System States for a Series of Finite Queues

1972 ◽  
Vol 20 (6) ◽  
pp. 1137-1141 ◽  
Author(s):  
Brian J. Haydon
Keyword(s):  
Finite Queues ◽  
System States

Algorithmic Approach to Analysis of Queuing System with Finite Queues and Jump-like Priorities

2012 ◽  
Vol 44 (12) ◽  
pp. 43-54 ◽  
Author(s):  
Agasi Zarbali ogly Melikov ◽  
Leonid A. Ponomarenko ◽  
Che Soong Kim
Keyword(s):  
Queuing System ◽  
Algorithmic Approach ◽  
Finite Queues

scholarly journals A Taylor Series Approach for Service-Coupled Queueing Systems with Intermediate Load

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Ekaterina Evdokimova ◽  
Sabine Wittevrongel ◽  
Dieter Fiems
Keyword(s):  
Performance Measures ◽  
Queueing Systems ◽  
Poisson Processes ◽  
Series Expansions ◽  
Service Rate ◽  
Single Server ◽  
Queueing Model ◽  
State Space Explosion ◽  
Finite Queues ◽  
Service Rates

This paper investigates the performance of a queueing model with multiple finite queues and a single server. Departures from the queues are synchronised or coupled which means that a service completion leads to a departure in every queue and that service is temporarily interrupted whenever any of the queues is empty. We focus on the numerical analysis of this queueing model in a Markovian setting: the arrivals in the different queues constitute Poisson processes and the service times are exponentially distributed. Taking into account the state space explosion problem associated with multidimensional Markov processes, we calculate the terms in the series expansion in the service rate of the stationary distribution of the Markov chain as well as various performance measures when the system is (i) overloaded and (ii) under intermediate load. Our numerical results reveal that, by calculating the series expansions of performance measures around a few service rates, we get accurate estimates of various performance measures once the load is above 40% to 50%.

scholarly journals An Optimized Triggering Algorithm for Event-Triggered Control of Networked Control Systems

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1262
Author(s):  
Sunil Kumar Mishra ◽  
Amitkumar V. Jha ◽  
Vijay Kumar Verma ◽  
Bhargav Appasani ◽  
Almoataz Y. Abdelaziz ◽  
...  
Keyword(s):  
Control Systems ◽  
Networked Control Systems ◽  
Networked Control ◽  
Pendulum System ◽  
Uniform Sampling ◽  
Inverted Pendulum System ◽  
Event Triggering ◽  
Non Uniform Sampling ◽  
System States ◽  
Event Triggered

This paper presents an optimized algorithm for event-triggered control (ETC) of networked control systems (NCS). Initially, the traditional backstepping controller is designed for a generalized nonlinear plant in strict-feedback form that is subsequently extended to the ETC. In the NCS, the controller and the plant communicate with each other using a communication network. In order to minimize the bandwidth required, the number of samples to be sent over the communication channel should be reduced. This can be achieved using the non-uniform sampling of data. However, the implementation of non-uniform sampling without a proper event triggering rule might lead the closed-loop system towards instability. Therefore, an optimized event triggering algorithm has been designed such that the system states are always forced to remain in stable trajectory. Additionally, the effect of ETC on the stability of backstepping control has been analyzed using the Lyapunov stability theory. Two case studies on an inverted pendulum system and single-link robot system have been carried out to demonstrate the effectiveness of the proposed ETC in terms of system states, control effort and inter-event execution time.

scholarly journals New delay-dependent observer-based control for uncertain stochastic time-delay systems

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Xiu-feng Miao ◽  
Long-suo Li
Keyword(s):  
Time Delay ◽  
The State ◽  
Delay Systems ◽  
Linear Matrix ◽  
Time Delay Systems ◽  
Parameter Uncertainties ◽  
Noise Disturbances ◽  
System States ◽  
Delay Dependent ◽  
Stochastic Time

AbstractThis paper considers the problem of estimating the state vector of uncertain stochastic time-delay systems, while the system states are unmeasured. The system under study involves parameter uncertainties, noise disturbances and time delay, and they are dependent on the state. Based on the Lyapunov–Krasovskii functional approach, we present a delay-dependent condition for the existence of a state observer in terms of a linear matrix inequality. A numerical example is exploited to show the validity of the results obtained.

Robust Tracking Control for Takagi–Sugeno Fuzzy Systems With Unmeasurable Premise Variables: Application to Tank System

2014 ◽  
Vol 136 (4) ◽  
Author(s):  
H. Ghorbel ◽  
A. El Hajjaji ◽  
M. Souissi ◽  
M. Chaabane
Keyword(s):  
Tracking Control ◽  
Fuzzy Systems ◽  
Design Procedure ◽  
Control Design ◽  
Linear Matrix ◽  
Robust Tracking Control ◽  
Fuzzy Observer ◽  
Tank System ◽  
System States ◽  
Takagi Sugeno

In this paper, a robust fuzzy observer-based tracking controller for continuous-time nonlinear systems presented by Takagi–Sugeno (TS) models with unmeasurable premise variables, is synthesized. Using the H∞ norm and Lyapunov approach, the control design for TS fuzzy systems with both unmeasurable premises and system states is developed to guarantee tracking performance of closed loop systems. Sufficient relaxed conditions for synthesis of the fuzzy observer and the fuzzy control are driven in terms of linear matrix inequalities (LMIs) constraints. The proposed method allows simplifying the design procedure and gives the observer and controller gains in only one step. Numerical simulation on a two tank system is provided to illustrate the tracking control design procedure and to confirm the efficiency of the proposed method.

Causation Entropy Identifies Sparsity Structure for Parameter Estimation of Dynamic Systems

2016 ◽  
Vol 12 (1) ◽  
Author(s):  
Pileun Kim ◽  
Jonathan Rogers ◽  
Jie Sun ◽  
Erik Bollt
Keyword(s):  
Parameter Estimation ◽  
Time Series Data ◽  
Multivariate Time Series ◽  
Measurement Data ◽  
Relative Magnitude ◽  
Initial Guess ◽  
Series Data ◽  
System Parameters ◽  
Estimation Problems ◽  
System States

Parameter estimation is an important topic in the field of system identification. This paper explores the role of a new information theory measure of data dependency in parameter estimation problems. Causation entropy is a recently proposed information-theoretic measure of influence between components of multivariate time series data. Because causation entropy measures the influence of one dataset upon another, it is naturally related to the parameters of a dynamical system. In this paper, it is shown that by numerically estimating causation entropy from the outputs of a dynamic system, it is possible to uncover the internal parametric structure of the system and thus establish the relative magnitude of system parameters. In the simple case of linear systems subject to Gaussian uncertainty, it is first shown that causation entropy can be represented in closed form as the logarithm of a rational function of system parameters. For more general systems, a causation entropy estimator is proposed, which allows causation entropy to be numerically estimated from measurement data. Results are provided for discrete linear and nonlinear systems, thus showing that numerical estimates of causation entropy can be used to identify the dependencies between system states directly from output data. Causation entropy estimates can therefore be used to inform parameter estimation by reducing the size of the parameter set or to generate a more accurate initial guess for subsequent parameter optimization.

Design of Remote Controller Using Code Matching and Frequency Hopping Technology

2010 ◽  
Vol 44-47 ◽  
pp. 1412-1416
Author(s):  
Geng Sheng Zheng ◽  
Cheng Liang Li
Keyword(s):  
Frequency Hopping ◽  
Work Process ◽  
Sleep State ◽  
Prototype Implementation ◽  
Design And Implementation ◽  
Emergency Condition ◽  
Channel Interference ◽  
External Conditions ◽  
System States ◽  
Remote Controller

This paper presents the design and implementation of a RF remote controller using code matching and frequency hopping technology. The proposed controller supports access to different random channels under disturbance environment. The work process of RF remote controller is composed of code matching, running state, handover state, and sleep state. Four system states can transform each other under corresponding external conditions. The suggested controller is more reliable than conventional ones especially during emergency condition such as noise and co-channel interference. The feasibility of the architecture has been demonstrated with a prototype implementation and presented in details.

scholarly journals Extended-State-Observer-Based Super Twisting Control for Pneumatic Muscle Actuators

Actuators ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 35
Author(s):  
Yu Cao ◽  
Zhongzheng Fu ◽  
Mengshi Zhang ◽  
Jian Huang
Keyword(s):  
Control Method ◽  
Experimental Studies ◽  
State Observer ◽  
Extended State Observer ◽  
Extended State ◽  
Pneumatic Muscle ◽  
System States ◽  
The Stability ◽  
Twisting Control ◽  
Muscle Actuators

This paper presents a tracking control method for pneumatic muscle actuators (PMAs). Considering that the PMA platform only feedbacks position, and the velocity and disturbances cannot be observed directly, we use the extended-state-observer (ESO) for simultaneously estimating the system states and disturbances by using measurable variables. Integrated with the ESO, a super twisting controller (STC) is design based on estimated states to realize the high-precision tracking. According to the Lyapunov theorem, the stability of the closed-loop system is ensured. Simulation and experimental studies are conducted, and the results show the convergence of the ESO and the effectiveness of the proposed method.

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