Search

This article studies the finite‐time control problem for a class of nonlinear chaotic semi‐Markov jump systems with incomplete transition rates described by the T‐S fuzzy model approach. As a means to depict the dynamical properties pertaining to the examined system, parametric uncertainties, faults, external disturbances and input saturation are taken into consideration. The foremost objective of this study is to come up with a composite control mechanism that effectively rejects and attenuates the repercussions of faults and disturbances. In particular, we primarily built a disturbance observer in order to obtain a precise estimation of the external disturbances. After which, the fault diagnosis observer is designated to effectively estimate the faults. Specifically, a composite reliable control mechanism is developed by fusing the output of the constructed observers with the mode‐dependent fuzzy‐rule based state feedback controller. By employing suitable Lyapunov functions in conjunction with the linear matrix inequality technique, a set of mode‐dependent conditions is derived to ensure the finite‐time stochastic boundedness of the underlying closed‐loop and estimation error systems. Following this, the anticipated controller and observer gain matrices are elicited by resolving the established linear matrix inequalities. Thereafter, intending to ascertain the efficacy and usefulness of accrued theoretical findings, simulation results performed on Chua's circuit system is endowed. [ABSTRACT FROM AUTHOR]

The problem of memory feedback tracking control for unmanned aerial vehicle systems subject to nonlinear actuator faults and disturbances is investigated in this paper. First, a generalized extended state observer is constructed to get the estimates of the system states and the disturbances. Then, by incorporating the obtained estimates in the control design, an anti-disturbance memory feedback tracking control law is designed such that the resulting closed-loop augmented system is asymptotically stable, and thereby the states of the unmanned aerial vehicle system track the given reference trajectories with satisfactory disturbance rejection performance. Notably, by constructing appropriate asymmetric Lyapunov–Krasovskii functional, the stability and stabilization conditions for guaranteeing the desired tracking and disturbance attenuation performance are derived in terms of linear matrix inequalities. Further, the observer gains are evaluated using the pole placement approach. Finally, numerical simulations are given to verify that the proposed control strategy is viable. [ABSTRACT FROM AUTHOR]

ABSTRACT The main thrust of this study is to scrutinize the issues of fault estimation and asynchronous sampled‐data fault‐tolerant control for semi‐Markov jump cyber‐physical systems with external disturbances, faults and deception attacks. To do so, initially, an intermediate variable is framed and then using that variable as a foundation, a mode‐dependent intermediate estimator is constructed, which estimates the fault signals and system's state simultaneously. Due to the unavailability of mode information in the Markov chain for the observer/controller, a hidden Markov model is employed to represent the asynchronous scenario between the mode of the original system and that of the designed observer/controller. Subsequently, benefited by the estimated terms and sampled‐data approach, an asynchronous sampled fault‐tolerant control protocol is offered up that facilitates compensating for the faults occurring in the system. In the meantime, the extended passive performance is used to lessen the negative impact of external disturbances exerting on the system. Besides this, the deception attacks occurring in the system are presumed to have a stochastic nature that adheres to the Bernoulli distribution. Moreover, by constructing mode‐dependent Lyapunov–Krasovskii functional and blending it with integral inequalities, the sufficient condition confirming the intended outcomes is procured in the framework of linear matrix inequalities. Thereafter, on the platform of deduced adequate criteria, an explicit formulation for the requisite gain values can be obtained. Ultimately, simulation results are offered to verify the reliability of presented outcomes. [ABSTRACT FROM AUTHOR]

Real biological neurons are dynamical systems that can process a nonlinear, arbitrary input signal with a dynamic threshold voltage, exhibit refractory time, and have a smooth F – I curve. This paper presents a generalized bio-plausible neuron model with refractoriness, frequency adaptation, and dynamic threshold. The spiking characteristics of the generalized neuron are enhanced with less circuitry and fewer parameters compared to older circuits. The proposed silicon neuron can generate all known spiking behaviors, just like a biological neuron. The circuit is designed using a 180 nm standard CMOS process. The entire design uses 22 transistors with a total power consumption of only 2 nW for a 1 nA step current at a spike frequency of 122 Hz. The power consumption and spike frequency rate depend on the input current. The proposed neuron is also capable of displaying both Type I and Type II frequency response characteristics. In addition, our neuron model underwent Monte Carlo simulation with 1000 sample runs to assess its robustness and stability against process variations and uncertainties. The results indicate that the average energy consumption of the proposed neuron model falls within the range of 16 pJ to 68 pJ. [ABSTRACT FROM AUTHOR]

This study focuses on examining the issues of extended dissipative-based composite anti-disturbance reliable tracking control for stochastic Takagi–Sugeno fuzzy systems afflicted by sensor faults and multiple disturbances. Explicitly, the multiple disturbances include the autonomous Wiener process and non random noises with partly known information that are generated by an exogenous plant. To address the difficulty of estimating the non random disturbance while considering the partially known information, the study incorporates a fuzzy stochastic disturbance observer. Furthermore, to solve the output tracking issue of the system under consideration, a modified repetitive tracking control is implemented. Then, combining the methodologies of disturbance observer-based control technique with modified repetitive control, a composite anti-disturbance reliable tracking control strategy is developed for achieving the intended tracking goal despite the multiple disturbances and sensor faults encountered. Additionally, the proposed approach involves extended dissipativity scheme, which includes $ H_\infty $ H∞, passivity, dissipativity, and $ \mathfrak {L}_2 - \mathfrak {L}_\infty $ L2−L∞ performances in a unified framework. In particular, by employing Lyapunov–Krasovskii functional approach, the essential stability criteria for the proposed closed-loop system are articulated in the form of linear matrix inequalities. Additionally, numerical illustrations are presented to exemplify the application and efficiency of the developed control protocol. [ABSTRACT FROM AUTHOR]

This work aims to analyse the cluster consensus for positive multi-agent systems (MASs) with nonlinearities. This study focuses on introducing an observer-based controller with the aim of achieving cluster consensus in the considered positive nonlinear MASs, where the controller includes time-varying delay. Specifically in cluster consensus, agents are divided into multiple clusters to accomplish various collective tasks, each influenced by distinct inter-cluster and intra-cluster communications. In this study, a fixed directed graph is employed to express the communication among agents. By designing a proper Lyapunov-Krasovskii functional and utilising the properties of graph, a set of conditions required for cluster consensus of the examined MASs is established as linear matrix inequalities. Finally, the effectiveness of the derived theoretical findings is confirmed through numerical examples. [ABSTRACT FROM AUTHOR]

Loss-less data compression becomes the need of the hour for effective data compression and computation in VLSI test vector generation and testing in addition to hardware AI/ML computations. Golomb code is one of the effective technique for lossless data compression and it becomes valid only when the divisor can be expressed as power of two. This work aims to increase compression ratio by further encoding the unary part of the Golomb Rice (GR) code so as to decrease the amount of bits used, it mainly focuses on optimizing the hardware for encoding side. The algorithm was developed and coded in Verilog and simulated using Modelsim. This code was then synthesised in Cadence Encounter RTL Synthesiser. The modifications carried out show around 6% to 19% reduction in bits used for a linearly distributed data set. Worst-case delays have been reduced by 3% to 8%. Area reduction varies from 22% to 36% for different methods. Simulation for Power consumption shows nearly 7% reduction in switching power. This ideally suggest the usage of Golomb Rice coding technique for test vector compression and data computation for multiple data types, which should ideally have a geometrical distribution. [ABSTRACT FROM AUTHOR]

The braking system is a crucial component in any vehicle serving the vital purpose of slowing down or halting the vehicle's motion. The safety of passengers hinges significantly on the effectiveness of this system. In traditional braking setups, a prevalent issue during panic braking scenarios is wheel locking, which can have dire consequences. To counteract this problem, the automotive industry has embraced the Antilock Braking System (ABS) as a preferred solution. ABS enhances vehicle stability and steering control by preventing wheel lockup, thereby minimizing stopping distances. This study delves into the innovative fusion of ABS with Proportional-Integral-Derivative (PID) controllers to optimize and dramatically reduce a vehicle's stopping distance. ABS well known for its ability to prevent wheel lockup during braking and combined with PID control algorithms to achieve precise real-time modulation of braking forces. Through rigorous experimentation conducted in MATLAB simulation, integrating ABS and PID controllers remarkably reduces stopping distances, ensuring superior control and stability in emergency braking. This simulation of a 300 kg motorcycle at 25 m/s highlights PIDcontrolled ABS dynamics, achieving gradual braking with slip within 12-15%, applying a maximum torque of 1500 Nm. [ABSTRACT FROM AUTHOR]

Summary: The issues of cluster synchronization and state estimation for a class of nonlinear complex dynamical networks are concurrently focused in this study. In precise, led by the design of complex dynamical networks, a proportional integral‐based observer is implemented for achieving robustness, by the virtue of which the states of examined networks are estimated. Thereupon, a proportional integral observer‐based hybrid triggered control scheme is proposed, wherein, the switch‐over between time‐ and event‐ triggered scheme is governed through a Bernoulli distributed random variable. Further, with the application of mixed H∞$$ {H}_{\infty } $$ and passivity performance technique, the external disturbances for the addressed complex dynamical networks are reduced. Based on the Lyapunov stability theory, the requisite sufficient conditions in respect of linear matrix inequalities are provided which ensures the discussed complex dynamical network's synchronization phenomenon. In a further, the presented criteria are exploited for the attainment of required controller, proportional and integral gain matrices. In conclusion, the applicability of proposed results and efficacy of the undertaken strategy are evidently proven with the illustration of two numerical examples with Chua's circuit and Goodwin oscillator model. [ABSTRACT FROM AUTHOR]

Summary: With the aid of a proportional integral framework, the presented article focuses on the problems of finite‐time boundedness and fault estimation for Takagi–Sugeno fuzzy singular systems subject to time delays, faults and external disturbances. To commence, we conjure up a fuzzy‐dependent intermediate variable and from thereon, a proportional integral‐based fuzzy intermediate estimator is constructed. Moreover, the constructed estimator precisely facilitates for estimating the fault signals and system states in simultaneously. Besides this, the integral term in the proportional integral estimator offers greater design flexibility and higher resilience. Secondly, an intermediate estimator‐based fault‐tolerant control is devised by availing the information from the proportional integral‐based fuzzy intermediate estimator, which aids in effectively compensating the faults arising in the system. Subsequently, by setting up an appropriate Lyapunov–Krasovskii functional, the set of adequate requirements asserting the finite‐time boundedness with the endorsed mixed H∞$$ {H}_{\infty } $$ and passivity performance index is established in terms of linear matrix inequalities. After that, an explicit framework for the requisite gain matrices can be found forth basing on the formed linear matrix inequality criteria. Ultimately, simulation findings are supplied to evaluate the utility and applicability of the theoretical insights. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of dissipative-based stabilization for fractional-order nonlinear control systems with uncertainties, time-delay, external disturbances, actuator faults, actuator and sensor saturations. Specifically, a non-fragile reliable dynamic output feedback controller is designed for the purpose of stabilization of the addressed system. Due to the effect of saturation phenomena occurring in both the actuator and sensor, the anti-windup loops framed with the help of the observer design are incorporated into the controller design. Some sufficient conditions are formulated in terms of linear matrix inequalities by choosing a suitable Lyapunov function thereby assuring the dissipative-based stabilization. The derived results are thus validated by two numerical examples including the practical model of two-stage chemical reactor. [ABSTRACT FROM AUTHOR]

Summary: The underlying intention of this work is to devise a tracking control protocol for the nonlinear cyber‐physical systems that are prone to external disturbances, time‐varying input delays and deception attacks. To be more precise, the modified repetitive tracking controller is formulated for ensuring the asymptotic tracking outcomes of the assayed system with the aim of addressing the impacts caused by external disturbances as well as input time‐varying delays. First of all, the nonlinearities of the investigated cyber‐physical systems are efficaciously approximated by the interval type‐2 fuzzy model approach. Further, the predictor technique is utilized in this study to mitigate the influence of input delays and specifically, the extended Smith predictor approach is employed. That is, the transfer function is inserted into the conventional Smith predictor's main feedback channel. In parallel, the active disturbance rejection technique is executed to reject and estimate the external disturbance impacts on the assayed system. Notably, the improved equivalent‐input‐disturbance estimator approach is tied up and more precisely, the estimated disturbances obtained from the afore‐said estimator are incorporated into the proposed controller. Whilst the deception attacks are characterized as a stochastic distributed random variable that are governed by the Bernoulli distribution. With all of this as a backdrop, the appropriate delay‐dependent constraints are expressed in the context of linear matrix inequalities by employing the Lyapunov stability theory. In line with the predetermined criteria, the relations for computing the required gain matrices are also formulated. Ultimately, the simulation analysis is carried out using two distinct numerical examples to confirm the importance of the proposed control mechanism from the perspective of theory as well as practice. [ABSTRACT FROM AUTHOR]

This article features the composite disturbance estimation and non-fragile hybrid-triggered control problems for continuous-time repeated scalar nonlinear systems prone to external disturbances. Priorly, the proportional integral observer comprising of both proportional and integral loops is incorporated to obtain better state estimations. Further, the external disturbance weakening the system performance is carefully estimated by deploying an improved equivalent-input-disturbance technique. Then, the availed disturbance estimate is blended into the control algorithm to exterminate the influence of the disturbance acting upon the proffered system. Next, a hybrid-triggered control comprised of a transition among event and time triggered paradigms are considered to reduce the network transmittance and also to simultaneously enhances the system outcomes. On top of that, the perturbations in controller gain matrix are taken into concern in order to make the controller more resilient towards redundant changes. Following that, utilising the Lyapunov theory, we obtain the mean-square asymptotic stability requirements for the developed system with the use of linear matrix inequalities and configure the gain matrices. Successively, the credibility of the synthesised control system is portrayed by exhibiting two numerical examples. [ABSTRACT FROM AUTHOR]

Summary: This work primarily concentrates on the design of fault‐tolerant anti‐disturbance control for synchronization of multiple memristor‐based neural networks subject to time delay, matched and mismatched disturbances. Moreover, in the addressed network model, we consider parameter uncertainties and actuator faults. Firstly in order to estimate the matched disturbances generated by the exogenous system, a disturbance observer is devised. Whereas, the mismatched part is tackled by employing the mixed ℋ∞$$ {\mathscr{H}}_{\infty } $$ and passivity performance indexes. Subsequently, a unified controller is designed by incorporating error feedback control and the disturbance estimate. Further, with the assistance of Lyapunov stability theory and linear matrix inequality technique, an adequate criteria is procured to ascertain the required synchronization criteria for the assayed network model with the mixed ℋ∞$$ {\mathscr{H}}_{\infty } $$ and passivity performance indexes. Following this, by basing on the established conditions, the explicit form of the controller and observer gain matrices is obtained. In the end, a numerical example with simulation results is shown to confirm the potential and usefulness of the conclusions acquired from the theoretical analysis. [ABSTRACT FROM AUTHOR]

The prime intent of this study is to scrutinize the state estimation and finite‐time (FT) stabilization problems for a class of periodic piecewise time‐varying systems (PPTVSs) in the presence of external disturbances, immeasurable states and gain fluctuations by dint of resilient control. Moreover, the proportional integral observer system is built in line with the output of the PPTVSs to reconstruct the states of the PPTVSs, since the state dynamics of the system are often not measurable. Meanwhile, the output signals are quantized with the use of a logarithmic quantizer prior to being fed into the constructed observer systems. Further, the fluctuations in the controller and observer gain matrices are considered to occur in a random manner and they pursue the pattern of a Bernoulli distributed white sequence. Subsequently, by means of Lyapunov stability theory and the matrix polynomial lemma, the adequate requirements for ascertaining the FT boundedness and IO‐FT stabilization of the addressed system are procured in the context of linear matrix inequalities. Thereupon, on the premise of the established criteria, the gain matrices of the controller and observer are obtained. Ultimately, the simulation results have been showcased including the mass spring damper system to exemplify the efficacy and usefulness of the theoretical conclusions drawn. [ABSTRACT FROM AUTHOR]

This article examines the proportional integral observer (PIO)-based resilient tracking control problem for periodic piecewise polynomial systems (PPPSs) in the presence of time delay and disturbances. To be precise, the PPPSs are formulated by dividing the fundamental period of periodic systems into numerous subintervals, each of which is defined using matrix polynomial functions. Further, the PIO strategy is employed to estimate the states of the undertaken system with high precision wherein the integral term in PIO enhances the system's design flexibility and also increases its robustness. Taking advantage of these characteristics, a PIO-based tracking control is configured with gain perturbations to track the desired reference states. Moreover, to attenuate the implications made by disturbances in considered system design, $ H_\infty $ H ∞ performance is employed. Furthermore, in order to establish adequate conditions in the form of linear matrix inequalities, the time-varying polynomial Lyapunov–Krasovskii functional is implemented. Then, the time-varying gain matrices of the control scheme and PIO configuration are computed by solving the obtained criteria through the MATLAB platform. Concludingly, to evidence for the discoveries' potential and usefulness, a numerical example is offered. [ABSTRACT FROM AUTHOR]

This study deals with the stabilisation problem of fractional-order time-delay systems with polytopic uncertainties and multiple disturbances with the use of Lyapunov stability theory. Notably, the multiple disturbances comprising both the known and unknown signals, are respectively characterised by the norm-bounded and exogenous system which signifies the harmonic signals with modelling perturbations. The control protocol is configured by the integration of proportional-retarded controller with gain perturbations and the output of an anti-disturbance observer. Precisely, the disturbance observer is taken into account for attenuating the influence of disturbance signals. Moreover, the implementation of a time-delay term in the feedback loop replicates the dynamic features of a derivative action that relies only on position measurements and its time differencing capabilities make it to be minimally sensitive against noise and provide a smoothing effect. By virtue of these circumstances, the asymptotic stability of the considered system is assured. With the aid of a suitable Lyapunov function, a set of robust order-dependent sufficient conditions is derived and then solved through the MATLAB LMI toolbox. As a result, the controller gain matrices can be computed and two numerical examples, including an electrical circuit model with simulation results are presented to certify the inherent potential of the theoretical outcomes. [ABSTRACT FROM AUTHOR]

This paper intends to analyse the disturbance rejection and output tracking control for a class of nonlinear control systems with disturbances. In this connection, we present a method that combines a proportional-integral observer and nonlinear-equivalent-input-disturbance estimator for superior disturbance rejection performance. Specifically, the nonlinear-equivalent-input-disturbance estimator comprises of equivalent-input-disturbance estimator and nonlinear feedback term, which is employed to estimate and reject the disturbances from the nonlinear system. Notably, the proportional-integral loop in the proportional-integral observer reduces the estimation inaccuracy of the nonlinear-equivalent-input-disturbance. Then the estimated disturbance is intertwined into the repetitive control input to compensate it efficiently. In order to obtain the required results, the proposed control system is converted into a two-dimensional modified repetitive control system to describe the learning and control actions. In particular, the proposed controller enables to adjust the gains directly to improve the learning and control performance and as a result, the tracking accuracy increases. Using a general Lyapunov–Krasovskii functional, singular value decomposition technique and linear matrix inequalities approach, a design algorithm for establishing proportional-integral observer and feedback gains is developed for the system under consideration. Finally, simulation results are given to illustrate the developed method's validity and superiority. [ABSTRACT FROM AUTHOR]

This paper is concerned with the input–output finite-time (IO-FT) stabilisation problem for a class of continuous-time periodic piecewise polynomial systems (PPPSs) with immeasurable states and external disturbances via state estimation-based robust reliable controller. Firstly, to reflect the actuality, a parameter uncertainty that exhibits the random nature and the actuator faults with nonlinear character are considered in the addressed PPPSs and the control scheme, respectively. In detail, the randomness of uncertain parameters is portrayed by the stochastic variable and it is presumed to pursue the Bernoulli distributions. Secondly, to estimate the immeasurable states of PPPSs, a periodic piecewise polynomial observer is designed depending on the output of PPPSs. The main intent of this article is to devise a state estimation-based robust reliable controller to ascertain the IO-FT stabilisation of the PPPSs. Moreover, by bridging the Lyapunov stability theory, linear matrix inequality technique and IO-FT stability theory, the required IO-FT stabilisation conditions in the frame of linear matrix inequality are procured for the system under consideration. Eventually, simulation results of the addressed PPPSs are shown in line with the proposed analytical findings, revealing the competence, inherent capability and utility of the devised control protocol. [ABSTRACT FROM AUTHOR]

Summary: This study emphasis on the problem of state tracking and disturbance attenuation for Takagi‐Sugeno fuzzy based model with input time‐delay via improved extended state observer based predictive proportional‐integral tracking control. To be precise, a predictive proportional‐integral tracking controller is formulated by implementing the Smith‐Predictor strategy to restrain the influence of input time‐delay. Then, with the aid of improved extended state observer, the lumped disturbance is estimated and it is combined with the predictive proportional‐integral tracking control for disturbance attenuation. Further, closed‐loop control‐system is considered to ensure the satisfactory state tracking results for the considered system regardless of time‐delay in the control input and lumped disturbances. Meanwhile, based on the Lyapunov theory approach, the stability criteria for the proposed system are formulated in terms of linear matrix inequalities following which the gain matrices are derived. Finally, in order to evident the supremacy of the proffered control system, two numerical simulation results are provided. [ABSTRACT FROM AUTHOR]

In this work, we address hybrid-driven-based robust synchronization problem for multi-weighted complex dynamical networks with actuator saturation and deception attacks. The hybrid-triggered mechanism, which combines a switch between the event-triggered scheme and the time-triggered scheme, is often used to reduce the data transmission and the alleviate network burden. Further, the equivalent-input-disturbance technique is applied to eliminate the unknown disturbance effect of the addressed system. Moreover, a memory controller is designed under actuator saturation to ensure that the resultant augmented system is asymptotically synchronized even in the presence of deception attacks. Finally, three numerical examples are given to show the validity of the obtained theoretical results. [ABSTRACT FROM AUTHOR]

This study tackles the fault estimation issue for a continuous-time periodic piecewise time-varying systems (PPTVSs) with delays, fault signal and external disturbances. In particular, the PPTVSs are conjured up by segmenting the fundamental period of the periodic system into a finite number of subintervals. Moreover, fault estimator is designed in line with periodic piecewise observer systems to estimate the immeasurable states of the PPTVSs and the fault signal, simultaneously. Subsequently, in accordance with the estimated values of the fault signal and state dynamics, a fault-tolerant controller is devised. Moreover, by utilising Lyapunov stability theory and matrix polynomial lemma, sufficient criteria are procured in context of linear matrix inequalities to affirm the uniform boundedness of the undertaken system and error system. Further, relying on the acquired constraints, the precise configuration of the fault-tolerant control and observer gain matrices are proffered. Eventually, by offering two illustrative examples including mass-spring-damper system, the utility and potential of presented theoretical insights are validated. [ABSTRACT FROM AUTHOR]

In this work pure CuCr2O4 and Mn-doped CuCr2O4 nanoparticles were prepared using Microwave combustion process. The phase analysis of the prepared samples is investigated using X-Ray Diffraction technique and an decrease in particle size observed from ∼37 to ∼26 nm with rise in Mn doping concentration. Further optical data revealed the presence of multiple Mn-related optical centres. Morphological studies revealed the prepared samples exhibited irregular plate-shaped agglomerates. Furthermore, the antibacterial performance of undoped CuCr2O4 and Mn-doped CuCr2O4 samples are investigated. At 500 °C, the electrical conductivity for the CuCr2O4 and Mn-doped CuCr2O4 samples were found to be 0.98 × 10−2 S/cm and 2.13 × 10−2 S/cm respectively. The activation energy of the pristine CuCr2O4 and Mn-doped CuCr2O4 samples was found to be 0.87 eV and 0.69 eV respectively. [ABSTRACT FROM AUTHOR]

A promising option for generating renewable energy is by using Organic solar cells (OSCs), but their efficiency and environmental impact remain major challenges. To explore the use of dibenzotetrabenzoporphyrin (DBTBP) and metal nanoparticles as potential solutions to these challenges is the purpose of the study. By utilising DBTBP and metal nanoparticles in OSCs, it is possible to improve their efficiency and reduce their environmental impact by decreasing the amount of toxic materials used and increasing their lifespan. The study investigates the effects of DBTBP and metal nanoparticles on the performance of OSCs, analysing their optical and electrical properties. The results suggest that the use of DBTBP and metal nanoparticles in OSCs can significantly enhance their efficiency and reduce their carbon footprint, making them a more sustainable and environmentally friendly option for renewable energy. The results show the important inferences for the development of OSCs as a viable source of renewable energy, particularly in light of the increasing demand for environmentally friendly technologies. The use of DBTBP and metal nanoparticles in OSCs has the potential to overcome some of the major challenges faced by the field, while also providing a more sustainable and efficient source of renewable energy. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of finite-time dissipative-based distributive non-fragile filter design for a class of discrete-time complex systems subject to randomly occurring multiple delays, dynamic quantization and missing measurements. The main intention of this work is to propose a distributive non-fragile filter that ensures the stochastic finite-time boundedness together with prescribed dissipative performance in the presence of multiple delays. To characterize the random nature of delays, stochastic variables are introduced which satisfy the Bernoulli binary distribution. Moreover, the two factors such as missing measurements and dynamic quantization are implemented in the measurement signal. By employing S-procedure and constructing proper Lyapunov–Krasovskii functional, a set of linear matrix inequality (LMI)-based sufficient conditions that guarantee the stochastic finite-time boundedness with dissipative performance of the augmented filtering error system is obtained. Finally, the efficiency of the proposed distributive non-fragile filter design is proved by presenting three numerical examples including the continuous stirred tank reactor (CSTR) and a quarter-car suspension model. [ABSTRACT FROM AUTHOR]

This study concerned with the synchronization problem over a finite-time domain for a class of fractional-order stochastic neural networks via non-fragile controller with discontinuous activation functions. Specifically, the suggested state feedback controller sequentially cope with non-fragile scheme for gain scheduling process. Notably, the main objective of this work is to obtained the finite-time synchronization criterion for the resulting synchronized error system over finite bound with the developed non-fragile controller. For that, some consignment of sufficient conditions is derived systematically by implementing Lyapunov's indirect method and finite-time stability theory which ensures the finite-time stochastic synchronization of the stipulated neural networks. Later on, the controller gain fluctuations that obeying certain white noise sequels derived from Bernoulli distribution are formulated in terms of linear matrix inequalities. Eventually, the illustrated study are substantiated through two numerical examples and the simulation results manifest the advantage and accuracy of the proposed synchronization criteria. [ABSTRACT FROM AUTHOR]

This paper proposes an approach for the solvability of multi-agent systems with Markov jumps subject to time-varying delay and uncertainties. The primary concern of this paper is to construct a state feedback control design with a guaranteed cost function which not only ensures consensus but also assures certain amount of energy consumption. This cost function is designed with the aid of control inputs of all agents and state error among neighbouring agents. A new set of sufficient conditions for the guaranteed cost consensus of the considered Markov jumping multi-agent system (MAS) is derived in terms of linear matrix inequalities (LMIs) by constructing suitable Lyapunov-Krasovskii functional (LKF) and with the aid of Kronecker product properties. Finally, a numerical example is given to illustrate the effectiveness of the developed theoretical results. [ABSTRACT FROM AUTHOR]

In this article, the issue of finite-time boundedness is investigated for a class of uncertain periodic piecewise systems subject to time-varying input/state delays and external disturbances. The main aim of this article is to design an H ∞ observer-based control protocol for guaranteeing the resulting closed-loop system to be finite-time bounded. The state dynamics of the system are not always directly measurable, so that a system states are reconstructed by constructing a periodic piecewise observer system to get the required result. Subsequently, the Lyapunov–Krasovskii functional by the decomposition of periodic positive-definite matrices is built and in conjunction with convex optimisation technique and extended Wirtinger's integral inequality, the sufficient conditions are derived to assure the finite-time boundedness of the closed-loop system. In particular, the corresponding periodic piecewise time-varying controller and observer gain matrices can be obtained as solutions to a set of derived sufficient linear matrix inequality-based conditions. Finally, the efficacy of the proposed control design is examined by utilizing two numerical examples with simulation results including a vibration system model. [ABSTRACT FROM AUTHOR]

This paper addresses the reliable finite-time stabilisation problem for a class of fractional-order memristor neural networks under sampled-data controller influenced by the quantisation signal and actuator failures. Precisely, the framework of observer has been initiated for estimating unmeasured state and remunerate the actuator faults with nonlinearities in the controller. Precisely, quantiser is incorporated in the network can reduce the process of transmitting data. Subsequently, activation function approach bringing together with traditional indirect Lyapunov theory endows some sufficient conditions in the frame of linear matrix inequalities to assure the finite-time stabilisation criterion for the addressed neural networks under the proposed reliable sampled-data control. Explicitly, the state feedback control and observer gain matrices are attained by solving the developed linear matrix inequalities. Convincingly, two numerical simulations are explored to substantiate the excellence and potentiality of the developed control law. [ABSTRACT FROM AUTHOR]

• A resilient GESO based MRC control is designed to tackle the uncertainties and disturbances of turbofan systems. • The concise design of the control is developed by imposing the estimated disturbance on the control input channel. • The developed controller makes the state of the system to follow the given reference signal with accurate tracking. • Additive and multiplicative fluctuations are considered while designing the controller for better tracking performance. • The design procedure of the controller gain matrices are developed in the framework of linear matrix inequalities. The intention of this work is to analyse the issues of multiple disturbance estimation and rejection as well as robust tracking control design for turbofan systems subject to input gain perturbations. A standard generalized extended state observer is developed to estimate both the state disturbances and output measurement disturbances, simultaneously. Therewith, a modified repetitive controller is utilized with generalized extended state observer to track the states of the turbofan system accurately. Then, a new composite control strategy is developed by incorporating the estimates obtained via generalized extended state observer in modified repetitive controller to attenuate the effect of disturbances. Based on the pole placement technique, the observer gain is calculated and in accordance with Lyapunov stability theory, a set of sufficient conditions which ensures the robust asymptotic stability of the considered turbofan system is derived in the form of linear matrix inequalities. Moreover by offering the numerical examples with simulation results, the superiority of developed control strategy is validated. [ABSTRACT FROM AUTHOR]

In the present work, the effect of Mn doping in Zinc Chromite (ZnCr2O4) and particle size reduction on catalytic and photocatalytic degradation performance have been evaluated. The pristine Zn1−xMnxCr2O4 (x = 0 to 0.03) nanoscale samples are synthesized through a hydrothermal approach. The synthesized catalysts are characterized by XRD, HR-SEM, HR-TEM, catalytic, and photocatalytic degradation analyses. X-ray diffraction analysis results confirmed the formation of the ZnCr2O4 structure and its phase purity, crystallite size, and Mn dopant effect. The surface morphology and particle size of Zn1−xMnxCr2O4 samples are evaluated by SEM and TEM measurements. The textural properties of ZnCr2O4 samples are identified by the surface area analysis. The catalytic performance of Mn-doped ZnCr2O4 samples reveals superior catalytic performance compared to pristine ZnCr2O4 in benzaldehyde and carbonyl compound productions. Under UV irradiation, an excellent photocatalytic degradation efficiency of 89.66% for Zn0.97Mn0.03Cr2O4 catalyst with methylene blue has been obtained. [ABSTRACT FROM AUTHOR]

This paper studies a resilient control-based fault estimation problem for a class of networked control systems subject to jumping parameters and deception attacks. In particular, a fault estimator is developed under an observer-based framework to estimate the faults and system states concurrently, and procure better estimation accuracy. Next, the closed-loop error system is constructed with major factors like gain fluctuations and cyber attacks that may damage the network security. In accordance with the Lyapunov stability approach, a set of adequate criteria in the configuration of linear matrix inequalities is derived to confirm the stochastic boundedness of the resulting system. Further, the considered resilient controller and the observer gain matrices are calculated from the established linear matrix inequality constraints. The validity of the developed schemes and performance of the obtained results is consummated through two numerical examples, which include a high alpha research vehicle model. [ABSTRACT FROM AUTHOR]

This work personifies the problem of attaining aspired state tracking outcomes along with fault tolerance and disturbance attenuation for non-linear networked control systems (NCSs) based on interval type-2 (IT2) fuzzy approach. In particular, these objectives are accomplished by deploying a improved extended state observer (IESO) based composite disturbance rejection and fault-tolerant hybrid-triggered proportional–integral (PI) tracking control algorithm. Especially, a hybrid-triggered PI tracking controller is configured by embodying the event as well as time-triggered actions in the integral part of the described PI tracking controller to enhance the overall efficiency of the network transmission. Subsequently, an IESO is put into action for simultaneous estimations of the actuator fault and lumped disturbances impacting the system. These estimations are then blended into the hybrid-triggered PI tracking control for realizing eminent state tracking performance. On top of that, by employing the Lyapunov procedure, the stability requirements for the proffered system are organized as linear matrix inequalities (LMIs). Successively, the gain matrices of the PI tracking controller and IESO are acquired by solving these stability constraints. Further, to substantiate the productivity of built controller, numerical outcomes are graphically visualized. [ABSTRACT FROM AUTHOR]

The bio-mimetic structure of a neuron is taken into account for utilizing the electrophysiological data. These neuron circuits are entertained for the use in digital computers. At the end of Moore's law, conventional technology is striking different difficulties, such as power consumption, area utilization, and energy efficiency. To conquer these hurdles, a nanoscale, the nonvolatile memristor used in the proposed neuron modified from the refined AH neuron. Synapses are also built using anti-parallel memristors. These neurons and synapse are joined together such that the performance metrics are analyzed the energy consumption is reduced by 89.656%. Besides, power consumption is limited by 37.568% and the spike frequency is measured as 10.263 kHz when compared with the traditional CMOS synapse connected with the proposed neuron. Moreover, the measured energy per spike is 3.37 fJ. The implementation of the neuron network is done by 45 nm technology. [ABSTRACT FROM AUTHOR]

Contrary to von Neumann computer architecture, neuromorphic computing is a biologically inspired method for building several sorts of brain-inspired computers. This computer technology uses silicon neurons and synapses to solve difficult machine learning and AI challenges. The goal of neuromorphic computing is to build a brain-like ability to compute, learn, and adapt. Building an appropriate neuroscience model, establishing a new architecture, modeling new devices, finding new materials for the devices, programming framework, and applications for these neuromorphic devices are major technological challenges. This study covers numerous neuron models from Hodgkin–Huxley to I&F, mathematical equations, circuit level analysis and motivations for neuromorphic computing. Here some of the most useful silicon neuron models are discussed in terms of biological plausibility, computational efficiency, and temperature dependency. This survey shows that more than 52 transistors make up the silicon HH neuron, which occupies less than 0.01 mm 2 and consumes 60 uW of power. On the other hand, an I&F neuron needs less than 20 transistors, occupies 442 um 2 and consumes 40 pW of power. [ABSTRACT FROM AUTHOR]

The two-step SILAR approach was used to create pure and Aluminium (Al) doped Zinc Oxide (ZnO) thin films. The structural, optical, and morphological properties of pure ZnO thin film and ZnO thin films doped with Al (1, 3, and 5)% were investigated. All the sample's diffraction peaks were mapped to a hexagonal Wurtzite form. For the synthesized thin films, dislocation density, crystallite size, microstrain, and lattice parameters were calculated. Pure ZnO thin films have a spherical structure, while Al-doped ZnO thin films have a hexagonal-faced rod-like shape. The bandgap of the prepared thin film reduces with the rise in Al content. The occurrence of deep level and near band edge emissions were confirmed by photoluminescence (PL) investigations. The maximal zone of inhibition was studied using the Agar diffusion process on Gram-positive and Gram-negative (i.e., S.aureus and E.coli) bacteria. Pure and Al-doped ZnO both showed significant antibacterial activity. All the samples exhibit significant antimicrobial activity. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of fault detection filter design for a class of nonlinear Markovian jump systems with incomplete measurements and distributed delay. A unified model is proposed to address the phenomena such as packet losses, signal quantization and sensor saturation. The objective is to design a finite-time dissipative-based fault detection filter such that for all unknown disturbances, the estimation error between the residual signal and the fault is minimized and also to guarantee the stochastic finite-time boundedness of the augmented filtering error system with a prespecified dissipative performance level. By using Lyapunov stability theory along with stochastic analysis techniques, a set of sufficient criterion is established for the existence of desired fault detection filter. Further, the filter gain parameters are obtained by solving the linear matrix inequality-based constraints. Two numerical examples including an inverted pendulum model are presented to illustrate the effectiveness of the proposed filter design algorithm. [ABSTRACT FROM AUTHOR]

In this paper, the design problem of fault detection filter for a class of networked control system subject to Markov jump parameters, randomly occurring uncertainties, sensor faults and packet dropouts by using state feedback control is investigated. The fault detection filter is used as an optimal residual generator that generates the residual signal and also guarantees the sensitivity of residual signal to the faults. To be more specific, a suitable threshold is selected for the residual evaluation function to reduce the error between the sensor faults and the residual signal. Further, by employing a fault detection technique along with output quantization approach, a new set of sufficient conditions is derived to ensure the stochastic stabilization of the addressed system with sensor faults under a predefined H ∞ performance level. Particularly, by constructing Lyapunov–Krasovskii functional and utilizing extended Wirtinger-based single integral inequality, the required sufficient conditions are derived in terms of linear matrix inequalities for getting the required result. At last, two numerical examples including high alpha research vehicle model are presented to demonstrate the usefulness of our developed results. [ABSTRACT FROM AUTHOR]

In this paper, an uncertainty and disturbance estimator (UDE)‐based control is employed to ensure the finite‐time tracking and disturbance rejection performance for a class of Takagi–Sugeno fuzzy switched systems including additive time‐varying delays, unknown time‐varying uncertainties and disturbances. To be precise, the robust tracking performance is achieved by estimating unknown uncertainties and disturbances with the aid of low‐pass filter by means of appropriate bandwidth choice of the desired filter. Moreover, a new delay‐dependent finite‐time stability criterion is derived by employing fuzzy‐dependent Lyapunov–Krasovskii functional, extended Wirtinger's integral inequality and average dwell‐time approach to enforce the addressed system to track the given reference system within a finite period of time. Finally, the developed theoretical results are ensured by presenting the numerical examples with simulation results. [ABSTRACT FROM AUTHOR]

This paper deals with the robust observer-based synchronisation problem for a class of complex dynamic networks subject to multi-weights, time-varying coupling delay and external disturbance. Specifically, the gain fluctuation appears in the proposed controller and is represented in terms of a random variable obeying the Bernoulli distribution. The main objective of this paper is to design a non-fragile memory state feedback controller such that the resulting error system is stochastically synchronised under a prescribed performance level . First, a Luenberger-type state observer is constructed to estimate the state variables of the addressed system. Second, by constructing an appropriate Lyapunov–Krasovskii functional and using Wirtinger-based integral inequality techniques, the required set of sufficient conditions for the synchronisation of the proposed system is established in the form of linear matrix inequalities. In the end, two numerical examples are provided to demonstrate the validity and feasibility of the developed theoretical results. [ABSTRACT FROM AUTHOR]

The fundamental objective of this study is to focus on the control design for a class of Takagi–Sugeno fuzzy chaotic semi-Markov jump systems afflicted with multi-source disturbances. With an intention to portray more actual dynamical characteristics of the considered system, the actuator faults, partially unknown transition probabilities, randomly occurring uncertainties and gain fluctuations are considered. In particular, the multi-source disturbances are classified into matched and mismatched disturbances. Notably, the matched disturbances generated by systems whose dynamics are expressed in state-space form which are estimated with the construction of disturbance observers. Further, extended dissipative performance is intended to minimize the impact of mismatched disturbances. Specifically, a composite resilient reliable control scheme is put forward for synthesizing state feedback controller and output of the disturbance observers with the aim of rejecting and attenuating the aforementioned disturbances. On the strength of Lyapunov stability theory and linear matrix inequality concepts, a group of sufficient conditions is acquired to ensure that the assayed closed-loop systems and disturbance estimation error systems are stochastically stable. After that, the explicit forms of the composite controller and disturbance observers that adhere to the developed stability conditions are precisely expressed. To this end, the developed theoretical results are then applied to a standard Chua's circuit model, which aids in validating its effectiveness and usability. [ABSTRACT FROM AUTHOR]

The fundamental objective of this study is to focus on the control design for a class of Takagi–Sugeno fuzzy chaotic semi-Markov jump systems afflicted with multi-source disturbances. With an intention to portray more actual dynamical characteristics of the considered system, the actuator faults, partially unknown transition probabilities, randomly occurring uncertainties and gain fluctuations are considered. In particular, the multi-source disturbances are classified into matched and mismatched disturbances. Notably, the matched disturbances generated by systems whose dynamics are expressed in state-space form which are estimated with the construction of disturbance observers. Further, extended dissipative performance is intended to minimize the impact of mismatched disturbances. Specifically, a composite resilient reliable control scheme is put forward for synthesizing state feedback controller and output of the disturbance observers with the aim of rejecting and attenuating the aforementioned disturbances. On the strength of Lyapunov stability theory and linear matrix inequality concepts, a group of sufficient conditions is acquired to ensure that the assayed closed-loop systems and disturbance estimation error systems are stochastically stable. After that, the explicit forms of the composite controller and disturbance observers that adhere to the developed stability conditions are precisely expressed. To this end, the developed theoretical results are then applied to a standard Chua's circuit model, which aids in validating its effectiveness and usability. [ABSTRACT FROM AUTHOR]