Advances in Nonlinear and Stochastic System Control

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Automation Control Systems".

Deadline for manuscript submissions: 20 April 2024 | Viewed by 16669

Special Issue Editors

College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China
Interests: nonlinear systems; stochastic systems; robust control; adaptive control
Institute of Automation, Qufu Normal University, Qufu 273165, China
Interests: control theory of nonlinear and stochastic systems
School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
Interests: sliding mode control; stochastic system; finite-time control; motion control; vehicle dynamics and control
Institute of Automation, Qufu Normal University, Qufu 273165, China
Interests: stochastic nonlinear control; adaptive control
School of Automation and Software Engineering, Shanxi University, Taiyuan 030006, China
Interests: control of stochastic nonlinear systems; adaptive control

Special Issue Information

Dear Colleagues,

Most engineering problems existing in process control, industry production and manufacturing systems can be modeled as nonlinear systems or stochastic systems. Linear systems are ideal mathematical models which can be viewed as an approximation of nonlinear systems. Nonlinear systems control, compared with that of linear systems, has more applications in practice and exhibits more complexity in the theoretical analysis. In addition, as it is well known that randomness inevitably exists in various engineering fields, such as process control, fault detection, mathematical finance and systems biology, so stochastic control has become one of the most popular research areas.

Although nonlinear control and stochastic control have attracted the attention of many scholars and made great progress in recent years, there still exist many new and challenging issues in aspects of both theory and application, which cover the fields of process control, food production and processing, fault estimation, manufacturing systems, power systems, system stability and stabilization, etc. All these topics merit further study in terms of both theory and application.

This Special Issue “Advances in Nonlinear and Stochastic System Controls” will focus on the theory development and engineering applications of nonlinear/stochastic control systems. The following topics are welcome, though submissions are not limited to these:

  • Stability, stabilization and optimization in nonlinear systems and stochastic systems;
  • Modelling, simulation and identification in process supervision, process optimization and process control;
  • Nonlinear variable structure and sliding mode controller designs;
  • New theories and approaches in the study of nonlinear/stochastic systems, including adaptive control, robust control, fuzzy control, model-free control, reinforcement learning, etc.;
  • Applications of various nonlinear and stochastic control theories to food production and processing, finance, economics, insurance, online estimate, manufacturing systems, fault detection, networked control systems, power systems, etc.

Prof. Dr. Weihai Zhang
Prof. Dr. Xuejun Xie
Prof. Dr. Shihong Ding
Prof. Dr. Liang Liu
Dr. Zhenguo Liu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • nonlinear systems
  • stochastic systems
  • process control
  • nonlinear modeling and optimization
  • process supervision and fault detection

Published Papers (15 papers)

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Research

18 pages, 354 KiB  
Article
Infinite Horizon H2/H Control for Discrete-Time Mean-Field Stochastic Systems
by Chaoyue Ma and Ting Hou
Processes 2023, 11(11), 3248; https://doi.org/10.3390/pr11113248 - 18 Nov 2023
Viewed by 599
Abstract
In this paper, we deal with the H2/H control problem in the infinite horizon for discrete-time mean-field stochastic systems with (x,u,v)-dependent noise. First of all, a stochastic-bounded real lemma, which is the [...] Read more.
In this paper, we deal with the H2/H control problem in the infinite horizon for discrete-time mean-field stochastic systems with (x,u,v)-dependent noise. First of all, a stochastic-bounded real lemma, which is the core of H analysis, is derived. Secondly, a sufficient condition in terms of the solution of coupled difference Riccati equations (CDREs) is obtained for solving the H2/H control problem above. In addition, an iterative algorithm for solving CDREs is proposed and a numerical example is given for verification of the feasibility of the developed results. Full article
(This article belongs to the Special Issue Advances in Nonlinear and Stochastic System Control)
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18 pages, 2791 KiB  
Article
T-S Fuzzy Algorithm Optimized by Genetic Algorithm for Dry Fermentation pH Control
by Pengjun Wang, Xing Shen, Ruirong Li, Haoli Qu, Jie Cao, Yongsheng Chen and Mingjiang Chen
Processes 2023, 11(8), 2227; https://doi.org/10.3390/pr11082227 - 25 Jul 2023
Cited by 1 | Viewed by 650
Abstract
In the process of anaerobic dry fermentation to produce biogas, maintaining a suitable pH in the environment is more conducive to the degradation of crop straw. When the pH in the fermentation environment is too low, the process of anaerobic digestion by anaerobic [...] Read more.
In the process of anaerobic dry fermentation to produce biogas, maintaining a suitable pH in the environment is more conducive to the degradation of crop straw. When the pH in the fermentation environment is too low, the process of anaerobic digestion by anaerobic bacteria is inhibited. Therefore, it is necessary to quickly adjust the pH. In this work, we studied the control technology of a pH regulation system and then constructed a T-S fuzzy controller. Upon simplifying the T-S fuzzy controller, the system delay time was reduced, and two genetic algorithms with different fitness performance indicators were used to optimize the T-S fuzzy control. The simulation experiment in this study was designed through simulation software, and the results show that the improved control method has a fast regulation ability. Finally, on-site experiments were conducted using the four control methods under the acidification conditions set in the experimental device. The results show that the control method used in this study to improve performance by integrating the error sum of squares has a short control time and small oscillation and overshoot, and it can better regulate the environmental pH to achieve appropriate conditions when acidification occurs during anaerobic dry fermentation. Full article
(This article belongs to the Special Issue Advances in Nonlinear and Stochastic System Control)
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19 pages, 4325 KiB  
Article
Study on a Second-Order Adaptive Sliding-Mode Observer Control Algorithm for the Sensorless Permanent Magnet Synchronous Motor
by Guozhong Yao, Yuanpeng Cheng, Zhengjiang Wang and Yuhan Xiao
Processes 2023, 11(6), 1636; https://doi.org/10.3390/pr11061636 - 26 May 2023
Cited by 2 | Viewed by 989
Abstract
The control of a permanent magnet synchronous motor (PMSM) without a position sensor based on a sliding-mode observer (SMO) algorithm has a serious jitter problem in the process of motor phase tracking. A second-order adaptive sliding-mode observer algorithm was proposed, and the ideas [...] Read more.
The control of a permanent magnet synchronous motor (PMSM) without a position sensor based on a sliding-mode observer (SMO) algorithm has a serious jitter problem in the process of motor phase tracking. A second-order adaptive sliding-mode observer algorithm was proposed, and the ideas and principles of the second-order sliding-mode observer algorithm based on the super-twisting algorithm were elaborated. In particular, adaptive estimation with the introduction of back-electromotive force (EMF) was investigated, and the Lyapunov stability criterion was used to determine the convergence properties of the algorithm. The results showed that the second-order adaptive sliding-mode observer algorithm had better jitter suppression and a better phase tracking performance than the traditional sliding-mode observer algorithm. The experimental results showed that when the motor velocity was 800 r/min, the velocity error of the second-order adaptive sliding-mode observer algorithm was 0.57 r/min and the position error was 0.018 rad, with accuracy improvements of 93.63% and 58.34%, respectively. When the motor velocity was 1000 r/min, the velocity error of the second-order adaptive sliding-mode observer algorithm was 0.94 r/min and the position error was 0.022 rad, with accuracy improvements of 90.55% and 55.10%, respectively. The jitter of the system was suppressed well, the curve of back-EMF was smoother, and the robustness of the system was high. Therefore, the second-order adaptive sliding-mode observer algorithm is more suitable for the position-sensorless control of a PMSM. Full article
(This article belongs to the Special Issue Advances in Nonlinear and Stochastic System Control)
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15 pages, 2654 KiB  
Article
Anti-Overturning Capability and Fuzzy PID Speed Control for Four-Way Shuttle Vehicles in Processed Grain Storage
by Li Li, Zhaoyun Wu, Zhongwei Zhang and Yulan Zhang
Processes 2023, 11(5), 1355; https://doi.org/10.3390/pr11051355 - 28 Apr 2023
Viewed by 891
Abstract
As the four-way shuttle vehicle is prone to overturning in finished grain storage during acceleration and deceleration, an overturning mechanical model is constructed. The design factors analyzed include grain bag height, vehicle and grain bag mass, and the type of grain’s effect on [...] Read more.
As the four-way shuttle vehicle is prone to overturning in finished grain storage during acceleration and deceleration, an overturning mechanical model is constructed. The design factors analyzed include grain bag height, vehicle and grain bag mass, and the type of grain’s effect on the vehicle’s anti-overturning stability. The critical overturning condition of the shuttle vehicle during operation is also determined as a result of this analysis. With the critical overturning condition, the speed control of the shuttle vehicle based on the fuzzy PID method is carried out to improve the anti-overturning stability. Significant details are made about the fuzzification of input and output variables, determination of membership function, establishment of the fuzzy rule base, fuzzy reasoning, and defuzzification. Finally, the comparative simulation model of fuzzy PID and conventional PID in the MATLAB/Simulink platform showed that the fuzzy PID control method had the advantages of fast convergence and quick response to the speed control of the four-way shuttle vehicle. Full article
(This article belongs to the Special Issue Advances in Nonlinear and Stochastic System Control)
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17 pages, 676 KiB  
Article
Adaptive Coexistence of Synchronization and Anti-Synchronization for a Class of Switched Chaotic Systems
by Ling Ren and Chenchen Peng
Processes 2023, 11(2), 530; https://doi.org/10.3390/pr11020530 - 09 Feb 2023
Cited by 1 | Viewed by 919
Abstract
This paper addresses the problem of coexistence of synchronization and anti-synchronization (CSAS) for a class of switched chaotic systems by adaptive control method, where the switched system is realized by unified chaotic systems under arbitrary switching signal. Firstly, necessary and sufficient conditions for [...] Read more.
This paper addresses the problem of coexistence of synchronization and anti-synchronization (CSAS) for a class of switched chaotic systems by adaptive control method, where the switched system is realized by unified chaotic systems under arbitrary switching signal. Firstly, necessary and sufficient conditions for the CSAS of the chaotic systems are proposed from two perspectives, one is by analyzing the parity of the system expression, and the other is by decomposing the system. Secondly, according to the obtained necessary and sufficient conditions, two algorithms are given to search the synchronization variables and anti-synchronization variables in the chaotic systems. Thirdly, the CSAS of the switched chaotic system can be achieved by a designed adaptive global controller with only one input channel under the arbitrary switching signal. Finally, the numerical simulation results verify the validity and effectiveness of the method we obtained. Full article
(This article belongs to the Special Issue Advances in Nonlinear and Stochastic System Control)
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14 pages, 367 KiB  
Article
Nonlinearly Parametrized Modeling and Adaptive Control for a Generic Hypersonic Vehicle
by Shaohua Yang and Xia Li
Processes 2023, 11(1), 263; https://doi.org/10.3390/pr11010263 - 13 Jan 2023
Viewed by 963
Abstract
This paper constructs a nonlinearly parametrized hypersonic cruise vehicle model on the basis of the existing on-orbit flight data using a curve-fitting technique. The hypersonic cruise vehicle system is separated into two interconnected subsystem: an attitude subsystem with rotational dynamics and a velocity [...] Read more.
This paper constructs a nonlinearly parametrized hypersonic cruise vehicle model on the basis of the existing on-orbit flight data using a curve-fitting technique. The hypersonic cruise vehicle system is separated into two interconnected subsystem: an attitude subsystem with rotational dynamics and a velocity subsystem with engine dynamics. The continuous adaptive controllers are designed for two subsystems using a novel function bounding technique and appropriate coordinate transformations, respectively, which ensure the global boundedness of all signals and achieve the non-zero equilibrium point regulation of nonlinearly parametrized hypersonic vehicle systems. One of the implications of this result is that growing nonlinearities in the uncertain model of the hypersonic vehicle system may be allowed for global stabilization. A simulation result verifies the effectiveness of the proposed adaptive control scheme. Full article
(This article belongs to the Special Issue Advances in Nonlinear and Stochastic System Control)
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14 pages, 1726 KiB  
Article
Observer-Based Predefined-Time Attitude Control for Spacecraft Subject to Loss of Actuator Effectiveness
by Teng Cao, Huajun Gong and Bing Han
Processes 2022, 10(11), 2294; https://doi.org/10.3390/pr10112294 - 04 Nov 2022
Viewed by 1121
Abstract
The predefined-time tracking problem of spacecraft attitude systems with loss of actuator effectiveness and lumped disturbance including the external disturbance and system uncertainty is studied. In order to obtain the estimation of the actuator efficiency factor more quickly and accurately, a robust learning [...] Read more.
The predefined-time tracking problem of spacecraft attitude systems with loss of actuator effectiveness and lumped disturbance including the external disturbance and system uncertainty is studied. In order to obtain the estimation of the actuator efficiency factor more quickly and accurately, a robust learning observer is designed. Based on the fault reconstruction information of the learning observer and the predefined-time stability lemma, a predefined-time tracking fault-tolerant control scheme is proposed for the faulty spacecraft attitude system. The stability of the learning observer and the whole control system is verified by the Lyapunov stability theory. Finally, the effectiveness and advantages of the proposed scheme are illustrated by simulation results including comparisons with existing works. Full article
(This article belongs to the Special Issue Advances in Nonlinear and Stochastic System Control)
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12 pages, 519 KiB  
Article
An Approximate Method of System Entropy in Discrete-Time Nonlinear Biological Networks
by Xiangyun Lin, Xinrui Wang, Weihai Zhang, Rui Zhang and Cheng Tan
Processes 2022, 10(9), 1736; https://doi.org/10.3390/pr10091736 - 01 Sep 2022
Viewed by 902
Abstract
This study discusses the calculation of entropy of discrete-time stochastic biological systems. First, measurement methods of the system entropy of discrete-time linear stochastic networks are introduced. The system entropy is found to be characterized by system matrices of the discrete-time biological systems. Secondly, [...] Read more.
This study discusses the calculation of entropy of discrete-time stochastic biological systems. First, measurement methods of the system entropy of discrete-time linear stochastic networks are introduced. The system entropy is found to be characterized by system matrices of the discrete-time biological systems. Secondly, the system entropy of nonlinear discrete-time stochastic biological systems is discussed and is calculated based on a global linearization method. The approximation of the values of system entropy of nonlinear stochastic systems needs to solve an optimization problem that is constrained by a kind of linear matrix inequality (LMI). Finally, a practical biochemical system is provided to verify the effectiveness of the proposed calculation method. Full article
(This article belongs to the Special Issue Advances in Nonlinear and Stochastic System Control)
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13 pages, 931 KiB  
Article
Fast Finite-Time Stability and Its Application in Adaptive Control of High-Order Stochastic Nonlinear Systems
by Yixuan Yuan and Junsheng Zhao
Processes 2022, 10(9), 1676; https://doi.org/10.3390/pr10091676 - 23 Aug 2022
Cited by 1 | Viewed by 1071
Abstract
In this article, a new design method for an adaptive fast finite-time controller (FTC) is proposed for the finite-time stability (FTS) issue of a class of high-order stochastic nonlinear systems (HOSNSs) with unknown parameters. Using a power integrator technology and Lyapunov function approach, [...] Read more.
In this article, a new design method for an adaptive fast finite-time controller (FTC) is proposed for the finite-time stability (FTS) issue of a class of high-order stochastic nonlinear systems (HOSNSs) with unknown parameters. Using a power integrator technology and Lyapunov function approach, an adaptive state feedback controller is derived to ensure fast FTS of HOSNSs. The developed adaptive fast FTC is equipped with less settling time to obtain better steady-state accuracy compared with the traditional FTC. The effectiveness of the proposed adaptive control scheme is demonstrated by a numerical example. Full article
(This article belongs to the Special Issue Advances in Nonlinear and Stochastic System Control)
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13 pages, 341 KiB  
Article
State Feedback Stabilization for a Class of Upper-Triangular Stochastic Nonlinear Systems with Time-Varying Control Coefficients
by Xixi Sun, Haisheng Yu and Xiaoyu Xu
Processes 2022, 10(8), 1465; https://doi.org/10.3390/pr10081465 - 26 Jul 2022
Viewed by 1024
Abstract
The problem explored in this article concerns the stability of the state feedback control of the upper-triangular stochastic nonlinear systems whose control coefficients are time-varying. First, the state feedback control of the corresponding nominal system is carried out by utilizing the backstepping technique [...] Read more.
The problem explored in this article concerns the stability of the state feedback control of the upper-triangular stochastic nonlinear systems whose control coefficients are time-varying. First, the state feedback control of the corresponding nominal system is carried out by utilizing the backstepping technique combined with the appropriate Lyapunov function. Then, low-gain homogeneous domination technology and the efficient coordinate transformation method are adopted to realize the state feedback control of the original system and ensure the global asymptotic stability (GAS) in probability of the system. Finally, an example is given to illustrate the feasibility and correctness of the method. Full article
(This article belongs to the Special Issue Advances in Nonlinear and Stochastic System Control)
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18 pages, 1302 KiB  
Article
Pareto Optimal Strategy under H Constraint for Discrete-Time Stochastic Systems
by Xiushan Jiang, Qingti Pang, Dongya Zhao and Qingkang Zhang
Processes 2022, 10(7), 1344; https://doi.org/10.3390/pr10071344 - 11 Jul 2022
Viewed by 1074
Abstract
This paper investigates the Pareto optimal strategy of discrete-time stochastic systems under H constraint, in which the weighting matrices of the weighted sum cost function can be indefinite. Combining the H control theory with the indefinite LQ control theory, the generalized [...] Read more.
This paper investigates the Pareto optimal strategy of discrete-time stochastic systems under H constraint, in which the weighting matrices of the weighted sum cost function can be indefinite. Combining the H control theory with the indefinite LQ control theory, the generalized difference Riccati equations (GDREs) are obtained. By means of the solution of the GDREs, the Pareto optimal strategy with H constraint is derived, and the necessary and sufficient conditions for the existence of the strategy are presented. Then the Pareto optimal solution under the worst-case disturbance is solved. Finally, the efficiency of the obtained results is illustrated by a numerical example. Full article
(This article belongs to the Special Issue Advances in Nonlinear and Stochastic System Control)
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14 pages, 4938 KiB  
Article
Sigmoid-like Event-Triggered Security Cruise Control under Stochastic False Data Injection Attacks
by Pengfei Zhang, Hongtao Sun, Chen Peng and Cheng Tan
Processes 2022, 10(7), 1326; https://doi.org/10.3390/pr10071326 - 06 Jul 2022
Cited by 4 | Viewed by 1136
Abstract
This paper presents a Sigmoid-like event-triggered scheme (Sigmoid-like ETS) for security cruise control systems (CCSs) under stochastic false data injection (FDI) attacks. In order to improve the sensitivity of the ETS, a Sigmoid-like function is first proposed to adjust the event-triggered threshold, dynamically. [...] Read more.
This paper presents a Sigmoid-like event-triggered scheme (Sigmoid-like ETS) for security cruise control systems (CCSs) under stochastic false data injection (FDI) attacks. In order to improve the sensitivity of the ETS, a Sigmoid-like function is first proposed to adjust the event-triggered threshold, dynamically. In what follows, by considering a class of stochastic FDI attacks which obey Bernoulli distribution, the Sigmoid-like event-triggered security control strategy is proposed to ensure both the security and resource saving of the CCSs. Thus, a sufficient stability and stabilization criterion is well derived to present the co-design of an H control and event-triggered parameter. Finally, some simulation experiments are conducted to verify the effectiveness of the proposed Sigmoid-like event-triggered security cruise control for networked vehicles. Full article
(This article belongs to the Special Issue Advances in Nonlinear and Stochastic System Control)
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12 pages, 419 KiB  
Article
Delay-Dependent Stability of Impulsive Stochastic Systems with Multiple Delays
by Chunjie Xiao and Ting Hou
Processes 2022, 10(7), 1258; https://doi.org/10.3390/pr10071258 - 24 Jun 2022
Viewed by 947
Abstract
This paper associates with stability analysis of linear impulsive stochastic delay systems (ISDSs). Although many conclusions about the stability of ISDSs have been obtained based on Lyapunov’s method, relatively few research theories about delay-dependent stability with less conservativeness have been established. Therefore, we [...] Read more.
This paper associates with stability analysis of linear impulsive stochastic delay systems (ISDSs). Although many conclusions about the stability of ISDSs have been obtained based on Lyapunov’s method, relatively few research theories about delay-dependent stability with less conservativeness have been established. Therefore, we introduce an appropriate Lyapunov-Krasovskii functional (LKF) to work out this problem, and a novel delay-dependent exponential stability theorem is first deduced. On the other hand, when mean-square stability is considered, we present delay-dependent stability conditions, it is of interest to note that the proposed conditions do not depend on the size of delays in the diffusion term, which solves the problems of determining the mean-square stability of ISDSs for which the diffusion term delays are not available. In the end, two numerical examples are carried out to verify the feasibility of our conclusions. Full article
(This article belongs to the Special Issue Advances in Nonlinear and Stochastic System Control)
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15 pages, 338 KiB  
Article
Stochastic Stabilization for Discrete-Time System with Input Delay and Multiplicative Noise in Control Variable
by Cheng Tan, Jianying Di, Mingyue Xiang, Ziran Chen and Binlian Zhu
Processes 2022, 10(5), 989; https://doi.org/10.3390/pr10050989 - 16 May 2022
Cited by 3 | Viewed by 1263
Abstract
The stabilization problems for time-delay stochastic systems with multiplicative noise in the control variable are investigated in this paper. The innovative contributions are described as follows. Since the past work on stabilization is based on some delay-dependent algebraic Riccati equation (DARE), how to [...] Read more.
The stabilization problems for time-delay stochastic systems with multiplicative noise in the control variable are investigated in this paper. The innovative contributions are described as follows. Since the past work on stabilization is based on some delay-dependent algebraic Riccati equation (DARE), how to numerically calculate the stabilizing solution remains an unsolved and open problem. On the one hand, an iterative algorithm for computing the unique stabilizing solution of DARE is proposed, while the convergence property is also proved. On the other hand, the concepts of critical stabilization and essential destabilization are proposed as a supplement to stochastic stabilization in terms of spectrum technique. Moreover, the Lyapunov-based necessary and sufficient conditions are developed. Full article
(This article belongs to the Special Issue Advances in Nonlinear and Stochastic System Control)
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22 pages, 619 KiB  
Article
Stochastic Review Inventory Systems with Deteriorating Items; A Steady-State Non-Linear Approach
by Adel F. Alrasheedi, Khalid A. Alnowibet and Ibtisam T. Alotaibi
Processes 2022, 10(4), 781; https://doi.org/10.3390/pr10040781 - 16 Apr 2022
Cited by 1 | Viewed by 1430
Abstract
The primary goal of business organization is optimally maximizing their productivity and profit whilst reducing the cost resulting from lost sales and services given to their customers, which can be achieved by exceeding the balance between the demand and supply. Analyzing real-world situations, [...] Read more.
The primary goal of business organization is optimally maximizing their productivity and profit whilst reducing the cost resulting from lost sales and services given to their customers, which can be achieved by exceeding the balance between the demand and supply. Analyzing real-world situations, including integrated queuing-inventory systems, such as M/M/1-systems and M/M/1/-systems, can help business organizations reach this goal. This research analyzes integrated queuing-inventory systems with lost sales validated under a deterministic and uniformly distributed order size scheme under continuous review. The limited integrated inventory-queuing M/M/1/N-1-system was chosen as subject of our interest due to its closeness to reality. Thus, this system with exponentially distributed deteriorating products and random planning time with lost sales was simulated. This research aimed to analyze customers’ sanctification by studying the addition of the deterioration parameter γ to the model under consideration. The proposed model’s demand was based on Poisson, wherein service times and lead times are exponentially distributed. We also examined M/M/1/ and M/M/1/N-1-systems investigated by Shwarz et al. using the proposed method to solve the linear system of equations obtained from the steady-state system balance equations results obtained are compared to those obtained from simulating the Schwarz approach. The analyzed model was tested for different values of Q, demand rate λ, and γ. The obtained results showed a strong dependency between γ, Q, and λ, providing the needed information for decision-makers to reach their goals depending on the performance measure of interest. Full article
(This article belongs to the Special Issue Advances in Nonlinear and Stochastic System Control)
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