Deep System Knowledge Required: Revisiting UCD Contribution in the Design of Complex Command and Control Systems

Control systems are pervasive in our lives. Our homes have environmental controls. The appliances we use, such as the washing machine, microwave, etc. carry embedded controllers in them. We fly in airplanes and drive automobiles that extensively use control systems. The industrial plants that produce consumer goods run on process control systems. The recent drive toward automation has increased our reliance on control systems technology. This book discusses control systems design from a model-based perspective for dynamic system models of single-input single-output type. The emphasis in this book is on understanding and applying the techniques that enable the design of effective control systems in multiple engineering disciplines. The book covers both time-domain and the frequency-domain design methods, as well as controller design for both continuous-time and discrete-time systems. MATLAB© and its Control Systems Toolbox are extensively used for design. Technical topics discussed in the book include: • Mathematical models of physical systems • Analysis of transfer function and state variable models • Control systems design objectives • Control system design with root locus • Control system design in the state-space • Control system design of sampled-data systems • Compensator design with frequency response methods

Control systems are pervasive in our lives. Our homes have environmental controls. The appliances we use, such as the washing machine, microwave, etc. carry embedded controllers in them. We fly in airplanes and drive automobiles that extensively use control systems. The industrial plants that produce consumer goods run on process control systems. The recent drive toward automation has increased our reliance on control systems technology. This book discusses control systems design from a model-based perspective for dynamic system models of single-input single-output type. The emphasis in this book is on understanding and applying the techniques that enable the design of effective control systems in multiple engineering disciplines. The book covers both time-domain and the frequency-domain design methods, as well as controller design for both continuous-time and discrete-time systems. MATLAB© and its Control Systems Toolbox are extensively used for design. Technical topics discussed in the book include: • Mathematical models of physical systems • Analysis of transfer function and state variable models • Control systems design objectives • Control system design with root locus • Control system design in the state-space • Control system design of sampled-data systems • Compensator design with frequency response methods

Manufacturing planning and control systems (MPC) design or redesign in the current dynamic industrial environment is a complex process and must be based on a true understanding of the business needs of a particular enterprise and the physical facilities and resources available to satisfy those needs. Interdomain relationships between various elements, both within and outside the system, must be considered in this context; a necessary requirement for any integrated systems design. Many past efforts in the field seem to lack this approach and as a result changes in the business needs are difficult, if not impossible, to incorporate in the current MPC systems without a major redesign. This chapter outlines the major design issues in this context and proposes a methodology to develop an integrated system's model for implementa­ tion. The methodology starts with an analysis of the business needs and considers the coordination and communications requirements between various disparate units and domains of an organization. To aid the design process, the methodology uses many well-known tools and methods in its various stages; their functions and usefulness are discussed. The chapter gives an example to show how the methodology can be used to develop a MPC system in real life .

PurposeDrawing on Simons's levers of control (LoC) framework, the primary aim of this study is to advance an understanding of the balance between empowerment and constraint in a non-profit UK organisation. In particular, this study examines the antecedents and manifestations of LoC (im)balance, in relation to employees' level of engagement with the control systems in place.Design/methodology/approachFor this study, 27 semi-structured interviews were conducted with different organisational members, from directors to non-managerial staff, to gain an in-depth appreciation of the main differences between managerial intentions in the design of management control systems (MCS) and employee perceptions regarding the role of such systems.FindingsThis research reveals that suppression of interactive systems and internal inconsistencies between different types of controls hinder the balance between empowerment and constraint. This imbalance is then found to have important consequences for employee buy-in, in some cases, defeating the purposes of control.Research limitations/implicationsThis study enhances our understanding of the gap between the design of control systems and the employee perceptions of it in an unusual organisational setting (non-profit and bringing together clinical and non-clinical staff and operations).Originality/valueThe study of MCS and its role in organisations has long been the focus of both academic and practitioner research. Yet, while extant literature focused on management's perspective on MCS, few studies have explored employees' attitudes and behaviours that accompany the implementation of control. What is more, little is known about the specific uses and behavioural outcomes of MCS in the context of non-profit organisations. Drawing on Simons's LoC framework, this paper addresses these gaps in the literature and investigates the balance between control and empowerment of employees in a UK non-profit organisation with significant clinical remit.

A method is described for using nonlinear programing in the computer-aided design of airplane control systems. It is assumed that the quality of such systems depends on many criteria. These criteria are included in the constraints vector (instead of attempting to combine them into a single scalar criterion, as is usually done), and the design proceeds through a sequence of nonlinear programing solutions in which the designer varies the specification of sets of requirements levels. The method is applied to design of a lateral stability augmentation system (SAS) for a fighter airplane, in which the requirements vector is chosen from the official handling-qualities specifications. Results are shown for several simple SAS configurations designed to obtain desirable handling qualities over all design flight conditions with minimum feedback gains. The choice of the final design for each case is not unique but depends on the designer's decision as to which achievable set of requirements levels represents the best for that system. Results indicate that constant gain systems can substantially exceed the highest required levels of handling qualities in all design flight conditions of the example considered. The role of the designer as a decision maker, interacting with the computer program, is discussed. Advantages of this type of designer-computer interaction are emphasized. Desirable extensions of the method are indicated.

10 - Robust design of intelligent control systems to mitigate earthquake-induced vibrations under uncertain conditions

The variant of construction of the decentralized control system of technological process is considered. The control system combines control according to the classical scheme of the explicit decomposition method and the proposed method of situational decomposition, which contributes to its efficiency and reliability. Complex control systems with the construction of physical and mathematical models are considered. The importance of the correct choice of construction of the target function of control subsystems is shown. A distributed multi-tiered system requires the right choice of the authority responsible for decision-making, which should be associated with the coordination on bilateral ties as well, with all subsystems placed at lower levels. Information interaction allows you to create the right management solution. The article deals with the design of control systems using the integrated software environment Trace mode6. The management of a technological process taking into account economic and human resources is considered. The authors made process control measuring systems using the method of auto-construction. The possibility of application in the educational process of the system of computer-aided design for practical training is shown. Information resources of this software environment allow one to create a portal to perform laboratory, course and diploma papers for remote access.

Distributed control and optimization form the backbone of many critical control systems, with typical examples including sensor networks, power grids, and intelligent transportation systems. As these systems grow in scale and complexity, ensuring the privacy of individual agents becomes increasingly essential. Privacy protection is no longer an optional add-on; it is a crucial element in the design of these systems. Sensitive data, such as states, measurements, and decisions, must be shielded from unauthorized access or malicious attacks, while still allowing the system to function effectively. This special issue aims to explore novel techniques and strategies that protect privacy in distributed control and optimization, showcasing how these approaches can be seamlessly integrated into real-world applications. The diverse contributions in this issue demonstrate the growing importance of privacy in the evolving field of distributed control systems. RNC7747 introduces a privacy-preserving method for coverage control in multi-agent systems with limited communication ranges, ensuring efficient operation without compromising agents' privacy. RNC7798 proposes a privacy-preserving consensus mechanism based on pulse-coupled oscillators, helping maintain privacy while agents coordinate in distributed networks. RNC7778 presents privacy preservation techniques for cloud-based cooperative LQG control systems, enabling privacy protection even when leveraging cloud resources. RNC8051 discusses achieving privacy-preserving average consensus in unreliable network environments, ensuring privacy despite communication challenges. RNC7929 introduces a novel approach to open privacy-preserving consensus via state decomposition, allowing agents to reach consensus while maintaining privacy. RNC7966 investigates leader-follower consensus in multi-agent systems with distributed event-triggered observations, ensuring privacy during agent coordination in real-time systems. RNC7789 discusses the tradeoff between privacy protection strength and control performance in control systems. RNC8029 proposes a new privacy mechanism for distributed average consensus on time-varying directed graphs. RNC7776 investigates event-triggered distributed optimization with differential privacy, reducing communication costs while safeguarding sensitive data. RNC7885 develops an event-triggered privacy-preserving optimization method for directed communication networks, emphasizing privacy during optimization tasks. RNC7791 focuses on robust optimization for virtual power plant scheduling under uncertainty, incorporating privacy preservation into the optimization process. RNC7730 explores prescribed-time distributed optimization with set constraints, offering time guarantees while maintaining privacy in dynamic optimization scenarios. RNC7926 provides a privacy-preserving algorithm for constrained resource allocation with communication delays, crucial for real-time decision-making in distributed systems. RNC7848 presents an adaptive event-triggered control strategy for cyber-physical systems under DoS and deception attacks, ensuring privacy and system security. RNC8068 addresses initial state privacy in nonlinear systems on Riemannian manifolds, offering methods to protect privacy in complex, high-dimensional control systems. RNC7906 focuses on dynamic consensus-based formation control for multi-robot systems, preserving privacy through output masking techniques while achieving coordination. RNC7688 introduces a periodic dynamic encoding mechanism for stealthy attack detection in distributed state estimation, focusing on security and privacy under attack scenarios. RNC70033 tackles robust consensus Kalman filtering for distributed state-saturated systems, incorporating dynamic-disturbed saturation levels and censored measurements to ensure privacy under uncertain conditions. The contributions in this special issue span a broad spectrum of topics related to privacy in distributed control and optimization. As distributed systems continue to evolve, these papers contribute to the ongoing conversation about balancing privacy protection with efficient system operation, highlighting the importance of privacy as a key consideration in the design and optimization of future distributed control systems. The authors declare no conflicts of interest.

Abstract: MAID is an expert system for the computer‐aided design of control systems. It is developed in conjunction with the successful application of a systematic control system design technique. The design problem has been decomposed into sub‐problems, resulting in good modularity of design knowledge. Interactive design and the designer's intuition are emphasized. MAID, which acts as a designer's assistant, was developed using the expert systems development facility provided within a control system design package. The coupling of symbolic and numerical processing was carried out in a natural way.

The dial gauge is used widely in the production line at present. The dial gauge has many types and huge quantity. At present, testing this type of instrument is mainly used manual observation method. By man-made factors, the testing efficiency and accuracy is low. In order to improve the test efficiency and accuracy, it is required to use the automatic test methods for dial gauge. Although the control algorithm of control system in automatic test system is simple, the control accuracy is high demanding. So the design of control systems is essential. This paper takes the dial gauge automatic test method for the object and studied on the control system in the automatic test system. It presents the design principles, methods in fully automatic test system and studied on the design of control systems, mechanical drive parts and the software architecture. Finally, through experimental results verify the test system design is reasonable. Practical application results show that the system is feasible, and the motion control system is high precision and higher intellectualized. It also has good application prospect, especially for some special environment which is not suitable for testing by human eye, this system shows its superiority.

After the description of the underlying principles on which the “multiagentbased production control” technology and the “holonic manufacturing control” concept within the intelligent manufacturing system paradigm are based, this work proposes an approach that supports the design of agent-based manufacturing control systems for different industrial holonic manufacturing scenarios. The results of the application to a pilot cell at industrial level are very promissory, showing that the approach seems to be very suited in accommodating heterogeneous hardware and software components in both their manufacturing control and information system, and in integrating existing/legacy systems.KeywordsFlexible Manufacturing SystemProduction AgentLogical DependencyTransport AgentManufacturing ObjectThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Structural issues in the design of marine control systems

Assistive devices of human knee joint: A review

Bare-bones languages serve small systems with ease: Cushmann, R HEDN Vol 25 No 16 (5 September 1980) pp 171–177

While linear covariance analysis is widely used for navigation system design and analysis, it is often overlooked as a tool for closed-loop guidance navigation and control (GN&C) system design and analysis. This article presents an overview of the techniques and methods required to develop a linear covariance analysis tool for a close-loop GN&C system. Then, using a simple nonlinear closed-loop GN&C problem as a guide, the capabilities of linear covariance analysis for the design and analysis of closed-loop systems are demonstrated. It is shown that linear covariance can be accurately applied to a closed-loop system with time-to-go guidance, dead-reckoning navigation, and a Kalman filter for state estimation. The accuracy and efficiency of linear covariance analysis is shown by direct comparison to Monte Carlo analysis results, and the value of linear covariance analysis is highlighted by presenting several analysis capabilities that are often required in the design and analysis of closed-loop GN&C systems. It is also shown how the efficiency of linear covariance enables new design methodologies, one of which is presented in this article, that would otherwise be prohibitive with Monte Carlo analysis.