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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]

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]

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]

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]

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]

This work addresses a time‐sensitive coverage control problem for multiple non‐holonomic mobile robots. The coverage objective is evaluated by the total arrivial time of robots reaching their dominant clients with the predefined constant but heterogeneous velocities. An extremum‐seeking control framework is proposed, including a numerical optimizer that iteratively produces the optimal waypoints of robots minimizing the total arriving time and a state regulator that drives the robot's positions to the optimal locations under both constraints non‐holonomic kinematic model and the constant‐velocity. An improved K‐means algorithm is first designed to produce the waypoint sequence. A theoretical analysis of the convergence of coverage objectives is provided. Then a fixed‐time state regulator for the robot's angular velocity is derived from regulating robot positions to the desired waypoints within each time step that varies with the heterogeneous traversing velocity and the distance between waypoints. Finally, the results are validated by a virtual robotic simulation platform and the experiment on real robots, showing that the proposed methods can efficiently deploy multiple heterogeneous robots for time‐sensitive services to clients with a discrete distribution. The simulation and experimental code are open‐sourced at https://gitee.com/ahu‐icip/simulation.git. [ABSTRACT FROM AUTHOR]

In this paper, we aim to investigate the exponential stability of general hybrid stochastic functional differential systems with delayed impulses. By using the average impulsive interval and the Lyapunov function method, we derive some sufficient conditions for exponential stability, which are less conservative than those existing results based on the supremum or infimum of impulsive interval and more convenient to be applied than those Razumikhin-type conditions in the literature. Meanwhile, we show that unstable hybrid stochastic delay differential systems, both linear and nonlinear, can be stabilized by suitably impulsive sequence. Finally, two examples are discussed to illustrate the effectiveness and advantages of the obtained results. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

An online adaptive optimal control problem for a class of nonlinear Markov jump systems (MJSs) is studied. It is worth noting that the dynamic information of MJSs is partially unknown. Applying the neural network linear differential inclusion techniques, the nonlinear terms in MJSs are approximately converted to linear forms. By using subsystem transformation schemes, we can transfer the nonlinear MJSs to N new coupled linear subsystems. Then a new online policy iteration algorithm is put forward to obtain the adaptive optimal controller. Some theorems are given afterward to ensure the convergence of the new algorithm. At last, a simulation example is provided to verify the applicability of the algorithm. [ABSTRACT FROM AUTHOR]

For a class of conic‐type non‐linear time‐delay Markov jump systems, the asynchronous dissipative output feedback controller based on the guaranteed cost control and quantiser is designed in this study. In real applications, the system and the controller modes are always non‐synchronous, so we introduce the hidden Markov model to solve this problem. Furthermore, we define three novel auxiliary variables and use quantisers to accomplish the output feedback controller design. Then, the finite‐time boundedness and strict dissipativity of the closed‐loop systems are guaranteed by sufficient conditions, and the controller also meets the guaranteed cost‐control performance. By solving a set of linear matrix inequalities, we get the controller gains, the guaranteed cost control performance index J*, and the dissipative performance index α. Finally, the correctness and feasibility of this designed approach are demonstrated by a given example. [ABSTRACT FROM AUTHOR]

The asynchronous resilient observer design problem for a class of non‐linear switched systems with time‐delays and uncertainties in a given finite‐time interval is studied here. By constructing appropriate multiple Lyapunov–Krasovskii functions and applying the average dwell‐time method, the switching law and the asynchronous resilient observer are designed to guarantee the finite‐time boundedness of the augment system with a specified H∞ performance. The resilient observer design problems can be derived to solve a set of linear matrix inequalities. A numerical simulation is employed to demonstrate the availability of the proposed methods. [ABSTRACT FROM AUTHOR]

Summary: Anthocyanins protect plants from biotic and abiotic stressors and provide great health benefits to consumers. In this study, we cloned four genes (Red Lettuce Leaves 1 to 4: RLL1 to RLL4) that contribute to colour variations in lettuce. The RLL1 gene encodes a bHLH transcription factor, and a 5‐bp deletion in some cultivars abolishes its function to activate the anthocyanin biosynthesis pathway. The RLL2 gene encodes an R2R3‐MYB transcription factor, which was derived from a duplication followed by mutations in its promoter region. The RLL3 gene encodes an R2‐MYB transcription factor, which down‐regulates anthocyanin biosynthesis through competing with RLL2 for interaction with RLL1; a mis‐sense mutation compromises the capacity of RLL3 to bind RLL1. The RLL4 gene encodes a WD‐40 transcription factor, homologous to the RUP genes suppressing the UV‐B signal transduction pathway in Arabidopsis; a mis‐sense mutation in rll4 attenuates its suppressing function, leading to a high concentration of anthocyanins. Sequence analysis of the RLL1‐RLL4 genes from wild and cultivated lettuce showed that their function‐changing mutations occurred after domestication. The mutations in rll1 disrupt anthocyanin biosynthesis, while the mutations in RLL2, rll3 and rll4 activate anthocyanin biosynthesis, showing disruptive selection for leaf colour during domestication of lettuce. The characterization of multiple polymorphic genes in this study provides the necessary molecular resources for the rational breeding of lettuce cultivars with distinct levels of red pigments and green cultivars with high levels of health‐promoting flavonoids. [ABSTRACT FROM AUTHOR]