systems under investigation allow more serious unknowns/uncertainties. More importantly, by remarkably reducing dimension dynamic compensator system unknowns (from n to 2) and considerably diminishing overparametrisation in this proposes an improved design scheme state-feedback controllers. It is turned out that, designed controller loop,...

Abstract This paper focuses on the observer design for nonlinear discrete‐time systems by means of canonical form. At first, sufficient and necessary conditions are obtained a class autonomous to be immersible into higher dimensional Then method called dynamic error linearization is developed. By introducing auxiliary system, augmented system shown locally equivalent generalized form, whose terms contain states output system. A constructive algorithm also provided obtain state coordinate...

This study considers the global adaptive control design for a class of high‐order uncertain non‐linear systems. Different from existing results, systems under investigation have serious unknowns which cannot be bounded by any known constants, and particularly double input channels, that is, scalar directly affects two one‐dimensional subsystems. Inspired author's recent skillfully combing method adding power integrator some techniques, an controller is successfully constructed can guarantee...

The synchronization of Chua's system, whose inputs include an unknown constant parameter, is studied in this paper. A constructive method applied to designing adaptive controller, which only one variable information the master system needed. With action control signals, parameter slave will approach corresponding system. At same time, errors also converge zero asymptotically. Numerical simulations show that proposed theoretical very effective.

This paper proposes a novel linear recurrent neural network for multivariable system identification, namely linerec (LNN). Based on this network, the transfer function matrix model of can be identified directly according to its input and output data. In way, LNNs differ from existing networks. An LNN is constructed based identification prior knowledge in system, weights have definite physical meaning. equivalent equation set, training algorithm Widrow-Hoff learning rules. paper, theoretical...

In previous studies on adaptive observers for linear time-varying (LTV) systems, the provided results were commonly based a strong assumption that there exists feedback gain matrix F(t) stabilizing pair (A(t), C(t)). However, in general, it is difficult task LTV system B(t), this note, we apply an improved high observer to design of class systems with uncertain parameters. The proposed removes difficulty finding by using high-gain matrix, where only constant parameter and need be designed....

This paper further investigates the problem of finite-time state feedback stabilization for a class stochastic nonholonomic systems in chained form. Compared with existing literature, under investigation have more uncertainties, such as the<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mrow><mml:msub><mml:mrow><mml:mi>x</mml:mi></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math>-subsystem contains disturbance. renders control methods...

Abstract In this paper, a floating-buoy wave energy converter using hydrostatic transmission system is studied. The entire work progress of power generation device introduced, and the hydraulic principles are emphasized through simulation to verify feasibility design principle system. mathematical model accumulator established applied in AMEsim simulation. results show that plays an important role correct configuration parameters can improve rapidity stability work. Experimental compared...

This paper investigates the exponential consensus problem for a class of nonlinear leader-following multi-agent systems using impulsive control, where impulses are generated by event-triggered mechanism and subjected to actuation delays. It is proved that Zeno behavior can be avoided, employing linear matrix inequality technique, some sufficient conditions realizing considered system derived. Actuation delay an important factor affecting system, our results show increasing enlarge lower...

This paper concerns the global regulation for a class of stochastic high-order nonlinear systems which admit more general system form than existing works. For details, except serious nonlinearities show that considered are generalisations strict-feedback systems, most distinct feature is exhibited by multiple unknown control directions, is, all coefficients virtual and actual have signs. By skillfully employing Nussbaum function, applying method adding power integrator, an effective scheme...

With the development of adaptive cruise control (ACC) vehicles, traffic on freeways will be a mixture ACC vehicles and traditional manual vehicles. It is new challenge for freeway state estimation. This paper proposes neural network-based method to estimate speed under mixed traffic. Three different network models are investigated using simulation data, which programmed by MATLAB. The results indicate that model with three input neurons (average speeds from microwave detector, percentage...