In this paper, the problem of sampled-data synchronization for Markovian jump neural networks with time-varying delay and variable samplings is considered. framework input approach linear matrix inequality technique, two delay-dependent criteria are derived to ensure stochastic stability error systems, thus, master systems stochastically synchronize slave systems. The desired mode-independent controller designed, which depends upon maximum sampling interval. effectiveness potential obtained...

In this paper, a sampled-data fuzzy controller is designed to stabilize class of chaotic systems. A Takagi-Sugeno (T-S) model employed represent the Based on general model, exponential stability issue closed-loop systems with an input constraint first investigated by novel time-dependent Lyapunov functional, which positive definite at sampling times but not necessary between times. Then, two sufficient conditions are developed for synthesis underlying T-S or without constraint. All proposed...

This paper is concerned with the problems of stability and dissipativity analysis for static neural networks (NNs) time delay. Some improved delay-dependent criteria are established NNs time-varying or time-invariant delay using partitioning technique. Based on these criteria, several sufficient conditions given to guarantee All results in this not only dependent upon but also number partitions. examples illustrate effectiveness reduced conservatism proposed results.

This paper studies the problem of sampled-data exponential synchronization complex dynamical networks (CDNs) with time-varying coupling delay and uncertain sampling. By combining time-dependent Lyapunov functional approach convex combination technique, a criterion is derived to ensure stability error dynamics, which fully utilizes available information about actual sampling pattern. Based on condition, design method desired controllers proposed make CDNs exponentially synchronized obtain...

This paper studies the problem of sampled-data control for master-slave synchronization schemes that consist identical chaotic Lur'e systems with time delays. It is assumed sampling periods are arbitrarily varying but bounded. In order to take full advantage available information about actual pattern, a novel Lyapunov functional proposed, which positive definite at times not necessarily inside intervals. Based on functional, an exponential criterion derived by analyzing corresponding error...

The balance between exploration and exploitation is a key problem for reinforcement learning methods, especially Q-learning. In this paper, fidelity-based probabilistic Q-learning (FPQL) approach presented to naturally solve applied control of quantum systems. approach, fidelity adopted help direct the process probability each action be selected at certain state updated iteratively along with process, which leads natural strategy instead pointed one configured parameters. A (PQL) algorithm...

This brief investigates the problem of global exponential stability analysis for discrete recurrent neural networks with time-varying delays. In terms linear matrix inequality (LMI) approach, a novel delay-dependent criterion is established considered via new Lyapunov function. The obtained condition has less conservativeness and number variables than existing ones. Numerical example given to demonstrate effectiveness proposed method.

This paper investigates the problem of robust passive control for networked fuzzy systems, where randomly occurring uncertainties, variable sampling intervals, and constant network-induced delay are taken into account. A discontinuous Lyapunov functional is introduced closed-loop which takes full advantage sawtooth structure time-varying interval induced by sample-and-hold signal transmission. sufficient condition proposed to ensure system be robustly stochastically passive. Then, solved....

A novel quantum-inspired reinforcement learning (QiRL) algorithm is proposed for navigation control of autonomous mobile robots. The QiRL adopts a probabilistic action selection policy and new strategy, which are inspired, respectively, by the collapse phenomenon in quantum measurement amplitude amplification computation. Several simulated experiments Markovian state transition demonstrate that more robust to rates initial states than traditional learning. approach then applied real robot,...

In this letter, we propose a lightweight yet effective Topology Guided Kinodynamic planner (TGK-Planner) for quadrotor aggressive flights with limited onboard computing resources. The proposed system follows the traditional hierarchical planning workflow, novel designs to improve robustness and efficiency in both pathfinding trajectory optimization sub-modules. Firstly, topology guided graph, which roughly captures topological structure of environment guides state sampling sampling-based...

Purpose The purpose of this paper is to develop a condition‐based replacement and spare provisioning policy for deteriorating systems with number identical units. Design/methodology/approach deterioration units modeled based on discrete‐time Markov chains, which can be classified into one finite states. Then, proposed This combines the ( S , s ) type inventory policy, where maximum stock level reorder level. Monte Carlo approach utilized evaluating average cost rate system under policy....

A linear matrix inequality (LMI) approach to the robust state feedback H∞ control for discrete singular systems with norm-bounded uncertainty is developed. By taking relationship between slow and fast subsystems of a system, new bounded real lemma proposed that proves be sufficient necessary. On basis this, result on performance obtained. An explicit expression desired controllers also given involves no system decomposition. The obtained results are formulated in terms strict LMIs....