Behavior Of Control System Research Articles

Anti-windup higher derivative Newton-based extremum seeking under input saturation

The physical constraint of actuators in practical systems, such as actuator magnitude saturation, can significantly impact the behaviour of control systems. To address this issue, a fast learning mechanism is introduced in this paper for constrained input in higher derivatives Newton-based extremum seeking. The approach employs a constrained optimisation method with an anti-windup loop based on a wide range of penalty functions to adapt the search and prevent the violation of constraints, thereby avoiding windup of integral action in a controller. The practical asymptotic stability of the proposed algorithm is proven through a modified singular perturbation method, and its effectiveness is validated through simulations.

Investigating the impact of discretization techniques on real-time digital control of DC-DC boost converters: A comprehensive analysis

This paper provides a thorough comparative analysis of discretization techniques commonly utilized in digital control applications for DC-DC boost converters (DBCs). Given the crucial role of DC-DC converters in various industries such as renewable energy systems, electric vehicles, and portable electronic devices, it is imperative to optimize their performance through efficient digital control. This study aims to improve the understanding of the effects of discretization methods on control system behaviour. It investigates their impact on the performance, stability and accuracy of control algorithms in the context of DBC, using dSPACE real-time interface (RTI) and hardware-in-the-loop (HIL) simulation for validation. This approach replicates real-world conditions, allowing performance to be evaluated in a controlled environment. The analysis examines behaviour in the time and frequency domains, providing insight into the strengths and weaknesses of each method. Experimental validation using MATLAB/Simulink/Stateflow on dSPACE RTI 1007 processor, DS2004 high-speed A/D and CP4002 timing and digital I/O boards ensures that the comparative analysis provides practical benefits for DBC digital control applications.

Disorders of compulsivity: Deficits in arbitrating learning strategies.

While previous research has shown that compulsivity is related to an imbalance between goal-directed and habitual learning systems, very little is known about whether this effect is due to the impairment of a single system or the impairment of the arbitration mechanism that determines which system controls behaviour at any given moment; the current study aims to address this disagreement. Nineteen alcohol use disorder, 30 obsessive-compulsive disorder (OCD) and 20 major depressive disorder patients and corresponding sex- and age-matched controls performed two-choice, three-stage Markov decision-making paradigm. Model-based and mode-free reinforcement learning models were used to independently fitted their behavioural data. Alcohol use disorder and OCD patients showed less model-based strategy choice than healthy controls in task conditions where the model-based strategy was optimal. Only OCD patients showed higher behavioural control system switching in task conditions where model-free use was optimal. Major depressive disorder patients did not differ from the matched control in both. These findings suggest that dysfunction in arbitration control between dual systems may be the basis for diverse disorders involving compulsivity.

Pengaruh Penerapan Akuntansi Sektor Publik dan Kualitas Aparatur Pemerintah terhadap Pencegahan Fraud Laporan Keuangan (Studi Empiris pada Kota Pekalongan)

This study discusses how the application of public sector accounting and the quality of government officials in preventing financial reporting fraud in the Pekalongan city government and the purpose of this study is to examine how fraud prevention is influenced by organizational ethical behavior and internal control systems. BPK found a number of problems in cases of low quality financial reporting and non-compliance with statutory provisions. Methodology Approach, Design and Methodology Participants in this study consisted of OPD staff in Pekalongan City totaling 61 respondents and for the sample using Purposive sampling is a sampling technique, while direct surveys and questionnaire distribution are survey methods. Analysis with the Smart PLS Version 3.0 Application. Based on the research findings, the SAP implementation variables and the quality of government officials have a significant effect on preventing financial reporting fraud.

Алгоритмы передачи информации в системах управления биологическими объектами

One of the problems of the theory of management of objects with a high degree of uncertainty of behavior is solved: the development of theoretical foundations of analysis, modeling methods and improvement of bio cybernetic systems, their algorithmic and software necessary to improve the efficiency of the management process is proposed. To solve this problem, it is proposed to use the mathematical apparatus of information theory, on the basis of which the information characteristics of the control signal transmission channel from the source to the control object through the external environment are calculated, taking into account the noise of the ecosystem of the control object. The existing systems using monomodal control signals that do not carry a semantic load are analyzed, and the disadvantages and limited possibilities of improving the control systems under consideration are described. Using the example of one of the insect behavior control systems with a trichromic view, a comparison of the results obtained using various technical means used as control signal sources was performed. For improving the efficiency of control systems, which use a multimodal control signal structure, proposed various algorithms for constructing control systems using a multimodal control signal structure are considered, namely: serial and parallel circuits, combined, combining serial and parallel algorithms for using control signal sources. As a method for further improving the efficiency of control systems for biological objects with a high degree of uncertainty, it is proposed to use biological signals containing a large semantic load for the control object, which determines its behavioral response. The directions of further research are formulated in order to maximize the amount of information transmitted to the control object.

Optimization-Based Ramping Reserve Allocation of BESS for AGC Enhancement

The transient behavior of Automatic Generation Control (AGC) systems is a critical aspect of power system operation. Therefore, fully extracting the potential of Battery Energy Storage Systems (BESSs) for AGC enhancement is of paramount importance. In light of the challenges posed by diverse resource interconnections and the variability associated, we propose an online optimization scheme that can adapt to changes in an unknown and variable environment. To leverage the synergy between BESSs and Conventional Generators (CGs), we devise a variant of the Area Injection Error (AIE) as a measure to quantify the ramping needs. Based on this measure, we develop a distributed optimization algorithm with adaptive learning rates for the allocation of the ramping reserve. The algorithm restores a larger learning rate for compliance with the ramping needs upon detecting a potentially destabilizing event. We demonstrate the effectiveness and scalability of the proposed scheme through comprehensive case studies. It is shown that the proposed scheme can improve the transient behavior of the AGC system by bridging the gap in ramping capability.

Modeling the influence of management control system and ambidextrous behavior on B2B customer relationships: a job demand-resource perspective

PurposeService–sales ambidexterity (SSA) offers sales managers crucial information about dealing with customer service failures through an effective management control system. This study aims to scrutinize the relationships among SSA, salesforce control system, salesperson’s role stressors and service recovery performance (SRP) in the business-to-business (B2B) context.Design/methodology/approachAn analysis is conducted based on survey data collected from 586 B2B sales employees participating in an extensive survey. Structural equation modeling is used to analyze the proposed hypotheses.FindingsEmpirical findings suggest that behavior-based control harms SSA. On the other hand, outcome-based control has a positive impact on SSA. The research outcomes further disclose that SSA positively impacts salesperson role conflict and emotional fatigue, whereas emotional fatigue negatively impacts SRP. Salesperson resilience notably moderates the association between SSA and emotional fatigue.Originality/valueThe study addresses there is a dearth of research on SSA applying the sales management control system. When studying about ambidexterity in sales context, many supervisory styles have been explored; however, to the best of the authors’ knowledge, this is the first systematic attempt to understand how sales management control systems play a role in SSA.

On Border-Collision Bifurcations in a Pulse System

Considering a piecewise smooth map describing the behavior of a pulse-modulated control system, we discuss border-collision related phenomena. We show that in the parameter space which corresponds to the domain of oscillatory mode a mapping is piecewise linear continuous. It is well known that in piecewise linear maps, classical bifurcations, for example, period doubling, tangent, fold bifurcations become degenerate (“degenerate bifurcations”), combining the properties of both smooth and border-collision bifurcations. We found unusual properties of this map, that consist in the fact that border-collision bifurcations of codimension one, including degenerate ones, occur when a pair of points of a periodic orbit simultaneously collides with two switching manifolds. This paper also discuss bifurcations of chaotic attractors such as merging and expansion (“interior”) crises, associated with homoclinic bifurcations of unstable periodic orbits.

Comprehensive Assessment of the Seismic Performance of an Innovative Hybrid Semiactive and Passive State Control System for a Low-Degree-of-Freedom Structure Using Real-Time Hybrid Simulation

The dynamic performance of base isolation systems provides an effective means to reduce the seismic vulnerability of buildings. However, large displacements in the base isolation during seismic events pose a major challenge for this control system. Recently, novel control systems have been implemented to control and reduce the excessive displacements. This study presents an evaluation of the seismic performance of unconnected-fiber-reinforced elastomeric isolators (U-FREI) and variable orifice damper (VOD) devices used together as a hybrid control system for a low-degree-of-freedom reference structure by employing real-time hybrid simulation (RTHS) testing technique. This physical cybernetic testing methodology allows a dynamic system of interest to be substructured into two components: numerical and experimental. In this study, the numerical substructure corresponds to a 2-degree of freedom model, representing a reference structure, and an experimental substructure was formed using the hybrid control system described. To develop an interface between the two substructures, a horizontal transfer system (HTS) was implemented and coupled with a vertical transfer system (VTS). Using RTHS, the performance of the reference structure and the hybrid control system was evaluated under six seismic events: CAM, CAT, El Centro, Loma Prieta, Pizarro, and Chihuahua, at a maximum acceleration of 0.10 g (0.981 m·s−2). The experimental behavior of the hybrid control system allows the reference structure to reduce its maximum drift by more than 24% compared to the fixed structure. Finally, the performance and accuracy of the RTHS tests were calculated.

Approximate averaged bounded synthesis for a parabolic process with two switching points

In this paper we analyze the problem of the optimal bounded control with semi-definite quality criterion for parabolic process with rapidly oscillating coefficients on finite time interval. The case when optimal control goes out both on lower, and on upper restriction, that is has two switch-points is considered. Our aim is to build a synthesized control which is practically preferable to program one. But after Fourier method application such a control will contain coefficients which are expressed by series and, in addition, it irregularly depends on small parameter ε. Thus, for practical application it is natural to restrict infinite series by finite sums and to get rid of dependence on a small parameter using average procedure. So, besides the law of optimal synthesis also approximate averaged feedback control, which provides control system behavior that is close to optimal one and thus has a series of advantages from the practical application point of view, is proposed and proved. The efficiency of approximate averaged control construction procedure consisted of cutting to finite sums of series in optimal control and replacing of Fourier coefficients nonregular depended on small parameter by corresponding average values is illustrated by an example of controlled system for parabolic process. We compare the properties of the averaged control and the sequence of optimal controls calculated at the different values of the small parameter. For comparison, we use the switching points of optimal control and averaged control, deviation between optimal control and averaged control, the difference in the values of the quality criterion on optimal control and averaged control. In considered example the precision of quality criteria value on approximate control has ε-order and for sufficiently small ε the precision is one order better then ε.

Computational Fluid Dynamics analysis on behavior of over-speed control system using a movable arm

Computational Fluid Dynamics analysis on behavior of over-speed control system using a movable arm

Nonlinear Modeling Analysis of Stabilization Behavior of Robotic Gait Control System Based on Image Processing Techniques

Abstract Existing robot gait control methods have problems such as high gait energy consumption and difficulty in generating optimal gait strategies. This paper designs a robot gait automatic control system based on the X86 platform and robot sensor interface. The main board of the robot controller is designed based on CISC, which ensures high stability and anti-interference capabilities. The information provided by ultrasonic sensors and infrared sensors is used to adjust and execute the robot’s trajectory, action sequence, and gait. To extract the target in the gait image, the frame difference algorithm is employed, and the phase and amplitude factors are collected after the Radon and Fourier-Mellin transform to identify gait characteristics for robot gait recognition. The robot’s two-dimensional spatial dynamics model is constructed continuously, and its dynamics equations are derived. The residual fusion technique is used to combine image data with sensor data. A system for stabilizing gait control has been designed. The tracking error rate of the robot is not more than ±10% in general, and a variety of gait patterns can be used to cross the obstacles, which verifies the effectiveness of the designed system for realizing the gait control and performance of the robot.

Alternating current servo motor and programmable logic controller coupled with a pipe cutting machine based on human-machine interface using dandelion optimizer algorithm - attention pyramid convolution neural network

<abstract> <p>The proposed research addresses the optimization challenges in servo motor control for pipe-cutting machines, aiming to enhance performance and efficiency. Recognizing the existing limitations in parameter optimization and system behavior prediction, a novel hybrid approach is introduced. The methodology combines a Dandelion optimizer algorithm (DOA) for servo motor parameter optimization and an Attention pyramid convolution neural network (APCNN) (APCNN) for system behavior prediction. Integrated with a Programmable Logic Controller (PLC) and human-machine interface (HMI), this approach offers a comprehensive solution. Our research identifies a significant research gap in the efficiency of existing methods, emphasizing the need for improved control parameter optimization and system behavior prediction for cost reduction and enhanced efficiency. Through implementation on the MATLAB platform, the proposed DOA-APCNN approach demonstrates a noteworthy 30% reduction in computation time compared to existing methods such as Heap-based optimizer (HBO), Cuckoo Search Algorithm (CSA), and Salp Swarm Algorithm (SSA). These findings pave the way for faster and more efficient pipe-cutting operations, contributing to advancements in industrial automation and control systems.</p> </abstract>

Principles of ontophylogenetic development of artificial general intelligence systems based on multi-agent neurocognitive architectures

The purpose of the study is to study the possibilities of multigenerational optimization of behavior control systems for agents of general artificial intelligence capable of independently solving a universal range of tasks in a real environment. The main principles of ontophylogenetic synthesis of control systems for agents of general artificial intelligence based on multi-agent neurocognitive architectures have been developed. Methods and algorithms for synthesizing the phenotypes of control systems of intelligent agents according to their genotypes are proposed. A software package for simulating the processes of ontophylogenetic synthesis of multi-agent neurocognitive architectures has been developed and experiments have been carried out to create phenotypes of intelligent agents based on them. A complex genome of an intelligent agent has been developed, the features of a multichromosome genetic algorithm for organizing calculations in the paradigm of multigenerational optimization of multiagent neurocognitive architectures have been established and substantiated. It is shown that multigenerational optimization of the multi-agent neurocognitive architecture of intelligent agents can contribute to the achievement of adaptive resistance to the operating conditions of a general artificial intelligence agent, provide the synthesis of its suboptimal structural and functional scheme, accelerate learning and algorithms for finding solutions to a universal range of problems solved by this agent in its ecological niche.

Simulation of discrete control systems with parallelism of behavior

Objectives. The problem of functional verification of control devices with respect to their design specification is considered. When solving the problems of implementing and testing of discrete systems, one has to deal with the presence of parallelism in the behavior of interacting control objects, which is also displayed in the assignment for designing control systems. The aim of the work is to develop a method for simulating descriptions of such systems, which allows their behavior testing dynamically on the area limited by their possible functioning.Methods. The paper considers a class of control systems with parallelism of the processes occurring in them, which permits linearization of their execution. To specify the behavior of such control systems, it is proposed to use the PRALU language of parallel control algorithms, which is based on Petri nets and which allows to order events occurring during the device operation. An object-oriented approach to simulation of the description of the control algorithm at the transaction level is proposed. For this purpose, a TLM (Transaction-Level Modeling) model has been developed for describing the devices with behavior parallelism in PRALU language. The transaction level model describes a system as a set of interacting processes that run in parallel and determine the behavior of the system over time.Results. The key concepts of the TLM model for simulating the descriptions of control algorithms in the PRALU language are defined: data structure, transactions, processes, and a barrier mechanism for synchronization of parallel processes. A method is proposed for transforming the description of an algorithm in the language into a TLM model, which is based on the representation of language operations as compositions of elementary operations that are performed sequentially. The set of these operations forms the basis for the algorithmic decomposition of a parallel algorithm in PRALU language into intermediate language program that is executed strictly sequentially. Translators of this program into the Verilog and C languages have been developed, the results of their compilation are simulators of the behavior of control system.Conclusion. The proposed simulation method can be used to create a test bench for functional verification of the circuit implementation of control devices with behavior parallelism. In this case, test sequences for verifying the circuit implementation can be generated dynamically – in the process of simulating the description of the algorithm in the PRALU language directly the control device or system, which include the control algorithm and the algorithms of controlled objects behavior.

A Systematic Literature Review on the Transformation of Entrepreneurial Intention to Entrepreneurial Action

Abstract Transformation of entrepreneurial intention to action is a relatively new field of research that has attracted considerable interest from researchers over the past decade. This literature review has endeavoured to systematise and categorise the past studies to comprehend their actual research focus. The study has used 65 articles published between 1981 – 2020, divided into two categories, as articles published between 1981-2000 and 2001 – 2020. This study has used PRISMA framework, with well-defined exclusion and inclusion clauses, to identify relevant articles. The review found psychosocial influence to be the major focus of entrepreneurship research during year 1981-2000 period, while entrepreneurial mindset, entrepreneur’s family background, gender, behavioural control and entrepreneurial eco system, to be the major focus of the studies conducted between year 2001 and 2020. This review also found quantitative research methodology to be more popular among entrepreneurship researchers with regression analysis and structural equation modelling being most preferred for data analysis. This study has identified University students to be the most preferred unit of observation, while nascent entrepreneurs were found to be the least preferred. The study has also identified intention-action transformation to be a relatively new field of study with the field only gaining momentum over the past decade. This study adds value to the existing literature, through systemization and categorization, while supporting the administrators, policymakers, universities, and future researchers.

PI Control Technology Principal Analysis and Simulation

As the requirements for control accuracy and speed increase, proportional-integral (PI) control systems can better achieve stable control. Proportional-integral (PI) control is widely used in modern industry because it has the characteristics of block speed and high accuracy. However, the performance of proportional control systems with different parameters varies greatly in different usage scenarios, and the behavior of PI control systems can be observed and adjusted in advance through computer simulation and modeling. This process can be optimized in advance by observing the response performance of the PI control system, thus reducing the development time and helping to improve the development efficiency in actual engineering. This paper explains the basic principle of PI control from the basic mathematical principle, and simulates the specific behavior of PI control system under different regulation parameters and shows the zero-pole distribution and step response of PI controller under different states and analyzes the application of PI control system in real engineering.

Development of a low-tech MPC-algorithm for versatile applications in buildings with thermal activated components

Buildings with thermal activated components enable short-term storage of heat and cold with a high level of comfort for the inhabitants. However, a challenge for temperature control is the inertia of the storage mass and the behaviour of conventional control systems during extreme weather events such as long heat periods. Predictive controllers, working with weather forecast data in combination with a simplified building model enable a prediction of the system behaviour in order to manage heating and cooling in an efficient way.Due to the fact, that existing model predictive controller (MPC) follow the principle of higher system intelligence, this work focuses on the most simple design for a MPC. The following scientific study describes the simple respectively low-tech MPC approach, the experimental setup & the simulation in Matlab/Simulink and the comparison with conventional controller solutions. Although the authors use the term low-tech MPC, the proposed solution can be seen as being at the lower bound to a MPC logic and in the classification as a “predictive optimization controller”.The developed algorithm processes solar radiation gains and outside temperature forecasts with building characteristics and calculates a predicted room temperature profile for 48 h into the future. By optimizing the room temperature in relation to the set temperature, a prognosis of the necessary energy demand is possible. The analysis and validation of the algorithm was carried out in a simulated building model with a thermal activated building component (e.g. ceiling/floor-heating). First results show that the developed algorithm is capable of meeting comfort parameters better than conventional controller strategies and therefore useful for various operations in buildings. Possible future extensions can focus on the ideal combination of heating/cooling demand and cost optimization via own PV energy production.

Soft-Reset Control With Max-of-Quadratics Lyapunov Certificates

We further develop a novel control paradigm encoding the core behavior of a reset control system within a continuous-time feedback, described by a differential inclusion. A tuning knob allows adjusting how close the continuous-time feedback resembles the behavior of the underlying reset controller. The Lyapunov conditions that we derive naturally lead to a sum-of-squares formulation allowing for the design of max-of-quadratics Lyapunov certificates associated with polynomial multipliers. A few application examples confirm the practical effectiveness of the proposed solutions.

On-site measurement of the hysteresis curve for improved modelling of transformers

Transient simulations are usually carried out to analyse the behaviour of control and protection systems when performing switching action in power transformers. For this reason, the saturation curve and/or the hysteresis curve of the transformer must be properly modelled. However, in most of the cases the real saturation/hysteresis curve of a transformer is not known, because such measurements are not carried out as part of the factory tests of a transformer. This article describes a method to measure the hysteresis- and saturation curve with a portable measuring system on-site. The added value of the measured saturation curve is illustrated through an example, in which a single-phase low voltage transformer is modelled. This example shows the added value of a measurement-based modelling. An additional example illustrates measurement of the hysteresis curve of 350 MVA, 420/110 kV power transformers.