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In this article, an extended state observer‐based finite‐region control scheme is presented for two‐dimensional Markov jump systems with unknown mismatched disturbances. The mathematical model of the two‐dimensional Markov jump systems is built on the well‐known Roesser model. By establishing special recursive formulas and utilizing the 2‐D Lyapunov function theory, sufficient conditions are obtained, which prove that the resultant system is finite‐region bounded, if some linear matrix inequalities are achieved. Then, we provide an algorithm to solve the extended state observer‐based controller gains. With the proposed control scheme, the external disturbances can be actively rejected from the system outputs. To conclude, a numerical example based on the Darboux equation is provided to demonstrate the validity and effectiveness of the devised control scheme. [ABSTRACT FROM AUTHOR]

This article concerns the admissibility analysis of singular time-delay systems. The aim is to get superior criteria in both low conservativeness and less decision variables. To this end, the systems are decomposed and treated with different methods. The Lyapunov–Krasovskii functionals (LKFs) are constructed based on the state decomposition. By using tighter integral inequalities and the free weighting matrix method, some new admissibility criteria are derived to compare with the previous results, and are applied to the partial element equivalent circuits (PEECs) in numerical examples, by which the advantages of the proposed method are verified. [ABSTRACT FROM AUTHOR]

This article focuses on the finite-time asynchronous output feedback control scheme for a class of Markov jump systems subject to external disturbances and nonlinearities. The conic-type nonlinearities hold a constraint condition which locates in a known hyper-sphere with an indefinite center. In addition, the asynchronization phenomenon occurs between the system and the controller, which can be represented by means of a hidden Markov model. A sufficient condition is derived not only to guarantee the finite-time boundedness of the acquired closed-loop systems but also to possess a desired $H_{\infty }$ performance on the basis of Lyapunov functional technique. Finally, the validity and feasibility of the proposed method are demonstrated with a dc-motor experiment. [ABSTRACT FROM AUTHOR]

This article study the asynchronous control problem for a class of discrete-time Markovian jumping Lur’e systems (MJLSs) over the finite-time interval. The partial accessibility of system modes with respect to the designed controller is described by a hidden Markov model (HMM). The asynchronous control law consists of two parts, i.e., the states and the nonlinearities involved in the dynamics of the controlled system. By selecting the appropriate Lyapunov functional and applying the modified sector condition, the finite-time stabilization conditions under the control constraints are derived. Finally, the effectiveness of the designed method is verified by an illustrative simulation. [ABSTRACT FROM AUTHOR]

This paper is concerned with the sliding mode control (SMC) via finite-time stabilization (FTS) for a class of conic-type nonlinear semi-Markovian jumping systems (SMJSs). Comparing with the classical Markovian jumping systems, the transition rates of SMJSs are related to the random sojourn-time $g$. Based on this, a suitable SMC law for driving the state trajectories to the designed sliding surface within a finite-time interval is given. Then, the FTS over reaching phase and sliding motion phase is further proved to guarantee the FTS of the whole SMJSs. Finally, the effectiveness of the proposed method is demonstrated by a time-delayed Chua’s circuit simulation. [ABSTRACT FROM AUTHOR]

This paper studies the $ {H}_{ {\infty }}$ sliding mode control (SMC) problem for a class of discrete-time conic-type nonlinear systems with time-delays and uncertainties. The nonlinear terms satisfy the conic-type constraint condition that lies in a know hyper-sphere with an uncertain center. By choosing a proper Lyapunov candidate, sufficient conditions are derived to ensure the asymptotic stability of the sliding mode dynamics while achieving a prescribed $ {H}_{ {\infty }}$ disturbance attenuation level and finally converted into a minimization problem. The controller is constructed to guarantee the discrete-time reach condition and maintain the states on the prespecified sliding surface. A simulation result and a practical example related to the Chua’s circuit are given at last to show the validity of our SMC strategy. [ABSTRACT FROM AUTHOR]

Summary: Joint estimation of states and time‐varying parameters of linear stochastic systems is of practical importance for fault diagnosis and fault tolerant control. The known fact is that measurements have outliers. They can significantly degrade the properties of linearly recursive algorithms, which are designed to work in presence of Gaussian noises. This article proposes two kinds of strategies for joint parameter‐state robust estimation of linear stochastic models in presence of all possible faults and non‐Gaussian noises. In the form of Theorem, joint robust algorithm for systems with sensor and component faults, as well as the algorithm for systems with parameter faults are proposed. Because of their good features in robust filtering, Masreliez‐Martin filter represents a cornerstone for realization of the proposed robust algorithms for joint state‐parameter estimation. The good features of proposed robust estimation algorithms, in relation to algorithms based on other widely‐used filters, are illustrated by simulation results. On the other side, intensive research in the field of mathematical modeling of pneumatic servo drives has shown that their mathematical models are nonlinear in which a lot of important details cannot be included in the model. Also, it has been well known that the nonlinear model can be approximated by a linear model with time‐varying parameters. Due to the abovementioned reasons, it can be assumed that the pneumatic cylinder model is a linear stochastic model with variable parameters. The good practical values of the proposed robust joint algorithm to identification of the pneumatic cylinder are illustrated by experimental results. [ABSTRACT FROM AUTHOR]

In this paper, an online adaptive optimal control problem of a class of continuous-time Markov jump linear systems (MJLSs) is investigated by using a parallel reinforcement learning (RL) algorithm with completely unknown dynamics. Before collecting and learning the subsystems information of states and inputs, the exploration noise is firstly added to describe the actual control input. Then, a novel parallel RL algorithm is used to parallelly compute the corresponding N coupled algebraic Riccati equations by online learning. By this algorithm, we will not need to know the dynamic information of the MJLSs. The convergence of the proposed algorithm is also proved. Finally, the effectiveness and applicability of this novel algorithm is illustrated by two simulation examples. [ABSTRACT FROM AUTHOR]

An observer‐based finite‐time asynchronous H∞ control law is designed for a class of hidden Markov jumping systems with non‐linearities and external disturbances. The non‐linearities satisfy the conic‐type constraint condition that lies in a known hypersphere with an uncertain centre. The non‐synchronisation phenomenon between the system modes and observer/controller modes is modelled by a hidden Markov model. By means of the proper stochastic Lyapunov–Krasovskii functional method, a sufficient condition is obtained to guarantee the stochastic finite‐time boundedness of the corresponding argument error dynamic systems with a satisfied H∞ disturbance rejection level. Finally, the feasibility and validity of the main results is illustrated through a pratical example related to the DC motor. [ABSTRACT FROM AUTHOR]

The finite‐time stabilisation for a class of time‐delayed Markovian jumping systems with conic nonlinearities is studied. The authors aim to design a suitable control law to stabilise the closed‐loop system during a specified finite time. An appropriate Lyapunov–Krasovskii functional method is given to ensure the existence of finite‐time stabilisation controller and the relevant sufficient conditions have been formulated in the form of linear matrix inequalities. Finally, a simulation example is given to show the effectiveness of the proposed design approach. [ABSTRACT FROM AUTHOR]

This paper investigates the asynchronous resilient controller design problem for a class of nonlinear switched systems with time-delays and uncertainties in a given finite-time interval. By constructing proper multiple Lyapunov–Krasovskii functions and applying average dwell time methods, a switching law and the relevant asynchronous resilient controller are designed to guarantee the finite-time boundedness of the closed-loop system with a specified ${H} _{\infty }$ performance index. The ${H} _{\infty }$ resilient controller design problems can be derived by solving a set of linear matrix inequalities. A practical example is employed to demonstrate the availability of the proposed methods. [ABSTRACT FROM AUTHOR]

The finite-time sliding mode controller design problem of a class of conic-type nonlinear systems with time-delays and mismatched external disturbance is studied. The time-delay conic nonlinearities are considered to lie in a known hypersphere with an uncertain center. A scalar selection criterion dependent sliding mode control (SMC) law is constructed to drive the state trajectories onto the specified sliding surface during any assigned short time interval. By using slack matrix approach, a delay-dependent sufficient condition is derived to ensure the finite-time boundedness of the closed-loop systems over the finite-time interval. Then, the algorithm for designing the finite-time SMC law is established. Finally, two examples related to the time-delayed Chua’s circuit is given to demonstrate the effectiveness of the developed methods. [ABSTRACT FROM AUTHOR]

Key message: The mutated LsTT2 and Ls2OGD genes are responsible for white seeds and yellow seeds in lettuce, respectively. Three LsCHS genes are involved in the biosynthesis of flavonoid in seed coats. Lettuce seeds have several different colors, including black, yellow, and white. The genetic mechanisms underlying color variations of lettuce seeds remain unknown. We used genome-wide association studies (GWAS) and map-based cloning approaches to clone genes controlling the color of lettuce seeds. LsTT2, which encodes an R2R3-MYB transcription factor and is homologous to the TT2 gene in Arabidopsis, was shown to be the causal gene for the variation of black and white seeds in lettuce. A point mutation leads to the lack of stop codon in the LsTT2 transcript, resulting in white seeds. Knockout of the LsTT2 gene converted black seeds to white seeds. The locus controlling yellow seeds was mapped to Chromosome 2. Knockout of two 2-oxoglutarate-dependent dioxygenases (2OGD) genes from the candidate region converted black seeds to yellow seeds, suggesting that these two 2OGD proteins catalyze the conversion of yellow metabolites to black metabolites. We also showed that three LsCHS genes from the candidate region are associated with flavonoid biosynthesis in seeds. Knockout mutants of the three LsCHS genes decreased color intensity. This study provides new insights into the regulation of flavonoid biosynthesis in plants. [ABSTRACT FROM AUTHOR]

A new online iterative algorithm for solving the H ∞ control problem of continuous-time Markovian jumping linear systems is developed. For comparison, an available offline iterative algorithm for converging to the solution of the H ∞ control problem is firstly proposed. Based on the offline iterative algorithm and a new online decoupling technique named subsystems transformation method, a set of linear subsystems, which implementation in parallel, are obtained. By means of the adaptive dynamic programming technique, the two-player zero-sum game with the coupled game algebraic Riccati equation is solved online thereafter. The convergence of the novel policy iteration algorithm is also established. At last, simulation results have illustrated the effectiveness and applicability of these two methods. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This studies the infinite horizon optimal control problem for a class of continuous‐time systems subjected to multiplicative noises and Markovian jumps by using a data‐driven policy iteration algorithm. The optimal control problem is equivalent to solve a stochastic coupled algebraic Riccatic equation (CARE). An off‐line iteration algorithm is first established to converge the solutions of the stochastic CARE, which is generalised from an implicit iterative algorithm. By applying subsystems transformation (ST) technique, the off‐line iterative algorithm is decoupled into N parallel Kleinman's iterative equations. To learn the solution of the stochastic CARE from N decomposed linear subsystems data, an ST‐based data‐driven policy iteration algorithm is proposed and the convergence is proved. Finally, a numerical example is given to illustrate the effectiveness and applicability of the proposed two iterative algorithms. [ABSTRACT FROM AUTHOR]

• The H ∞ fault-tolerant control scheme is studied for a class of conic-type nonlinear Markov jump systems with sensor and actuator faults. • The hidden Markov model is introduced to deal with the asynchronous phenomenon, and the H ∞ fault-tolerant controller is designed by selecting suitable Lyapunov-Krasovskii functional. • The proposed control strategy can not only ensure the finite-time boundedness of the closed-loop system, but also guarantee the required H ∞ performance. This paper studies the H ∞ fault-tolerant control problem for a class of conic-type nonlinear Markov jump systems with sensor and actuator faults as well as unknown disturbances. Firstly, the hidden Markov model is introduced to deal with the asynchronous problem existing in the control systems. By selecting suitable Lyapunov-Krasovskii function, linear matrix inequalities techniques are applied to obtain the H ∞ fault-tolerant controller. A new condition of the state feedback H ∞ fault-tolerant controller with actuator faults and sensor faults is presented. The proposed control strategy can not only ensure the finite-time boundness of the closed loop system, but also guarantee the required H ∞ performance. Lastly, the availability of the design scheme is validated by a simulation example. [ABSTRACT FROM AUTHOR]

This paper studies the robust finite-time energy-to-peak filtering problem for a class of uncertain nonlinear Markovian jumping systems (MJSs) with energy constraint external disturbances. The Takagi–Sugeno (T–S) fuzzy model is employed to represent the nonlinear MJSs. By selecting the appropriate Lyapunov–Krasovskii functional, a sufficient condition is derived such that the filtering error dynamic fuzzy MJSs are finite-time stable and have a prescribed level of L 2 – L ∞ disturbance attenuation in a finite time-interval. The sufficient condition on the existence of robust finite-time energy-to-peak fuzzy filtering criterion is formulated in the form of linear matrix inequalities and the designed finite-time energy-to-peak fuzzy filter is described as an optimization one. A numerical example is given to illustrate the effectiveness of the proposed design approach. [ABSTRACT FROM AUTHOR]

The finite-time passive control for a class of nonlinear uncertain systems with time-delays and uncertainties is studied. The nonlinear parameters are satisfied Lipschitz conditions. An optimal robust passive controller with respect to the finite-time interval is designed while the exogenous disturbances are unknown but energy bounded. Based on passive control theory, the sufficient condition for the existence of finite-time robust passive controller is given. This condition such that the resulting closed-loop system is finite-time boundedness (FTB) for all admissible uncertainties and satisfies the given passive control index. By using the constructed Lyapunov function, and applying linear matrix inequalities techniques (LMIs), the design method of the finite-time optimal passive controller is derived and can be obtained. Simulation results demonstrate the validity of the proposed approach. [ABSTRACT FROM AUTHOR]

This study studies the online adaptive optimal control problems for a class of continuous‐time Markov jump linear systems (MJLSs) based on a novel policy iteration algorithm. By utilising a new decoupling technique named subsystems transformation, the authors re‐construct the MJLSs and a set of new coupled systems composed of N subsystems are obtained. The online policy iteration algorithm was used to solve the coupled algebraic matrix Riccati equations with partial knowledge regarding to the system dynamics, and the relevant optimal controllers equivalent to the investigated MJLSs are designed. Moreover, the convergence of the novel policy iteration algorithm is also established. Finally, a simulation example is given to illustrate the effectiveness and applicability of the proposed approach. [ABSTRACT FROM AUTHOR]

The finite-time H ∞ control problem of a class of Lipschitz nonlinear system with parameter uncertainties is studied. The nonlinear parameters are considered to satisfy the quasi-one-sided Lipschitz condition. By using Lyapunov function approach and linear matrix inequality techniques, a state feedback controller is designed to guarantee that the resulted closed-loop system is finite-time bounded and satisfies a given H ∞ constraint condition. And the designed algorithm is described as an optimization one. Simulation results illustrate the validity of the proposed approach. [ABSTRACT FROM AUTHOR]

The paper deals with the problem of non-fragile observer-based passive control for a class of Markovian jumping systems (MJSs) subjected to uncertainties, nonlinearities and time-delays. Based on the Takagi–Sugeno fuzzy models, the dynamics of mode-dependent non-fragile state observer and feedback controller system and the combined closed-loop fuzzy dynamic MJSs are constructed. A sufficient condition for passivity and stochastic stability of the combined system is derived and proved by means of the Lyapunov–Krasovskii functional methods and linear matrix inequalities (LMIs) techniques. The non-fragile passive controller and observer parameters can be solved directly by using the existing LMIs optimization techniques. Finally, a numerical simulation is given to illustrate the performance of the proposed approach. [ABSTRACT FROM AUTHOR]

The observer-based finite-time passive control problem of a class of Lipschitz nonlinear systems with uncertainties and time delays is studied. The nonlinear parameters are considered to satisfy the global Lipschitz conditions and the exogenous disturbances are unknown but energy-bounded. By constructing an appropriate Lyapunov function, a observer-based state feedback controller is designed to guarantee that the resulting closed-loop system is finite-time bounded and satisfies the given passive constraint condition. Some sufficient conditions for the solution to this problem are derived in terms of linear matrix inequalities. Simulation results illustrate the validity of the proposed approach. [ABSTRACT FROM AUTHOR]

Abstract: The unbiased H ∞ filtering problem is considered for a class of Markov jump systems (MJSs) with distributed time-delays. Based on the selected Lyapunov–Krasovskii functional, it gives a sufficient condition for the existence of the mode-dependent unbiased H ∞ filter such that the filtering error dynamic MJSs is stochastically stable and satisfies a prescribed level of H ∞ disturbance attenuation in an infinite time-interval. The design criterions are presented in the form of linear matrix inequality techniques, and then are described as the optimization problems. At last, two numerical examples are employed to illustrate the effectiveness of the developed techniques. [Copyright &y& Elsevier]

Abstract: This paper studies the finite-time state estimation and H ∞ filter design problem for a class of uncertain Markovian jumping systems (MJSs) with bounded transition probabilities. Based on the selected Lyapunov–Krasovskii functional, the finite-time H ∞ filter is constructed to derive a sufficient condition such that the filtering error dynamic MJSs are finite-time bounded and satisfies a prescribed level of H ∞ disturbance attenuation in a finite time-interval. Then, in terms of linear matrix inequalities (LMIs) techniques, the sufficient condition on the existence of finite-time H ∞ filter is presented and proved. The filter matrices can be solved directly by using the existing LMIs optimization techniques. Finally, two numerical examples are given to illustrate the effectiveness of the proposed design approach. [Copyright &y& Elsevier]

Abstract: The stochastic finite-time boundedness (FTB) problem is considered for a class of Markovian jumping neural networks (MJNNs) with time delay and uncertainties. By selecting the appropriate stochastic Lyapunov–Krasovskii functional, sufficient conditions of stochastic FTB of MJNNs are presented and proved. The FTB criteria are formulated in the form of linear matrix inequalities. Simulation results illustrate the effectiveness of the developed approaches. [Copyright &y& Elsevier]

Abstract: This paper studies output regulation for continuous-time Markovian jumping systems (MJSs), for which mode-dependent regulation equations are investigated. With the extension of regulation scheme to MJSs by stochastic Lyaponov–Krasovskii functional framework, sufficient conditions are, respectively, obtained for state feedback and error feedback. The resulting closed-loop system is guaranteed to be stochastically stable and the output regulation error almost asymptotically converges to zero. A semi-definite optimization approach via disciplined convex programming is adopted to ensure relaxed solutions of the regulation equations. Finally, two numerical simulations are given to illustrate the performance of the proposed approach. [Copyright &y& Elsevier]

In this paper we study the robust control problems with respect to the finite-time interval of uncertain non-linear Markov jump systems. By means of Takagi–Sugeno fuzzy models, the overall closed-loop fuzzy dynamics are constructed through selected membership functions. By using the stochastic Lyapunov–Krasovskii functional approach, a sufficient condition is firstly established on the stochastic robust finite-time stabilization. Then, in terms of linear matrix inequalities techniques, the sufficient conditions on the existence of the stochastic finite-time controller are presented and proved. Finally, the design problem is formulated as an optimization one. The simulation results illustrate the effectiveness of the proposed approaches. [ABSTRACT FROM PUBLISHER]

This paper studies the adaptive fault estimation problems for stochastic Markovian jump systems (MJSs) with time delays. With the aid of the selected Lyapunov-Krasovskii functional, the adaptive fault estimation algorithm based on adaptive observer is proposed to enhance the rapidity and accuracy performance of fault estimation. A sufficient condition on the existence of adaptive observer is presented and proved by means of linear matrix inequalities techniques. The presented results are extended to multiple time-delayed MJSs. Simulation results illustrate that the validity of the proposed adaptive faults estimation algorithms. [ABSTRACT FROM AUTHOR]

Abstract: This paper studies the robust fault detection filter (RFDF) design problems for uncertain nonlinear Markov jump systems with state delays and parameter uncertainties. By means of Takagi–Sugeno fuzzy models, the dynamics of filtering error generator and the fuzzy RFDF system are constructed. With the aid of the selected weighting matrix function, the design objective is to find an optimal RFDF which results in a minimal difference between the reference model (ideal solution) and the RFDF (real solution) to be designed. A sufficient condition is firstly established on the stochastic stability by using stochastic Lyapunov–Krasovskii functional approach. Then in terms of linear matrix inequalities techniques, sufficient conditions on the existence of fuzzy RFDF are presented and proved. Finally, the design problem is formulated as an optimization algorithm. Simulation results illustrate that the proposed RFDF can detect the faults shortly after the occurrences. [Copyright &y& Elsevier]

Abstract: This paper studied the proportional-integral (PI) control problems of stochastic Markovian jump systems (MJSs) with uncertain parameters. Under complete access to the system states, the PI controller design procedure turns to static output feedback control problem that make the closed-loop dynamics of this class of uncertain MJSs be robustly stochastically stable. A sufficient condition on the existence of PI controller is presented and proved by means of linear matrix inequality techniques. The presented results are extended to the case when the system states are not accessible. In order to make the relative equations approximate with a satisfactory precision, we described the problem as a semidefinite programming one via disciplined convex optimization. Simulation results illustrate the validity of the proposed algorithms. [Copyright &y& Elsevier]

Abstract: The stochastic finite-time boundedness problem is considered for a class of uncertain Markovian jumping neural networks (MJNNs) that possess partially known transition jumping parameters. The transition of the jumping parameters is governed by a finite-state Markov process. By selecting the appropriate stochastic Lyapunov–Krasovskii functional, sufficient conditions of stochastic finite time boundedness of MJNNs are presented and proved. The boundedness criteria are formulated in the form of linear matrix inequalities and the designed algorithms are described as optimization ones. Simulation results illustrate the effectiveness of the developed approaches. [Copyright &y& Elsevier]

This paper studies the robust stochastic stability problem for a class of Markov jump systems with norm bounded uncertain parameters and distributed time-delays. Integral inequality techniques together with Lyapunov-Krasovskii functional approach are employed to develop new delay-dependent sufficient conditions for stochastic stability. The main results are derived via linear matrix inequalities formulation. Simulation examples illustrate the effectiveness of the developed techniques. [ABSTRACT FROM AUTHOR]

Abstract: This paper provides the observer-based finite-time control problem of time-delayed Markov jump systems that possess randomly jumping parameters. The transition of the jumping parameters is governed by a finite-state Markov process. The observer-based finite-time H ∞ controller via state feedback is proposed to guarantee the stochastic finite-time boundedness and stochastic finite-time stabilization of the resulting closed-loop system for all admissible disturbances and unknown time-delays. Based on stochastic finite-time stability analysis, sufficient conditions that ensure stochastic robust control performance of time-delay jump systems are derived. The control criterion is formulated in the form of linear matrix inequalities and the designed finite-time stabilization controller is described as an optimization one. The presented results are extended to time-varying delayed MJSs. Simulation results illustrate the effectiveness of the developed approaches. [Copyright &y& Elsevier]

Abstract: The peak-to-peak filtering problem is studied for a class of Markov jump systems with uncertain parameters. By re-constructing the system, the dynamic filtering error system is obtained. The objective is to design a peak-to-peak filter such that the induced gain from the unknown inputs to the estimated errors is minimized or guaranteed to be less or equal to a prescribed value. By using appropriate stochastic Lyapunov–Krasovskii functional, sufficient conditions are initially established on the existence of mode-dependent peak-to-peak filter which also guarantees the stochastic stability of the filtering error dynamic systems. The design criterions are presented in the form of linear matrix inequalities and then described as an optimization problem. Simulation results demonstrate the validity of the proposed approaches. [Copyright &y& Elsevier]

Abstract: The unbiased H ∞ filtering problem is studied for stochastic Markov jump system with constant and neutral time-delays. By re-constructing the system, the dynamic filtering error characteristics of unknown inputs and time-delays are obtained. A sufficient condition is initially established on the existence of mode-dependent unbiased H ∞ filter of constant time-delay system using stochastic Lyapunov–Krasovskii function. Then, the unbiased H ∞ filter is also designed for the jump system with constant and neutral time-delays. The design criterions are presented in the form of linear matrix inequality. Finally, the unbiased H ∞ filtering problems are described as optimization algorithms. Numerical examples illustrate the effectiveness of the developed techniques. [Copyright &y& Elsevier]

This paper focuses on the issue of the finite-region H ∞ asynchronous control scheme, which is devoted to the transient behavior of a class of two-dimensional Markov jump systems. The disquisitive system is characterized based upon a Roesser model. Considering the fact that there exists an asynchronous phenomenon between the controlled plant and the controller, we introduce a hidden Markov model to address the non-synchronization. By resorting to a given conditional probability matrix, the mode jumps between the controlled plant and the controller are determined. To conclude, an example is employed to illustrate the potential applications of the devised approach. [ABSTRACT FROM AUTHOR]

In this paper, we consider the stochastically finite-time L 2 control problem for a class of positive stochastic Poisson jump systems (PSPJSs). By introducing a novel mode decoupling technique, some necessary and sufficient conditions are given to guarantee the stochastic finite-time boundedness of the input-free PSPJSs. Then, a proper mode-dependent finite-time state feedback controller is designed such that the positiveness, stochastic finite-time boundedness and the specified L 2 disturbance attenuation performance are attained simultaneously for the closed-loop SPJSs. Finally, two examples are given to show the feasibility and validity of the proposed methods. [ABSTRACT FROM AUTHOR]

The popular leafy vegetable lettuce (Lactuca sativa L.) is susceptible to cold stress during the growing season, which slows growth rate, causes leaf yellowing and necrosis, and reduced yield and quality. In this study, transcriptomic and metabolomic analyses of two cold-resistant lettuce cultivars (GWAS-W42 and F11) and two cold-sensitive lettuce cultivars (S13K079 and S15K058) were performed to identify the mechanisms involved in the cold response of lettuce. Overall, transcriptome analysis identified 605 differentially expressed genes (DEGs), including significant enrichment of genes involved in the flavonoid and flavonol (CHS, CHI, F3H, FLS, CYP75B1, HCT, etc.) biosynthetic pathways related to oxidation–reduction and catalytic activity. Untargeted metabolomic analysis identified fifteen flavonoid metabolites and 28 other metabolites potentially involved in the response to cold stress; genistein, quercitrin, quercetin derivatives, kaempferol derivatives, luteolin derivatives, apigenin and their derivatives accumulate at higher levels in cold-resistant cultivars. Moreover, MYBs, bHLHs, WRKYs and Dofs also play positive role in the low temperature response, which affected the expression of structural genes contributing to the variation of metabolites between the resistant and sensitive. These results provide valuable evidence that the metabolites and genes involved in the flavonoid biosynthetic pathway play important roles in the response of lettuce to cold stress. [ABSTRACT FROM AUTHOR]

• Fault detection scheme for conic nonlinear systems in finite frequency domain is designed. • Sufficient conditions to realize H_ fault sensitivity and H_ disturbance attenuation. • The fuzzy fault detection problem is transformed into an optimization algorithm. • A tunnel diode-circuit is given to confirm the validity of the designed scheme. In this paper, we focused on the issue of fault detection subject to a class of conic-type nonlinear systems in the finite frequency domain (FFD). Applying Takagi Sugeno (T-S) fuzzy models, the conic-type dynamic error system is established. To prove that the residual vector is robust to external disturbances and sensitive to faults, we provide some conditions to realize H − fault sensitivity performance and H ∞ disturbance attenuation performance within the FFD. Then, utilizing linear matrix inequalities techniques, the fuzzy fault detection observer design problem is transformed into an optimization algorithm. Finally, a numerical example related to a tunnel diode-circuit is given to confirm the validity of the designed scheme. [ABSTRACT FROM AUTHOR]

This paper addresses finite-time boundedness and stabilization problem for n -neuron uncertain positive Markovian jumping neural networks (MJNNs). Firstly, we analyze the positive MJNNs in the input-free case and then propose a sufficient condition to ensure the input-free finite-time boundedness. Then applying the state feedback scheme, a suitable finite-time stabilizable controller is devised to guarantee the positiveness of the closed-loop MJNNs. Moreover, some sufficient conditions for the existence of the controller gain solutions are proposed and proved by using the stochastic Lyapunov-Krasovskii functional approach and linear matrix inequalities techniques. Finally, we give two simulation examples to demonstrate the effectiveness and feasibility of the proposed methods. [ABSTRACT FROM AUTHOR]