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The purpose of this paper is to propose and validate a robust industrial control system. The aim is to design a Multivariable Proportional Integral controller that accommodates multiple responses while considering the process's control and noise parameters. In addition, this paper intended to develop a multidisciplinary approach by combining computational science, control engineering and statistical methodologies to ensure a resilient process with the best use of available resources.

Taguchi's robust design methodology and multi-response optimisation approaches are adopted to meet the research aims. Two-Input-Two-Output transfer function model of the distillation column system is investigated. In designing the control system, the Steady State Gain Matrix and process factors such as time constant (t) and time delay (?) are also used. The unique methodology is implemented and validated using the pilot plant's distillation column. To determine the robustness of the proposed control system, a simulation study, statistical analysis and real-time experimentation are conducted. In addition, the outcomes are compared to different control algorithms.

Research indicates that integral control parameters (K_i) affect outputs substantially more than proportional control parameters (K_p). The results of this paper show that control and noise parameters must be considered to make the control system robust. In addition, Taguchi's approach, in conjunction with multi-response optimisation, ensures robust controller design with optimal use of resources. Eventually, this research shows that the best outcomes for all the performance indices are achieved when Kp11 = 1.6859, Kp12 = −2.061, Kp21 = 3.1846, Kp22 = −1.2176, Ki11 = 1.0628, Ki12 = −1.2989, Ki21 = 2.454 and Ki22 = −0.7676.

This paper provides a step-by-step strategy for designing and validating a multi-response control system that accommodates controllable and uncontrollable parameters (noise parameters). The methodology can be used in any industrial Multi-Input-Multi-Output system to ensure process robustness. In addition, this paper proposes a multidisciplinary approach to industrial controller design that academics and industry can refine and improve.

At the beginning of the Corona Virus Disease 2019 (COVID-19) pandemic, a digitalized construction environments surfaced in the heating, ventilation and air conditioning (HVAC) systems in the form of a modern delivery system called demand controlled ventilation (DCV). Demand controlled ventilation has the potential to solve the building ventilation's biggest problem of managing indoor air quality (IAQ) for controlling COVID-19 transmission in indoor environments. However, the improper evaluation and information management of infection prevention on dense crowd activities such as measurement errors and volatile organic compound (VOC) generation failure rates, is fragmented so the aim of this research is to integrate this and explore potentials with machine learning algorithms (MLAs).

The method used is a thorough systematic literature review (SLR) approach. The results of this research consist of a detailed description of the DCV system and digitalized construction process of its IAQ elements.

The discussion revealed that DCV has a potential for being further integrated by perceiving it as a MLAs and hereby enabling the management of IAQ level from the perspective of health risk function mechanism (i.e. VOC and CO₂) for maintaining a comfortable thermal environment and save energy of public and private buildings (PPBs). The appropriate MLA can also be selected in different occupancy patterns for seasonal variations, ventilation behavior, building type and locations, as well as current indoor air pollution control strategies. Furthermore, the conceptual framework showed that MLA application such as algorithm design/Model Predictive Control (MPC) integration can alleviate the high spread limitation of COVID-19 in the indoor environment.

Finally, the research concludes that a large unexploited potential within integration and innovation is recognized in the DCV system and MLAs which can be improved to optimize level of IAQ from the perspective of health throughout the building sector DCV process systems. The requirements of CO₂ based DCV along with VOC concentrations monitoring practice should be taken into consideration through further research and experience with adaption and implementation from the ventilation control initial stage of the DCV process.

This study proposes a predictive neural network model reference decoupling control method for the coupling problem between the leg joints of hydraulic quadruped robots, and verifies its decoupling effect..

The machine–hydraulic cross-linking coupling is studied as the coupling behavior of the hydraulically driven quadruped robot, and the mechanical dynamics coupling force of the robot system is controlled as the disturbance force of the hydraulic system through the Jacobian matrix transformation. According to the principle of multivariable decoupling, a prediction-based neural network model reference decoupling control method is proposed; each module of the control algorithm is designed one by one, and the stability of the system is analyzed by the Lyapunov stability theorem.

The simulation and experimental research on the robot joint decoupling control method is carried out, and the prediction-based neural network model reference decoupling control method is compared with the decoupling control method without any decoupling control method. The results show that taking the coupling effect experiment between the hip joint and knee joint as an example, after using the predictive neural network model reference decoupling control method, the phase lag of the hip joint response line was reduced from 20.3° to 14.8°, the amplitude attenuation was reduced from 1.82% to 0.21%, the maximum error of the knee joint coupling line was reduced from 0.67 mm to 0.16 mm and the coupling effect between the hip joint and knee joint was reduced from 1.9% to 0.48%, achieving good decoupling.

The prediction-based neural network model reference decoupling control method proposed in this paper can use the neural network model to predict the next output of the system according to the input and output. Finally, the weights of the neural network are corrected online according to the predicted output and the given reference output, so that the optimization index of the neural network decoupling controller is extremely small, and the purpose of decoupling control is achieved.

Several conceptual works suggest that more digitalized information systems in management accounting have the potential to make this corporate function more effective. Against this backdrop, this study aims to investigate the impact of information systems quality in management accounting on the effectiveness of management control systems. Additionally, this study examines the moderating effect of process automation.

A cross-sectional survey of 125 German Mittelstand firms and hierarchical regression analyses were used for data collection and analysis.

The findings confirm the assumed positive effect of information systems quality in management accounting on management control effectiveness. They also confirm the assumed moderating effect of process automation. The authors find that the relationship between information systems quality in management accounting and management control effectiveness is more pronounced if the firm features a higher degree of process automation.

Several earlier case studies and a few quantitative studies indicated the potentially positive effect of high-quality information systems in management accounting on management control effectiveness. To the best of the authors‘ knowledge, this study is among the first to deliver quantitative proof of this relationship in the context of German Mittelstand firms. Moreover, the authors add to this literature the moderating effect of process automation in the relationship between information systems quality in management accounting and management control effectiveness.

Component positioning is an important part of aircraft assembly, aiming at the problem that it is difficult to accurately fall into the corresponding ball socket for the ball head connected with aircraft component. This study aims to propose a ball head adaptive positioning method based on impedance control.

First, a target impedance model for ball head positioning is constructed, and a reference positioning trajectory is generated online based on the contact force between the ball head and the ball socket. Second, the target impedance parameters were optimized based on the artificial fish swarm algorithm. Third, to improve the robustness of the impedance controller in unknown environments, a controller is designed based on model reference adaptive control (MRAC) theory and an adaptive impedance control model is built in the Simulink environment. Finally, a series of ball head positioning experiments are carried out.

During the positioning of the ball head, the contact force between the ball head and the ball socket is maintained at a low level. After the positioning, the horizontal contact force between the ball head and the socket is less than 2 N. When the position of the contact environment has the same change during ball head positioning, the contact force between the ball head and the ball socket under standard impedance control will increase to 44 N, while the contact force of the ball head and the ball socket under adaptive impedance control will only increase to 19 N.

In this paper, impedance control is used to decouple the force-position relationship of the ball head during positioning, which makes the entire process of ball head positioning complete under low stress conditions. At the same time, by constructing an adaptive impedance controller based on MRAC, the robustness of the positioning system under changes in the contact environment position is greatly improved.

The implementation of control systems allows marketing managers to improve operational decisions and organizational results. This paper aims to identify the relationship between control combinations and organizational results and analyze the relationships between the variables attributed to the marketing managers and with marketing control combinations. Decisions involving marketing control combine formal and informal mechanisms and generate control systems that have a favorable relationship with organizational results.

The paper is based on 301 cross-sectional surveys among marketing managers. The classification procedure based on metric distance was implemented to identify the marketing control combinations. A hierarchical cluster analysis was carried out with perceptions about formal and informal control, to validate the control combination classifications. Finally, a discriminant analysis and ANOVA test were carried out for exploring factors associated with the managers. The data analysis was supported by IBM SPSS Statistics 24 software.

The authors found evidence that, when managers perceive high-control systems, the perception of non-financial and financial results is always better, but the presence of high-clan control also returns optimal results. In addition, the manager's satisfaction levels and work motivation are higher with high control systems than with other control systems.

This study contributes to the existing knowledge by providing a broader empirical basis to extend conceptual frameworks about marketing control combinations that emerge in practice.

企業設置營銷控制系統來進行營銷控制,這可讓市場經理能改善其營運決策和組織成果。本文擬確定控制合併與組織成果的關係;本文亦擬分析涉及市場經理的變數與營銷控制合併的關係。涉及營銷控制的決策會結合正式和非正式的機制,而這些決策會帶來與組織成果有良性關係的控制系統。

本研究乃基於對市場經理進行的301項橫斷調查。研究人員實施基於度量距離的分類程式,來確定營銷控制合併;為了證實有關的控制合併分類是正確的,研究人員就對正式控制和非正式控制的觀感和看法、進行了階層式分群法分析;最後,研究人員進行了判別分析和變異數分析 (ANOVA), 以探索與經理有關聯的因素。有關的數據分析得到IBM公司的SPSS (統計產品與服務解決方案) Statistics 24 (統計軟體) 的支持。

我們證實了、若主管感知高控制的系統,其對非財務結果和財務結果的看法必會較好的,但高社群控制亦會帶來最佳的結果。我們亦證實了高控制系統,較其它控制系統,更能提高主管的滿意程度和工作動機。

本研究提供了一個更廣闊的經驗基礎,以擴展涉及在實踐中出現的營銷控制合併的概念框架,就此,本研究豐富了這方面的知識。

This study aims to examine how the legitimacy of internal auditing is reconstructed during enterprise resource planning (ERP)-driven technological change.

The study is based on the comparative analysis of internal auditing and its transformation due to ERP implementations at two case firms operating in the food sector in Egypt – one a major Egyptian multinational corporation (MNC) and the other a major domestic company (DC).

Internal auditors (IAs) at MNC saw ERP implementation as an opportunity to reconstruct the legitimacy of internal auditing work by engaging and partnering with actors involved with the ERP change. In doing so, the IAs acquired system certifications and provided line functions and external auditors with data-driven business insights. The “practical coping mechanism” adopted by the IAs led to the acceptance (and legitimacy) of their work. In contrast, IAs at DC adopted a purposeful strategy of disengaging, blaming and rejecting since they were skeptical of the top management team's (TMT's) sincerity. The “disinterestedness” led to the loss of legitimacy in the eyes of the stakeholders.

The article offers two contributions. First, it extends the literature by highlighting a spectrum of behavior displayed by IAs (coping with impending issues vs strategic purposefulness) during ERP-driven technological change. Second, the article contributes to the literature on legitimacy by highlighting four intertwined micro-processes – participating, socializing, learning and role-forging – that contribute to reconstructing the legitimacy of internal auditing.

This study aimed to examine the adoption of consortium blockchain technology to ensure interoperability for the transparency of budgetary control in Ghanaian local government.

This study is based on the design science research (DSR) observational technique for developing a consortium blockchain budgetary control system for Ghana's local government.

The study resulted in the design of a consortium blockchain monitoring and evaluation system to set up a mechanism to monitor various budget projects, processes and transactions for Ghana's local government. The findings also proved Ghana is ideally positioned to gain an advantage from designed artefacts such as ours, given its digital financial service (DFS) policy. In addition, the evaluation of the designed artefact proves there will be a positive impact on budgetary processes by addressing transparency concerns; however, the success of this concern depends on how the local government organisation embraces the artefact.

The study sheds light on budget monitoring and evaluation tied to peer-to-peer (P2P) participation in the public sector via an advanced administrative digitalised networking and communication algorithm (A Distributed Ledger Technology - blockchain). The difference between the designed artefact and the traditional M&E system is argued. The study is limited by the paradoxes and inefficiencies of the integration of blockchain into the Ghanaian local government but, at the same time, presents a high level of certainty and possibility.

The proposed artefact has presented relevance because it is a new solution to existing concerns like trust, transparency, accountability and compliance, thereby improving local government budget administration.

The study has offered unique and new methods, guidelines and designs for tracking various budget projects and processes beyond the conventional technology-driven approach via DSR, exhibiting a unique solution for solving budget transparency, trust, accountability, compliance and data accessibility concerns.

The study aims to equip robots with the ability to precisely maintain interaction forces, which is crucial for tasks such as polishing in highly dynamic environments with unknown and varying stiffness and geometry, including those found in airplane wings or thin, soft materials. The purpose of this study is to develop a novel adaptive force-tracking admittance control scheme aimed at achieving a faster response rate with higher tracking accuracy for robot force control.

In the proposed method, the traditional admittance model is improved by introducing a pre-proportional-derivative controller to accelerate parameter convergence. Subsequently, the authors design an adaptive law based on fuzzy logic systems (FLS) to compensate for uncertainties in the unknown environment. Stability conditions are established for the proposed method through Lyapunov analysis, which ensures the force tracking accuracy and the stability of the coupled system consisting of the robot and the interaction environment. Furthermore, the effectiveness and robustness of the proposed control algorithm are demonstrated by simulation and experiment.

A variety of unstructured simulations and experimental scenarios are designed to validate the effectiveness of the proposed algorithm in force control. The outcomes demonstrate that this control strategy excels in providing fast response, precise tracking accuracy and robust performance.

In real-world applications spanning industrial, service and medical fields where accurate force control by robots is essential, the proposed method stands out as both practical and straightforward, delivering consistently satisfactory performance across various scenarios.

This research introduces a novel adaptive force-tracking admittance controller based on FLS and validated through both simulations and experiments. The proposed controller demonstrates exceptional performance in force control within environments characterized by unknown and varying.

This study aims to introduce a novel technique for nonlinear sensor time constant estimation and sensor dynamic compensation in hot-bar soldering using an extended Kalman filter (EKF) to estimate the temperature of the thermocouple.

Temperature optimal control is combined with a closed-loop proportional integral differential (PID) control method based on an EKF. Different control methods for measuring the temperature of the thermode in terms of temperature control, error and antidisturbance are studied. A soldering process in a semi-industrial environment is performed. The proposed control method was applied to the soldering of flexible printed circuits and circuit boards. An infrared camera was used to measure the top-surface temperature.

The proposed method can not only estimate the soldering temperature but also eliminate the noise of the system. The performance of this methodology was exemplary, characterized by rapid convergence and negligible error margins. Compared with the conventional control, the temperature variability of the proposed control is significantly attenuated.

An EKF was designed to estimate the temperature of the thermocouple during hot-bar soldering. Using the EKF and PID controller, the nonlinear properties of the system could be effectively overcome and the effects of disturbances and system noise could be decreased. The proposed method significantly enhanced the temperature control performance of hot-bar soldering, effectively suppressing overshoot and shortening the adjustment time, thereby achieving precise temperature control of the controlled object.