Relevant bibliographies by topics / Network based control systems

Academic literature on the topic 'Network based control systems'

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Published: 17 July 2024

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Journal articles on the topic "Network based control systems"

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Jadidi, Zahra, Shantanu Pal, Mukhtar Hussain, and Kien Nguyen Thanh. "Correlation-Based Anomaly Detection in Industrial Control Systems." Sensors 23, no. 3 (February 1, 2023): 1561. http://dx.doi.org/10.3390/s23031561.

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Industrial Control Systems (ICSs) were initially designed to be operated in an isolated network. However, recently, ICSs have been increasingly connected to the Internet to expand their capability, such as remote management. This interconnectivity of ICSs exposes them to cyber-attacks. At the same time, cyber-attacks in ICS networks are different compared to traditional Information Technology (IT) networks. Cyber attacks on ICSs usually involve a sequence of actions and a multitude of devices. However, current anomaly detection systems only focus on local analysis, which misses the correlation between devices and the progress of attacks over time. As a consequence, they lack an effective way to detect attacks at an entire network scale and predict possible future actions of an attack, which is of significant interest to security analysts to identify the weaknesses of their network and prevent similar attacks in the future. To address these two key issues, this paper presents a system-wide anomaly detection solution using recurrent neural networks combined with correlation analysis techniques. The proposed solution has a two-layer analysis. The first layer targets attack detection, and the second layer analyses the detected attack to predict the next possible attack actions. The main contribution of this paper is the proof of the concept implementation using two real-world ICS datasets, SWaT and Power System Attack. Moreover, we show that the proposed solution effectively detects anomalies and attacks on the scale of the entire ICS network.
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Zhang, Haitao, and Zhen Li. "Fuzzy Immune Control Based Smith Predictor for Networked Control Systems." International Journal of Engineering and Technology 3, no. 1 (2011): 81–84. http://dx.doi.org/10.7763/ijet.2011.v3.204.

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Zou, Y., T. Chen, and S. Li. "Network-based predictive control of multirate systems." IET Control Theory & Applications 4, no. 7 (July 1, 2010): 1145–56. http://dx.doi.org/10.1049/iet-cta.2008.0577.

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Efrati, T., and H. Flashner. "Neural Network Based Tracking Control of Mechanical Systems." Journal of Dynamic Systems, Measurement, and Control 121, no. 1 (March 1, 1999): 148–54. http://dx.doi.org/10.1115/1.2802435.

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A method for tracking control of mechanical systems based on artificial neural networks is presented. The controller consists of a proportional plus derivative controller and a two-layer feedforward neural network. It is shown that the tracking error of the closed-loop system goes to zero while the control effort is minimized. Tuning of the neural network’s weights is formulated in terms of a constrained optimization problem. The resulting algorithm has a simple structure and requires a very modest computation effort. In addition, the neural network’s learning procedure is implemented on-line.
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Dovbnya, Vitaly G., Sergey N. Frolov, Konstantin P. Sulima, and Alexey N. Schitov. "SPECIFICS OF IMPLEMENTATION OF CONTROL SYSTEMS BASED ON LORAWAN TECHNOLOGY." T-Comm 14, no. 9 (2020): 24–30. http://dx.doi.org/10.36724/2072-8735-2020-14-9-24-30.

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In the context of the rapid growth of various areas of the Internet of things, there is currently no unified approach to building networks based on low-power Wide-area Network (LPWAN) wireless networks, taking into account the general requirements for them as automated control systems (ACS). There are the following areas of use of the Internet of things: industry and production; transport and transportation; control of the technical condition of building structures, air quality, background noise and energy consumption; waste management; smart Parking and providing data on traffic jams; smart street lighting and use in everyday life. Networks based on LoRaWAN technology provide low-cost energy-efficient wireless communications for modern ACS in a variety of industries. It is cost-effective for designing hardware and software for telemetry and controlling, such as a system of control and monitoring engineering systems of buildings and facilities (SMES) and automated outdoor lighting control systems. The article presents a structural and functional analysis of approaches to the construction of hardware and software complex elements based on LoRаWAN, taking into account the specifics and logic of the SMES and ASUS. It also provides calculations of network bandwidth and capacity for a single LoRaWAN gateway in a different mode of operation of ACS. A parametric analysis of existing implementations was carried out to design the management server (SU), which is the main element of the LoRaWAN network. The results allowed to obtain seventeen indicators that determine the functionality of a network server (NS). Network server software development. Major structures and the mechanisms of interaction of its elements are determined during the process of designing the original implementation of NS software.
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Abdulrab, Hakim, Fawnizu Azmadi Hussin, Azrina Abd Aziz, Azlan Awang, Idris Ismail, and P. Arun Mozhi Devan. "Reliable Fault Tolerant-Based Multipath Routing Model for Industrial Wireless Control Systems." Applied Sciences 12, no. 2 (January 6, 2022): 544. http://dx.doi.org/10.3390/app12020544.

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Communication in industrial wireless networks necessitates reliability and precision. Besides, the existence of interference or traffic in the network must not affect the estimated network properties. Therefore, data packets have to be sent within a certain time frame and over a reliable connection. However, the working scenarios and the characteristics of the network itself make it vulnerable to node or link faults, which impact the transmission reliability and overall performance. This article aims to introduce a developed multipath routing model, which leads to cost-effective planning, low latency and high reliability of industrial wireless mesh networks, such as the WirelessHART networks. The multipath routing model has three primary paths, and each path has a backup node. The backup node stores the data transmitted by the parent node to grant communication continuity when primary nodes fail. The multipath routing model is developed based on optimal network planning and deployment algorithm. Simulations were conducted on a WirelessHART simulator using Network Simulator (NS2). The performance of the developed model is compared with the state-of-the-art. The obtained results reveal a significant reduction in the average network latency, low power consumption, better improvement in expected network lifetime, and enhanced packet delivery ratio which improve network reliability.
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Nwazor, Nkolika Ogechukwu, and Eliezar Elisha Audu. "Data communications network for real-time industrial control systems." Nigerian Journal of Technological Development 19, no. 1 (June 6, 2022): 48–58. http://dx.doi.org/10.4314/njtd.v19i1.6.

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The advancements in network technologies and the evolution of the Internet of Things (IoT) have made supporting industrial control systems over probabilistic data networks promising. However, control systems’ communication over the traditional data networks is faced with problems of instability in feedback control and poor quality of performance due to time-varying data propagation delay. This paper presents two approaches that can enable real-time industrial control over non-deterministic computer networks allowing control system designers to take advantage of the existing communication infrastructures. The first approach is based on system-level interaction over two wires network called the collaboration network. The second approach is based on the implementation of the virtual local area network (VLAN). This method allows real-time control of industrial equipment or systems over IP-based networks while other computers are connected. Nodes providing real-time control services have the same PortID on the VLAN switch. This approach minimizes data traffic and reduces time-varying delay in system control over IP networks. The first approach was modeled and simulated using Proteus ISIS software. Two PIC16F877A microcontrollers were used to represent two nodes. CISCO packet tracer was used in the second approach to model and simulate IP-based control system communications over the traditional data network. Results indicate that the use of a two-wire collaborative network approach to a real-time control system is effective but requires an additional network alongside the main data traffic channel. VLAN, therefore, presents a more flexible approach that relies on the same infrastructures.
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Zhang, Yan. "Network Optimization-Based MPC for Distributed Control Systems." Advanced Materials Research 482-484 (February 2012): 2485–88. http://dx.doi.org/10.4028/www.scientific.net/amr.482-484.2485.

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In this paper, a novel network optimization-based MPC scheme is proposed for on-line optimization and control of a class of distributed control systems, in which the on-line optimization of the whole system is decomposed into that of several small-scale sub-systems in distributed structures. Under network environment, the connectivity of the communication network is assumed to be sufficient for each sub-system to exchange information with other sub-systems. An iterative algorithm for networked MPC with ideal information model is developed for DCS. Finally, the simulation study of the fuel feed flow control for the walking beam reheating furnace is provided to test the effectiveness and practicality of the proposed networked MPC algorithm.
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Masoumzadeh, Amirreza, and James Joshi. "Ontology-based access control for social network systems." International Journal of Information Privacy, Security and Integrity 1, no. 1 (2011): 59. http://dx.doi.org/10.1504/ijipsi.2011.043731.

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Hong Seong Park, Yong Ho Kim, Don-Sung Kim, and Wook Hyun Kwon. "A scheduling method for network-based control systems." IEEE Transactions on Control Systems Technology 10, no. 3 (May 2002): 318–30. http://dx.doi.org/10.1109/87.998012.

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Dissertations / Theses on the topic "Network based control systems"

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Xu, Andong. "Flexible adaptive-network-based fuzzy inference system." Diss., Online access via UMI:, 2006.

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Thesis (M.S.)--State University of New York at Binghamton, Thomas J. Watson School of Engineering and Applied Science, Dept. of Systems Science and Industrial Engineering, 2006.
Includes bibliographical references.
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Zuo, Wei. "Fourier neural network based tracking control for nonlinear systems /." View abstract or full-text, 2008. http://library.ust.hk/cgi/db/thesis.pl?MECH%202008%20ZUO.

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Ramesh, Chithrupa. "State-based Channel Access for a Network of Control Systems." Doctoral thesis, KTH, Reglerteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-144057.

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Wireless networked control systems use shared wireless links to communicate between sensors and controllers, and require a channel access policy to arbitrate access to the links. Existing multiple access protocols perform this role in an agnostic manner, by remaining insular to the applications that run over the network. This approach does not give satisfactory control performance guarantees. To enable the use of wireless networks in emerging industrial applications, we must be able to systematically design wireless networked control systems that provide guaranteed performances in resource-constrained networks. In this thesis, we advocate the use of state-based channel access policies. A state-based policy uses the state of the controlled plant to influence access to the network. The state contains information about not only the plant, but also the network, due to the feedback in the system. Thus, by using the state to decide when and how frequently to transmit, a control system can adapt its contribution to the network traffic, and enable the network to adapt access to the plant state. We show that such an approach can provide better performance than existing methods. We examine two different state-based approaches that are distributed and easy to implement on wireless devices: event-based scheduling and adaptive prioritization. Our first approach uses events to reduce the traffic in the network. We use a state-based scheduler in every plant sensor to generate non-coordinated channel access requests by selecting a few critical data packets, or events, for transmission. The network uses a contention resolution mechanism to deal with simultaneous channel access requests. We present three main contributions for this formulation. The first contribution is a structural analysis of stochastic event-based systems, where we identify a dual predictor architecture that results in separation in design of the state-based scheduler, observer and controller. The second contribution is a Markov model that describes the interactions in a network of event-based systems. The third contribution is an analysis of the stability of event-based systems, leading to a stabilizing design of event-based policies. Our second approach uses state-based priorities to determine access to the network. We use a dominance protocol to evaluate priorities in a contention-based setting, and characterize the resulting control performance. An implementation and evaluation of this channel access mechanism on sensor nodes is also presented. The thesis finally examines the general networked control problem of jointly optimizing measurement and control policies, when a nonlinear measurement policy is used to perform quantization, event-triggering or companding. This contribution focuses on some of the fundamental aspects of analyzing and synthesizing control systems with state-based measurement policies in a more generalized setting. We comment on the dual effect, certainty equivalence and separation properties for this problem. In particular, we show that it is optimal to apply separation and certainty equivalence to a design problem that permits a dynamic choice of the measurement and control policies.

QC 20140408

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Nardi, Flavio. "Neural network based adaptive alogrithms for nonlinear control." Diss., Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/12012.

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Chan, Yat-fei. "Neurofuzzy network based adaptive nonlinear PID controllers." Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B43958357.

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Chan, Yat-fei, and 陳一飛. "Neurofuzzy network based adaptive nonlinear PID controllers." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B43958357.

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Moles, Joshua Stephen. "Chemical Reaction Network Control Systems for Agent-Based Foraging Tasks." PDXScholar, 2015. https://pdxscholar.library.pdx.edu/open_access_etds/2203.

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Chemical reaction networks are an unconventional computing medium that could benefit from the ability to form basic control systems. In this work, we demonstrate the functionality of a chemical control system by evaluating classic genetic algorithm problems: Koza's Santa Fe trail, Jefferson's John Muir trail, and three Santa Fe trail segments. Both Jefferson and Koza found that memory, such as a recurrent neural network or memories in a genetic program, are required to solve the task. Our approach presents the first instance of a chemical system acting as a control system. We propose a delay line connected with an artificial neural network in a chemical reaction network to determine the artificial ant's moves. We first search for the minimal required delay line size connected to a feed forward neural network in a chemical system. Our experiments show a delay line of length four is sufficient. Next, we used these findings to implement a chemical reaction network with a length four delay line and an artificial neural network. We use genetic algorithms to find an optimal set of weights for the artificial neural network. This chemical system is capable of consuming 100% of the food on a subset and greater than 44% of the food on Koza's Santa Fe trail. We also show the first implementation of a simulated chemical memory in two different models that can reliably capture and store information over time. The ability to store data over time gives rise to basic control systems that can perform more complex tasks. The integration of a memory storage unit and a control system in a chemistry has applications in biomedicine, like smart drug delivery. We show that we can successfully store the information over time and use it to act as a memory for a control system navigating an agent through a maze.
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Kutay, Ali Turker. "Neural Network Based Adaptive Output Feedback Control: Applications and Improvements." Diss., Available online, Georgia Institute of Technology, 2005, 2005. http://etd.gatech.edu/theses/available/etd-11282005-122234/.

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Thesis (Ph. D.)--Aerospace Engineering, Georgia Institute of Technology, 2006.
J. Eric Corban, Committee Member ; Panagiotis Tsiotras, Committee Member ; Eric N. Johnson, Committee Member ; Nader Sadegh, Committee Member ; Anthony J. Calise, Committee Chair.
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Lee, Seungjae. "Neural network based adaptive control and its applications to aerial vehicles." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/11957.

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Zhao, Yun-Bo. "Packet-Based Control for Networked Control Systems." Thesis, University of South Wales, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.490204.

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Networked control systems (NCSs) are such control systems where the control loop is closed via some form of communication networks. These control systems are widely applicable in remote and distributed control applications. The inserted network however presents great challenges to conventional control theory as far as the design and analysis of NCSs are concerned. These challenges are caused primarily by the communication constraints in NCSs, e.g., network-induced delay, data packet dropout, data packet disorder, network access constraint, etc., which significantly degrade the system performance or even destabilize the system. When applying conventional control approaches to NCSs, considerable conservativeness is inevitable due to the failure to exploit network characteristics. Therefore, the co-design approach to NCSs in which control approaches and characteristics of NCSs are both fully considered, is believed to be the best way forward for the design of NCSs. In this thesis, we investigate the packet-based transmission of the network being used in NCSs, and propose a packet-based control (PB-control) approach to NCSs. In this approach, the 'packet' structure of data transmission in NCSs which is distinct from conventional control systems, is taken advantage of where, the control signals are first 'packed' and then sent as a sequence instead of one at a time as done in conventional control systems. \Vith the efficient use of the 'packet' structure, we can then actively compensate for the communication constraints in NCSs including the network-induced delay, data packet dropout and data packet disorder simultaneously. After determining the PB-control structure, we then extend its application to several categories of problems as follows. j • The first application is to two types of special nonlinear systems described by a Hammerstein model and a Wiener model respectively. A 'two-step' approach is adopted in this situation to separate the nonlinear process from the whole system which then enables the PB-control approach to be implemented. • It is observed that the communication constraints in NeSs are stochastic in nature, and thus a stochastic analysis of the PB-control approach is presented -----'''-'--'--~-• .:.o'... '-~.::C''c:....'..:..'..;...';';;;'~~.~'----' ......;.''''- ---'- ..-..;.;.~~ / iii under the Markov jump system framework, by modeling the network-induced delay and data packet dropout as a homogeneous ergodic Markov chain. The sufficient and necessary conditions for stochastic stability and stabilization in this situation are also obtained. • Continuous-time plant and continuous network-induced delay are observed to be more difficult to handle when implementing the PB-control approach. For this challenge, a discretization technique is introduced for the continuous network-induced delay and as a result, a novel model for NCSs is derived which is different to that obtained by conventional analysis from time delay system theory. A stabilized controller is also obtained in this situation by using delay-dependent analysis. • The last application is to deal with the situation where a set of NeSs share the network and thus the network access constraint has to be considered. For this situation, a PB-control and scheduling co-design approach is proposed where, PB-control is still applied to each subsystem while scheduling algorithms are applied to schedule the network resources among the subsystems to guarantee the stability of the whole system. We also point out in the thesis that further research on the PB-control approach is still needed as far as nonlinear, continuous-time systems and stochastic analysis are concerned.
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Books on the topic "Network based control systems"

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Liu, G. P. Neural network based predictive control for nonlinear systems. Sheffield: University of Sheffield, Dept. of Automatic Control and Systems Engineering, 1996.

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Esfandiari, Kasra, Farzaneh Abdollahi, and Heidar A. Talebi. Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-73136-6.

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Zhao, Yun-Bo, Guo-Ping Liu, Yu Kang, and Li Yu. Packet-Based Control for Networked Control Systems. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-6250-6.

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Liu, G. P. Neural network based variable structure control for nonlinear discrete systems. Sheffield: University of Sheffield, Dept. of Automatic Control and Systems Engineering, 1996.

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Garcia, Eloy, Panos J. Antsaklis, and Luis A. Montestruque. Model-Based Control of Networked Systems. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07803-8.

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Mazumder, Sudip K. Wireless Networking Based Control. New York, NY: Springer Science+Business Media, LLC, 2011.

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Joby, P. P., Valentina E. Balas, and Ram Palanisamy, eds. IoT Based Control Networks and Intelligent Systems. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-5845-8.

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Joby, P. P., Marcelo S. Alencar, and Przemyslaw Falkowski-Gilski, eds. IoT Based Control Networks and Intelligent Systems. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-6586-1.

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Elli, Kartsakli, ed. Contention-based collision-resolution medium access control algorithms. New York: Nova Science Publishers, 2009.

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Elli, Kartsakli, ed. Contention-based collision-resolution medium access control algorithms. New York: Nova Science Publishers, 2009.

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Book chapters on the topic "Network based control systems"

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Ilić, Marija D., and Shell Liu. "Network-Based System Regulation." In Hierarchical Power Systems Control, 195–217. London: Springer London, 1996. http://dx.doi.org/10.1007/978-1-4471-3461-9_8.

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Enokido, Tomoya, and Makoto Takizawa. "Preventing Illegal Information Flow Based on Role-Based Access Control Model." In Network-Based Information Systems, 242–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-85693-1_26.

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Yang, Shuang-Hua. "Dealing with Internet Transmission Delay and Data Loss from the Network View." In Internet-based Control Systems, 53–65. London: Springer London, 2011. http://dx.doi.org/10.1007/978-1-84996-359-6_6.

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Kratchanov, Kostadin, Tzanko Golemanov, Emilia Golemanova, and Tuncay Ercan. "Control Network Programming with SPIDER: Dynamic Search Control." In Knowledge-Based and Intelligent Information and Engineering Systems, 253–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15390-7_26.

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Sun, Xi-Ming, Kun-Zhi Liu, Xue-Fang Wang, and Andrew R. Teel. "Model-Based Event-Triggered Control for Distributed Networked Control Systems." In Control and Optimization Based on Network Communication, 11–31. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9534-7_2.

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Li, Zhijun, Chenguang Yang, and Liping Fan. "Neural Network Based Model Reference Control." In Advanced Control of Wheeled Inverted Pendulum Systems, 193–210. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-2963-9_9.

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Wisniewski, Lukasz. "Timeliness in Ethernet Based Network Control Systems." In New methods to engineer and seamlessly reconfigure time triggered Ethernet based systems during runtime based on the PROFINET IRT example, 37–103. Berlin, Heidelberg: Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-662-54650-5_3.

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Nakamura, Shigenari, Tomoya Enokido, and Makoto Takizawa. "Object-Based Information Flow Control Model in P2PPS Systems." In Advances in Network-Based Information Systems, 110–21. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98530-5_10.

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Brindha, M., P. Nabisal Afrine, R. Priyadarshini, and P. S. Manoharan. "Artificial Neural Network Based Fault Diagnosing System." In IoT Based Control Networks and Intelligent Systems, 885–95. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-5845-8_63.

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Leitold, Dániel, Ágnes Vathy-Fogarassy, and János Abonyi. "Reduction of Relative Degree by Optimal Control and Sensor Placement." In Network-Based Analysis of Dynamical Systems, 27–48. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36472-4_3.

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Conference papers on the topic "Network based control systems"

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"Network-based control systems." In IECON 2009 - 35th Annual Conference of IEEE Industrial Electronics (IECON). IEEE, 2009. http://dx.doi.org/10.1109/iecon.2009.5415381.

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"Network-based control systems." In IECON 2012 - 38th Annual Conference of IEEE Industrial Electronics. IEEE, 2012. http://dx.doi.org/10.1109/iecon.2012.6389394.

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"Network-based control systems." In IECON 2010 - 36th Annual Conference of IEEE Industrial Electronics. IEEE, 2010. http://dx.doi.org/10.1109/iecon.2010.5674959.

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"Network-based control systems." In IECON 2011 - 37th Annual Conference of IEEE Industrial Electronics. IEEE, 2011. http://dx.doi.org/10.1109/iecon.2011.6119712.

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"Network-based control systems." In IECON 2008 - 34th Annual Conference of IEEE Industrial Electronics Society. IEEE, 2008. http://dx.doi.org/10.1109/iecon.2008.4758419.

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Fujinaka, Toru, and Sigeru Omatu. "Network-Based Intelligent Control Systems." In 2008 International Conference on Computational Intelligence for Modelling Control & Automation. IEEE, 2008. http://dx.doi.org/10.1109/cimca.2008.105.

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Chai, Senchun, Lijing Dong, Baihai Zhang, and Xiangyun Chai. "Dynamic neural network based networked predictive control for Networked control systems." In 2011 9th IEEE International Conference on Control and Automation (ICCA). IEEE, 2011. http://dx.doi.org/10.1109/icca.2011.6138049.

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Lightowler, N., and H. Nareid. "Artificial Neural Network Based Control Systems." In SAE 2003 World Congress & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2003. http://dx.doi.org/10.4271/2003-01-0359.

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"Network based control systems and applications." In 2012 IEEE 21st International Symposium on Industrial Electronics (ISIE). IEEE, 2012. http://dx.doi.org/10.1109/isie.2012.6237369.

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"Network based control systems and applications." In 2011 IEEE 20th International Symposium on Industrial Electronics (ISIE). IEEE, 2011. http://dx.doi.org/10.1109/isie.2011.5984465.

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Reports on the topic "Network based control systems"

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Moles, Joshua. Chemical Reaction Network Control Systems for Agent-Based Foraging Tasks. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.2200.

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Calise, Anthony J. Neural Network Based Adaptive Control of Uncertain and Unknown Nonlinear Systems. Fort Belvoir, VA: Defense Technical Information Center, September 2001. http://dx.doi.org/10.21236/ada389515.

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Heggestad, Harold M. Knowledge-Based System Analysis and Control Defense Switched Network Task Areas. Fort Belvoir, VA: Defense Technical Information Center, September 1991. http://dx.doi.org/10.21236/ada543937.

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Heggestad, Harold M. Knowledge-Based System Analysis and Control Defense Switched Network Task Areas. Fort Belvoir, VA: Defense Technical Information Center, September 1987. http://dx.doi.org/10.21236/ada543939.

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Heggestad, Harold M. Knowledge-Based System Analysis and Control Defense Switched Network Task Areas. Fort Belvoir, VA: Defense Technical Information Center, September 1988. http://dx.doi.org/10.21236/ada543940.

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Seginer, Ido, James Jones, Per-Olof Gutman, and Eduardo Vallejos. Optimal Environmental Control for Indeterminate Greenhouse Crops. United States Department of Agriculture, August 1997. http://dx.doi.org/10.32747/1997.7613034.bard.

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Increased world competition, as well as increased concern for the environment, drive all manufacturing systems, including greenhouses, towards high-precision operation. Optimal control is an important tool to achieve this goal, since it finds the best compromise between conflicting demands, such as higher profits and environmental concerns. The report, which is a collection of papers, each with its own abstract, outlines an approach for optimal, model-based control of the greenhouse environment. A reliable crop model is essential for this approach and a significant portion of the effort went in this direction, resulting in a radically new version of the tomato model TOMGRO, which can be used as a prototype model for other greenhouse crops. Truly optimal control of a very complex system requires prohibitively large computer resources. Two routes to model simplification have, therefore, been tried: Model reduction (to fewer state variables) and simplified decision making. Crop model reduction from nearly 70 state variables to about 5, was accomplished by either selecting a subset of the original variables or by forming combinations of them. Model dynamics were then fitted either with mechanistic relationships or with neural networks. To simplify the decision making process, the number of costate variables (control policy parametrs) was recuced to one or two. The dry-matter state variable was transformed in such a way that its costate became essentially constant throughout the season. A quasi-steady-state control algorithm was implemented in an experimental greenhouse. A constant value for the dry-matter costate was able to control simultaneously ventilation and CO2 enrichment by continuously producing weather-dependent optimal setpoints and then maintaining them closely.
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Kokurina, O. Yu. VIABILITY AND RESILIENCE OF THE MODERN STATE: PATTERNS OF PUBLIC-LEGAL ADMINISTRATION AND REGULATION. Kokurina O.Yu., February 2022. http://dx.doi.org/10.12731/kokurina-21-011-31155.

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The modern understanding of the state as a complex social system allows us to assert that its resilience is based on ensuring systemic homeostasis as a stabilizing dynamic mechanism for resolving contradictions arising in society associated with the threat of losing control over the processes of public administration and legal regulation. Public administration is a kind of social management that ensures the organization of social relations and processes, giving the social system the proper coordination of actions, the necessary orderliness, sustainability and stability. The problem of state resilience is directly related to the resilience of state (public) administration requires a «breakthrough in traditional approaches» and recognition of «the state administration system as an organic system, the constituent parts and elements of which are diverse and capable of continuous self-development». Within the framework of the «organizational point of view» on the control methodology, there are important patterns and features that determine the viability and resilience of public administration and regulation processes in the state and society. These include: W. Ashby's cybernetic law of required diversity: for effective control, the degree of diversity of the governing body must be no less than the degree of diversity of the controlled object; E. Sedov’s law of hierarchical compensations: in complex, hierarchically organized and networked systems, the growth of diversity at the top level in the structure of the system is ensured by a certain limitation of diversity at its lower levels; St. Beer’s principle of invariance of the structure of viable social systems. The study was supported by the RFBR and EISI within the framework of the scientific project No. 21-011-31155.
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Pstuty, Norbert, Mark Duffy, Dennis Skidds, Tanya Silveira, Andrea Habeck, Katherine Ames, and Glenn Liu. Northeast Coastal and Barrier Network Geomorphological Monitoring Protocol: Part I—Ocean Shoreline Position, Version 2. National Park Service, June 2022. http://dx.doi.org/10.36967/2293713.

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Following a review of Vital Signs – indicators of ecosystem health – in the coastal parks of the Northeast Coastal and Barrier Network (NCBN), knowledge of shoreline change was ranked as the top variable for monitoring. Shoreline change is a basic element in the management of any coastal system because it contributes to the understanding of the functioning of the natural resources and to the administration of the cultural resources within the parks. Collection of information on the vectors of change relies on the establishment of a rigorous system of protocols to monitor elements of the coastal geomorphology that are guided by three basic principles: 1) all of the elements in the protocols are to be based on scientific principles; 2) the products of the monitoring must relate to issues of importance to park management; and 3) the application of the protocols must be capable of implementation at the local level within the NCBN. Changes in ocean shoreline position are recognized as interacting with many other elements of the Ocean Beach-Dune Ecosystem and are thus both driving and responding to the variety of natural and cultural factors active at the coast at a variety of temporal and spatial scales. The direction and magnitude of shoreline change can be monitored through the application of a protocol that tracks the spatial position of the neap-tide, high tide swash line under well-defined conditions of temporal sampling. Spring and fall surveys conducted in accordance with standard operating procedures will generate consistent and comparable shoreline position data sets that can be incorporated within a data matrix and subsequently analyzed for temporal and spatial variations. The Ocean Shoreline Position Monitoring Protocol will be applied to six parks in the NCBN: Assateague Island National Seashore, Cape Cod National Seashore, Fire Island National Seashore, Gateway National Recreation Area, George Washington Birthplace National Monument, and Sagamore Hill National Historic Site. Monitoring will be accomplished with a Global Positioning System (GPS )/ Global Navigation Satellite System (GNSS) unit capable of sub-meter horizontal accuracy that is usually mounted on an off-road vehicle and driven along the swash line. Under the guidance of a set of Standard Operating Procedures (SOPs) (Psuty et al., 2022), the monitoring will generate comparable data sets. The protocol will produce shoreline change metrics following the methodology of the Digital Shoreline Analysis System developed by the United States Geological Survey. Annual Data Summaries and Trend Reports will present and analyze the collected data sets. All collected data will undergo rigorous quality-assurance and quality-control procedures and will be archived at the offices of the NCBN. All monitoring products will be made available via the National Park Service’s Integrated Resource Management Applications Portal.
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Modlo, Yevhenii O., Serhiy O. Semerikov, Ruslan P. Shajda, Stanislav T. Tolmachev, and Oksana M. Markova. Methods of using mobile Internet devices in the formation of the general professional component of bachelor in electromechanics competency in modeling of technical objects. [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3878.

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The article describes the components of methods of using mobile Internet devices in the formation of the general professional component of bachelor in electromechanics competency in modeling of technical objects: using various methods of representing models; solving professional problems using ICT; competence in electric machines and critical thinking. On the content of learning academic disciplines “Higher mathematics”, “Automatic control theory”, “Modeling of electromechanical systems”, “Electrical machines” features of use are disclosed for Scilab, SageCell, Google Sheets, Xcos on Cloud in the formation of the general professional component of bachelor in electromechanics competency in modeling of technical objects. It is concluded that it is advisable to use the following software for mobile Internet devices: a cloud-based spreadsheets as modeling tools (including neural networks), a visual modeling systems as a means of structural modeling of technical objects; a mobile computer mathematical system used at all stages of modeling; a mobile communication tools for organizing joint modeling activities.
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Polak, Elijah. Optimization-Based Design of Control Systems. Fort Belvoir, VA: Defense Technical Information Center, February 1987. http://dx.doi.org/10.21236/ada182529.

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