Jump Systems Research Articles

Filtering for Nonlinear and Linear Markov Jump Systems

Filtering for Nonlinear and Linear Markov Jump Systems

Asynchronous Energy-to-Peak Filtering for Restricted Markov Jump Systems

Asynchronous Energy-to-Peak Filtering for Restricted Markov Jump Systems

Event‐based adaptive finite‐time control scheme with improved performance assurance for nonlinear Markov jumping systems

SummaryThis article investigates the adaptive finite‐time control design with performance assurance for nonlinear Markov jumping systems. First, the radial basis function neural networks are applied to tackle unknown nonlinear terms. Subsequently, within the framework of the command‐filtered backstepping control, the new error compensation signals are devised to remove the effect caused by filter error. Additionally, an adaptive finite‐time prescribed performance control law with an event‐triggered mechanism is developed to achieve a balance between tracking performance and bandwidth consumption, which ensures that the closed‐loop system is practically finite‐time stable in mean square and guarantees that the tracking error adjusts to the predetermined area. Finally, two simulation examples are provided to verify the validity and superiority of the devised scheme.

Cognitive and Motor Capacities Are Poorly Correlated with Agility in Early Pubertal Children: Gender-Stratified Analysis

This research aimed to identify relations of cognitive and power capacities with reactive agility in pubescent boys (n = 55) and girls (n = 46). Cognitive abilities were evaluated by the Stroop test, while the BlazePod system was used to evaluate agility performance conducting 20 yard shuttle and triangle tests of non-reactive (TCODS) and reactive agility (TRAG), respectively. Performance in jumping power was assessed through the squat jump (SJ), countermovement jump (CMJ), and drop jump (DHJ) utilising the Opto Jump system (Microgate, Bolzano, Italy), while sprinting ability over distances of 10 and 20 m was measured using a photocells system. A principal component was extracted from the four Stroop test variables using factor analysis. Forward stepwise multiple regression analysis was conducted separately for boys and girls to evaluate the multivariate relationships among the predictors and the criterion. Among boys, 80% of the TRAG variance was explained (MultipleR = 0.9), with TCODS and SJ as significant predictors (β = 0.53 and −1.01, respectively). For girls, the TCODS was the significant predictor (β = 0.65), explaining 43% of the variance (MultipleR = 0.65). These results show that (i) cognitive abilities measured with the Stroop test were not a reliable tool for predicting TRAG, (ii) jumping power was a significant predictor of TRAG in boys, and (iii) TCODS was a significant predictor of TRAG in girls. The findings indicated that cognitive abilities do not significantly influence reactive agility in pubescent children. It seems that power features have a greater influence on reactive agility, particularly in boys who have more developed motor skills at this age compared to girls.

Input-to-State Stabilization for Markov Jump Systems With Dynamic Quantization and Multimode Injection Attacks

Input-to-State Stabilization for Markov Jump Systems With Dynamic Quantization and Multimode Injection Attacks

Cooperative Design of Asynchronous Controller and Dynamic Packet Dropouts Compensator for Strictly Dissipative T–S Fuzzy Markov Jump Systems

Cooperative Design of Asynchronous Controller and Dynamic Packet Dropouts Compensator for Strictly Dissipative T–S Fuzzy Markov Jump Systems

Dynamic Event-Triggered Control for Delayed Nonlinear Markov Jump Systems under Randomly Occurring DoS Attack and Packet Loss

This paper aims to address the exponential stability and stabilization problems for a class of delayed nonlinear Markov jump systems under randomly occurring Denial-of-Service (DoS) attacks and packet loss. Firstly, the stochastic characteristics of DoS attacks and packet loss are depicted by the attack success rate and packet loss rate. Secondly, a Period Observation Window (POW) method and a hybrid-input strategy are proposed to compensate for the impact of DoS attack and packet loss on the system. Thirdly, A Dynamic Event-triggered Mechanism (DETM) is introduced to save more network resources and ensure the security and reliability of the systems. Then, by constructing a general common Lyapunov functional and combining it with the DETM and other inequality analysis techniques, the less conservative stability and stabilization criteria for the underlying systems are derived. In the end, the effectiveness of our result is verified through two examples.

Mismatched Quantized H ∞ Output-Feedback Control of Fuzzy Markov Jump Systems With a Dynamic Guaranteed Cost Triggering Scheme

Mismatched Quantized <i>H</i> _∞ Output-Feedback Control of Fuzzy Markov Jump Systems With a Dynamic Guaranteed Cost Triggering Scheme

Finite-Time H∞ Controllers Design for Stochastic Time-Delay Markovian Jump Systems with Partly Unknown Transition Probabilities.

This paper concentrates on the finite-time H∞ control problem for a type of stochastic discrete-time Markovian jump systems, characterized by time-delay and partly unknown transition probabilities. Initially, a stochastic finite-time (SFT) H∞ state feedback controller and an SFT H∞ observer-based state feedback controller are constructed to realize the closed-loop control of systems. Then, based on the Lyapunov-Krasovskii functional (LKF) method, some sufficient conditions are established to guarantee that closed-loop systems (CLSs) satisfy SFT boundedness and SFT H∞ boundedness. Furthermore, the controller gains are obtained with the use of the linear matrix inequality (LMI) approach. In the end, numerical examples reveal the reasonableness and effectiveness of the proposed designing schemes.

Finite-time Stabilization for Singular Markov Jump Systems with Generally Uncertain Transition Rates

Finite-time Stabilization for Singular Markov Jump Systems with Generally Uncertain Transition Rates

Stochastic LQ optimal control for Markov jumping systems with multiplicative noise using reinforcement learning

The stochastic linear quadratic (LQ) problem of discrete-time linear Markov jumping systems with multiplicative noise is investigated in this paper. Two reinforcement learning algorithms, one model-based and one model-free, are designed. The algorithms can be readily adapted to handle nonlinear cases by employing an appropriate function approximator. In the linear case, the network structure is designed to enable the problem to be solved without succumbing to modeling errors. For the model-free algorithm, an approach based on moving averages is proposed to reduce estimation variance. A proof of convergence is also provided. Finally, the effectiveness of the proposed algorithms is demonstrated through a numerical example.

Reinforcement Learning-Based Robust Tracking Control for Unknown Markov Jump Systems and its Application

Reinforcement Learning-Based Robust Tracking Control for Unknown Markov Jump Systems and its Application

Asynchronous Sliding-Mode Control for Discrete-Time Networked Hidden Stochastic Jump Systems With Cyber Attacks.

In this study, asynchronous sliding-mode control (SMC) for discrete-time networked hidden stochastic jump systems subjected to the semi-Markov kernel (SMK) and cyber attacks is investigated. Considering the statistical characteristic of the SMK, which is challenging to acquire in engineering, this study recognizes the SMK to be incomplete. Due to the mode mismatch between the original system and the control law in the operating process, a hidden semi-Markov model is proposed to describe the considered asynchronous situation. The main aim of this study is to construct an asynchronous SMC mechanism based on an incomplete SMK framework under the condition of random denial-of-service attacks so that the resulting closed-loop system can realize the mean-square stability. By virtue of the upper bound of the sojourn time in each mode, innovative techniques are developed for mean-square stability analysis under an incomplete SMK. Furthermore, an asynchronous SMC scheme is designed to achieve the reachability of the quasi-sliding mode. Finally, the effectiveness is verified using an electronic throttle model.

Coding–Decoding-Based Sliding Mode Control for Markovian Jump Systems Under Constrained Bit Rate: An Adaptive Quantizer Approach

This paper investigates the asynchronous sliding mode control (SMC) issue for uncertain hidden Markovian jump systems (MJSs) under constrained bit rate. An improved coding-decoding procedure with state-dependent adaptive quantization parameters is established to enable the controller to decode state and mode information from the system and the detector, respectively. Based on this procedure, a decoded-data-based asynchronous SMC strategy is provided and sufficient conditions are developed to ensure that the closed-loop dynamics are exponentially ultimately bounded and the system state is driven onto a sliding region simultaneously in the sense of mean square. The desired parameters of the quantizer and controller are obtained by solving an optimization problem, in which the objective function is constructed by using the trade-off between the ultimate state bound and the decay rate. Moreover, the integrative design of bit rate allocation protocol and quantizer as well as control parameters are converted into a nonlinear programming problem with integer constraint, which is solved by means of an improved sparrow search algorithm. Finally, a direct current motor system is employed to illustrate the effectiveness of the present approach under three different cases.

The Strictly Dissipative Condition of Continuous-Time Markovian Jump Systems with Uncertain Transition Rates

This study addresses the problem of strictly dissipative stabilization for continuous-time Markovian jump systems (MJSs) with external disturbances and generally uncertain transition rates that contain completely unknown transition rates and their bound values. A stabilization condition is obtained to guarantee strict dissipativity for the MJSs with partial knowledge in terms of the transition rates. To reduce the conservativity of the proposed condition, we used a boundary condition related to the bounds of the transition rate with slack variables. Finally, two simulation results are presented to describe the feasibility of the proposed controller.

Short- to Mid-Term Clinical and Radiological Results of Selective Laser Melting Highly Porous Titanium Cup in Primary Total Hip Arthroplasty.

(1) Background: The aim of this study was to evaluate short- to mid-term clinical and radiological results in patients undergoing primary total hip arthroplasty (THA) with the use of a Selective Laser Melting 3D-printed highly porous titanium acetabular cup (Jump System Traser®, Permedica Orthopaedics). (2) Methods: We conducted a retrospective study and collected prospective data on 125 consecutive patients who underwent primary THA with the use of highly porous titanium cup. Each patient was evaluated preoperatively and postoperatively with a clinical and radiological assessment. (3) Results: The final cohort consisted of 104 patients evaluated after a correct value of 52 (38-74) months. The median Harris Hip Score (HHS) significantly improved from 63.7 (16-95.8) preoperatively to 94.8 (38.2-95.8) postoperatively (p < 0.001), with higher improvement associated with higher age at surgery (β = 0.22, p = 0.025). On postoperative radiographs, the average acetabular cup inclination and anteversion were 46° (30°-57°) and 15° (1°-32°), respectively. All cups radiographically showed signs of osseointegration with no radiolucency observed, or component loosening. (4) Conclusions: The use of this highly porous acetabular cup in primary THA achieved excellent clinical, functional, and radiological results at mid-term follow-up. A better clinical recovery can be expected in older patients. The radiological evaluation showed excellent osseointegration of the cup with complete absence of periprosthetic radiolucent lines.

Collaborative Optimization Design of Event-based Asynchronous Filter for Discrete-time T-S Fuzzy Markov Jump Systems

Collaborative Optimization Design of Event-based Asynchronous Filter for Discrete-time T-S Fuzzy Markov Jump Systems

Fault-Tolerant Reduced-Order Asynchronous Networked Filtering of 2-D Bernoulli Jump Systems

Fault-Tolerant Reduced-Order Asynchronous Networked Filtering of 2-D Bernoulli Jump Systems

Event-Triggered Distributed Fusion Estimator for Asynchronous Markov Jump Systems with Correlated Noises and Fading Measurements.

In this study, we investigate event-triggered distributed fusion estimation for asynchronous Markov jump systems subject to correlated noises and fading measurements. The measurement noises are interrelated, and they are simultaneously coupled with the system noise. The sensor samples measurements uniformly, and the sampling rates of the sensors are different. First, the asynchronous system is synchronized at state update points; then, the local filter is obtained. Furthermore, a variance-based event-triggered strategy is introduced between the local estimator and the fusion center to decrease the energy consumption of network communication. Then, a distributed fusion estimation algorithm is proposed using a matrix-weighted fusion criterion. Finally, the effectiveness of the algorithm is verified using computer simulations.

Control of 2-D Semi-Markov Jump Systems: A View from Mode Generation Mechanism

Control of 2-D Semi-Markov Jump Systems: A View from Mode Generation Mechanism