Relevant bibliographies by topics / Limiting algorithm control

Academic literature on the topic 'Limiting algorithm control'

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Published: 30 May 2022
Last updated: 31 May 2022

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Journal articles on the topic "Limiting algorithm control"

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张, 品. "A Research Based on Adaptive Rate Limiting Congestion Control Algorithm." Hans Journal of Wireless Communications 05, no. 01 (2015): 36–42. http://dx.doi.org/10.12677/hjwc.2015.51006.

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Wand, Yair, and Ron Weber. "Limiting the Search Space during Controls Evaluation of a Modified Information System." Journal of Information Systems 32, no. 3 (September 1, 2017): 91–111. http://dx.doi.org/10.2308/isys-51908.

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ABSTRACT Controls must be changed when information systems are modified. Audit, assurance, and quality-control (AAQC) personnel must evaluate the reliability of controls in the new system versions. Based on Bunge (1977, 1979) and Wand and Weber (1989a, 1990), we describe a model and search-space algorithm that AAQC personnel can use to determine where required control changes are likely to be located in the new system version, thereby mitigating the need for an exhaustive evaluation of all controls. To use the model and algorithm, AAQC personnel must have (1) accurate and complete requirements specifications for the old and new versions of the system, (2) a controls specification for the old version that covers all errors and irregularities that might occur, (3) evidence to conclude all controls for the old version are in place, adequate, and working, and (4) specifications for the new version expressed as a level structure of systems and subsystems.
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Ait Sahed, Oussama, Kamel Kara, and Mohamed Laid Hadjili. "Constrained Fuzzy Predictive Control Using Particle Swarm Optimization." Applied Computational Intelligence and Soft Computing 2015 (2015): 1–15. http://dx.doi.org/10.1155/2015/437943.

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A fuzzy predictive controller using particle swarm optimization (PSO) approach is proposed. The aim is to develop an efficient algorithm that is able to handle the relatively complex optimization problem with minimal computational time. This can be achieved using reduced population size and small number of iterations. In this algorithm, instead of using the uniform distribution as in the conventional PSO algorithm, the initial particles positions are distributed according to the normal distribution law, within the area around the best position. The radius limiting this area is adaptively changed according to the tracking error values. Moreover, the choice of the initial best position is based on prior knowledge about the search space landscape and the fact that in most practical applications the dynamic optimization problem changes are gradual. The efficiency of the proposed control algorithm is evaluated by considering the control of the model of a 4 × 4 Multi-Input Multi-Output industrial boiler. This model is characterized by being nonlinear with high interactions between its inputs and outputs, having a nonminimum phase behaviour, and containing instabilities and time delays. The obtained results are compared to those of the control algorithms based on the conventional PSO and the linear approach.
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Li, Ting Gui, and Gang Li. "Annular Heating Furnace Temperature Control Based on the Fuzzy-PID Algorithm and Cascade Double-Cross Limiting Control." Applied Mechanics and Materials 556-562 (May 2014): 2478–82. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.2478.

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Annular heating furnace temperature control is a typical and complex industrial process control system,with the characteristics of multivariable,time-varying parameters,nonlinear,coupling, large inertia and pure delay,so it is difficult to obtain satisfactory control effect when using conventional PID control. In view of the above problems, adopting fuzzy PID algorithm and cascade double-cross limiting control, combustion control effect is greatly improved, self-tuning of PID parameters is realized, and control quality is enhanced. The experimental results show that, fuzzy PID control shows good dynamic and steady performance, its control effect is significantly improved when compared with conventional PID control, and it has better overall performance.
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Abbas, Mohammed Qasim, and Yaser Atta Yassin. "Modification of speed and current limiting performance of BLDC motor based on harmony search optimization method." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 1 (April 1, 2020): 549. http://dx.doi.org/10.11591/ijeecs.v18.i1.pp549-557.

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The brushless DC (BLDC) motor is a multi-variable and non-linear system so that it's required more advanced explaining and controlling set. In this work, an algorithm is proposed based on the harmony search algorithm (HAS) method. HSA mimics music improvisation process to find the optimal solution. In BLDC motor, many constraints are required; speed performance and current limiting control are dominated. HAS is proposed to find the optimal PID parameters for the two speed and current-limiting controllers that are proposed in the drive. By Matlab/Simulink results, a good performance is shown compared with the classical method that absence current-limiting controller.
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Cui, Jing Jun. "Motor Drive Control Based on Microcontroller and PID." Applied Mechanics and Materials 484-485 (January 2014): 511–14. http://dx.doi.org/10.4028/www.scientific.net/amm.484-485.511.

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This paper describes the incremental PID control algorithm and the basic principles of motor soft start, and introduced STM32F103RB8 basic performance microcontroller, combined with incremental PID control advantages, and gives MCU in motor soft start process control application. Practice shows that the incremental PID applications, simplifying the control ideas to improve the performance of the current loop control, limiting the starting current, smooth start-up speed, and achieved good results motor start.
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Du, Xian Jun, Xiao Hong Hao, and Ping Yu. "A Clonal Selection Algorithm Based Optimization of Activated Sludge Process." Advanced Materials Research 490-495 (March 2012): 19–23. http://dx.doi.org/10.4028/www.scientific.net/amr.490-495.19.

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A Clonal Selection Algorithm (CSA) was used in this article to the wastewater biological treatment activated sludge process optimization with the lowest operational costs by limiting total substrate discharge mass. A simulation result shows that the method is efficiency, and it also provides a new approach for other optimal control problem.
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Knaga, Jarosław, Stanisław Lis, Sławomir Kurpaska, Piotr Łyszczarz, and Marcin Tomasik. "Optimisation of Energy Use in Bioethanol Production Using a Control Algorithm." Processes 9, no. 2 (February 2, 2021): 282. http://dx.doi.org/10.3390/pr9020282.

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In this work, the possibility of limiting energy consumption in the manufacturing process of bioethanol to obtain biofuel was analysed. For this purpose, a control algorithm has been optimised while retaining the good quality of the control signals. New in this study is the correlation of the control algorithm not only with the signal’s quality, but also with the energy consumption in such an energy-intensive process as rectification. The rectification process in a periodic production system has been researched. The process was modelled on a test station with the distillation mixture capacity of 25 dm3. For the optimization, the following control algorithms have been applied: relay, PID and PID after modification to I-PD. The simulation was carried out on a transfer function model of the plant that has been verified on a real object, a rectification column. The simulations of energy consumption and control signal’s quality have been carried out in the Matlab®-Simulink environment after implementing the model of the research subject and control algorithms. In the simulation process, an interference signal with an amplitude of 3% and frequency of 2 mHz was used. The executed analyses of the control signal quality and the influence of the control algorithm on the energy consumption has shown some essential mutual relationships. The lowest energy consumption in the rectification process can be achieved using the I-PD controller—however, the signal quality deteriorates. The energy savings are slightly lower while using the PID controller, but the control signal quality improves significantly. From a practical point of view, in the considered problem the best control solution is the classic PID controller—the obtained energy effect was only slightly lower while retaining the good quality of the control signals.
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Lee, Taehyun, Eungsu Han, Un-Chul Moon, and Kwang Y. Lee. "Supplementary Control of Air–Fuel Ratio Using Dynamic Matrix Control for Thermal Power Plant Emission." Energies 13, no. 1 (January 2, 2020): 226. http://dx.doi.org/10.3390/en13010226.

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This paper proposes a supplementary control for tighter control of the air–fuel ratio (AFR), which directly affects the environmental emissions of thermal power plants. Dynamic matrix control (DMC) is applied to the supplementary control of the existing combustion control loops and the conventional double cross limiting algorithm for combustion safety is formulated as constraints in the proposed DMC. The proposed supplementary control is simulated for a 600-MW drum-type power plant and 1000 MW ultra-supercritical once-through boiler power plant. The results show the tight control of the AFR in both types of thermal power plants to reduce environmental emissions.
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Ma, Li, Jiayuan Shan, Junhui Liu, and Yan Ding. "Missile IGC Based on Improved Model Predictive Control and Sliding Mode Observer." International Journal of Aerospace Engineering 2021 (November 16, 2021): 1–14. http://dx.doi.org/10.1155/2021/9680346.

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Considering recurrent optimization process in model predictive control (MPC), the model uncertainties and disturbances terms in the missile’s guidance and control model can degrade recursive feasibility, and there are control mutation problems in common MPC algorithm. This paper presents a disturbance rejection model predictive control algorithm for missile integrated guidance and control (IGC). Firstly, a sliding mode observer (SMDO) is designed to estimate the unknown disturbances caused by target maneuvering. Secondly, the method of optimizing control increment is adopted in MPC to avoid the phenomenon of control mutation in the model calculation. By limiting the control increment in each cycle, it ensures the continuity of the control input. Thirdly, by combining the SMDO and MPC, an IGC algorithm is presented, and the stability of the algorithm is proved by using Lyapunov stability theory. Finally, the simulation results with different impact angles verify the effectiveness of the proposed algorithm for intercepting maneuver target.
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Dissertations / Theses on the topic "Limiting algorithm control"

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Чамата, Сергій Миколайович. "Технологічне забезпечення шліфування оправок станів холодної прокатки труб." Doctoral thesis, Київ, 2015. https://ela.kpi.ua/handle/123456789/13928.

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Book chapters on the topic "Limiting algorithm control"

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Mirchandani, Vinod, Ante Prodan, and Olivier Marcé. "TPC and Non-TPC Based Topology Control Approaches for QoS Improvement in MR-WMN." In Wireless Network Traffic and Quality of Service Support, 304–29. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-61520-771-8.ch012.

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A grand challenge in Multi-Radio Wireless Mesh Networks (MR-WMN) is to limit the interference such that its net capacity increases without compromising scalability and stability. In this chapter, the authors first provide an insight into the implications of transmit power control (TPC) on the MR-WMN topology and QoS. In this regard, a review of some of the key work is carried out they then explore the approach of non-TPC based topology control schemes for limiting the interference in a static nodes based MR-WMN system that uses a distributed, light-weight, cooperative multiagents. A path reduction (PR) algorithm is the principle behind our topology control scheme and its viability is explained through NetLogo tool based simulation results. The effectiveness of the PR algorithm is shown in terms of improved interference cost reduction and decrease in path length. The focus of this chapter is mainly on non-TPC approach rather than the TPC approach.
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Ani, Vincent Anayochukwu. "Optimal Operational Strategy for PV/Wind-Diesel Hybrid Power Generation System with Energy Storage." In Renewable and Alternative Energy, 1438–60. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-1671-2.ch050.

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Telecommunications industry requires efficient, reliable and cost-effective hybrid power system as alternative to the power supplied by diesel generator. This paper proposed an operational control algorithm that will be used to control and supervise the operations of PV/Wind-Diesel hybrid power generation system for GSM base station sites. The control algorithm was developed in such a way that it coordinates when power should be generated by renewable energy (PV panels and Wind turbine) and when it should be generated by diesel generator and is intended to maximize the use of renewable system while limiting the use of diesel generator. Diesel generator is allocated only when the demand cannot be met by the renewable energy sources including battery bank. The developed algorithm was used to study the operations of the hybrid PV/Wind-Diesel energy system. The control simulation shows that the developed algorithm reduces the operational hours of the diesel generator thereby reducing the running cost of the hybrid energy system as well as the pollutant emissions. With the data collected from the site, a detailed economic and environmental analysis was carried out using micro power optimization software homer. The study evaluates savings associated with conversion of the diesel powered system to a PV/Wind-Diesel hybrid power system.
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Bäck, Thomas. "An Empirical Comparison." In Evolutionary Algorithms in Theory and Practice. Oxford University Press, 1996. http://dx.doi.org/10.1093/oso/9780195099713.003.0009.

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Given the discussions about Evolutionary Algorithms from the previous chapters, we shall now apply them to the artificial topologies just presented. This will be done by simply running the algorithms in their standard forms (according to the definitions of standard forms as given in sections 2.1.6, 2.2.6, and 2.3.6) for a reasonable number of function evaluations on these problems. The experiment compares an algorithm that self-adapts n standard deviations and uses recombination (the Evolution Strategy), an algorithm that self-adapts n standard deviations and renounces recombination (meta-Evolutionary Programming), and an algorithm that renounces self-adaptation but stresses the role of recombination (the Genetic Algorithm). Furthermore, all algorithms rely on different selection mechanisms. With respect to the level of self-adaptation, the choice of the Evolution Strategy and Evolutionary Programming variants is fair, while the Genetic Algorithm leaves us no choice (i.e., no self-adaptation mechanism is used within the standard Genetic Algorithm). Concerning the population size the number of offspring individuals (λ) is adjusted to a common value of λ = 100 in order to achieve comparability of population sizes while at the same time limiting the computational requirements to a justifiable amount. This results in the following three algorithmic instances that are compared here (using the standard notation introduced in chapter 2): • ES(n,0,rdI, s(15,100)): An Evolution Strategy that self-adapts n standard deviations but does not use correlated mutations. Recombination is discrete on object variables and global intermediate on standard deviations, and the algorithm uses a (15,100)-selection mechanism. • mEP(6,10,100): A meta-Evolutionary Programming algorithm that — by default — self-adapts n variances and controls mutation of variances by a meta-parameter ζ = 6. The tournament size for selection and the population size amount to q = 10 and μ = 100, respectively. • GA(30,0.001,r{0.6, 2}, 5,100): A Genetic Algorithm that evolves a population of μ = 100 bitstrings of length l = 30 • n, each. The scaling window size for linear dynamic scaling is set to ω = 5. Proportional selection, a two-point crossover operator with application rate 0.6 and a mutation operator with bit-reversal probability 1.0·10−3 complete the algorithm.
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Bayramov, Azad Agalar, and Elshan Giyas Hashimov. "Application SMART for Small Unmanned Aircraft System of Systems." In Handbook of Research on Artificial Intelligence Applications in the Aviation and Aerospace Industries, 193–213. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1415-3.ch008.

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This chapter presents results of SMART for small Unmanned Aerial Vehicles System of Systems complex making, the development of complex control and Infrared communication algorithms, investigations of operation effectiveness of reconnaissance SMART UAVs System-of-System and of the distributed systems of wireless sensors. The development of UAV System-of-System complex and the military tactic tasks and reconnaissance application have been considered. The problems upon providing effective functioning of reconnaissance UAV during analysis and control of highly dynamic scenes are considered. It is shown that during the optimum regime of functioning and taking into account given limiting conditions on total radiation power of radio signals, the reconnaissance UAV should possess the current radiation power inversely proportional to the amount of signal-noise ratio. The technical realization of such optimum regimes is possible by way of development of adaptive control of transmitter power depending on the amount of useful signal detected during reconnaissance activity of UAV.
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Sang, Aimin, Guosen Yue, Xiaodong Wang, and Mohammad Madihian. "Cross-Layer Performance of Scheduling and Power Control Schemes in Space-Time Block Coded Downlink Packet Systems." In Handbook on Advancements in Smart Antenna Technologies for Wireless Networks, 374–97. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-59904-988-5.ch018.

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In this chapter, we consider a cellular downlink packet data system employing the space-time block coded (STBC) multiple- input-multiple-output (MIMO) scheme. Taking the CDMA high data rate (HDR) system for example, we evaluate the cross-layer performance of typical scheduling algorithms and a point-to-point power control scheme over a time division multiplexing (TDM)-based shared MIMO channel. Our evaluation focuses on the role of those schemes in multi-user diversity gain, and their impacts on medium access control (MAC) and physical layer performance metrics for delay-tolerant data services, such as throughput, fairness, and bit or frame error rate. The cross-layer evaluation shows that the multi-user diversity gain, which comes from opportunistic scheduling schemes exploiting independent channel oscillations among multiple users, can increase the aggregate throughput and reduce the transmission error rate. It also shows that STBC/MIMO and one-bit and multi-bit power control can indeed help the physical and MAC layer performance but only at a risk of limiting the multiuser diversity gain or the potential throughput of schedulers for delay-tolerant bursty data services.
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Conference papers on the topic "Limiting algorithm control"

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Liers, Florian, Bernd Hochberg, Markus Malicke, and Andreas Mitschele-Thiel. "Limiting UMTS Dropping Rate with Control-Based CAC Algorithm." In 2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications. IEEE, 2006. http://dx.doi.org/10.1109/pimrc.2006.254203.

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Price, Jack, Damien Laird, and Ioannis Raptis. "Spider Bots: A Low Cost Platform for Testing and Validating Cooperative Control Algorithms." In ASME 2014 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/dscc2014-6041.

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A primary factor limiting the development, testing, and validation of decentralized algorithms for large-scale multi-robot teams is the high cost of the available systems. When a successful test necessitates that an algorithm functions on dozens or even hundreds of robots simultaneously, a low price tag on each robot is crucial. This paper presents Spider-Bots, a low cost platform for testing and validating control algorithms for multi-robot swarms. The platform is comprised of centimeter-scale mobile robots that can communicate wirelessly and interact with their environment, along with easy to use software libraries. The resulting platform was validated by testing its ability to execute and record data from three separate algorithms: Set-point navigation, object manipulation, and collision avoidance.
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Roberts, Luke, Hugh A. Bruck, and Satyandra K. Gupta. "Autonomous Loitering Control for a Flapping Wing Miniature Aerial Vehicle With Independent Wing Control." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-34752.

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Flapping wing miniature aerial vehicles (FWMAVs) offer advantages over traditional fixed wing or quadrotor MAV platforms because they are more maneuverable than fixed wing aircraft and are more energy efficient than quadrotors, while being quieter than both. Currently, autonomy in FWMAVs has only been implemented in flapping vehicles without independent wing control, limiting their level of control. We have developed Robo Raven IV, a FWMAV platform with independently controllable wings and an actuated tail controlled by an onboard autopilot system. In this paper, we present the details of Robo Raven IV platform along with a control algorithm that uses a GPS, gyroscope, compass, and custom PID controller to autonomously loiter about a predefined point. We show through simulation that this system has the ability to loiter in a 50 meter radius around a predefined location through the manipulation of the wings and tail. A simulation of the algorithm using characterized GPS and tail response error via a PID controller is also developed. Flight testing of Robo Raven IV demonstrated the success of this platform, even in winds of up to 10 mph.
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Miller, Christopher, Kelilah Wolkowicz, Jariullah Safi, and Sean N. Brennan. "State of Charge Estimation for an Electric Wheelchair Using a Fuel Gauge Model." In ASME 2016 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/dscc2016-9802.

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Electric wheelchair users depend on a reliable power system in order to regain mobility in their daily lives. If a wheelchair’s battery power depletes without the user being aware, the individual may become stranded, further limiting their freedom of mobility and potentially placing the user in a harmful situation. This research seeks to develop a State-of-Charge (SOC) estimator for the batteries of an electric wheelchair. A second-order equivalent circuit battery model is developed and parameterized for a wheelchair’s lead-acid battery pack. To simplify the SOC estimation, this algorithm models a vehicle’s fuel gauge. A coulomb accumulator is incorporated to estimate energy usage in the non-linear region of the OCV-SOC curve, while a Kalman filter is used to estimate SOC in the linear region of the curve. The estimator is verified using experimentally collected data on-board a robotic wheelchair. The implementation of these algorithms with powered wheelchairs can significantly improve the estimation of wheelchair battery power and can ultimately be coupled with warning systems to alert users of depleting battery life, as well as enable low-power modes to increase wheelchair user safety.
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Breidi, Farid, Jordan Garrity, and John Lumkes. "Investigation of a Real-Time Pressure Based Valve Timing Correction Algorithm." In ASME/BATH 2017 Symposium on Fluid Power and Motion Control. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/fpmc2017-4342.

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Digital hydraulics is an emerging field in fluid power, complementing conventional hydraulic and potentially improving efficiency and dynamic performance. High speed electrically controlled on/off valves are key enablers for many digital hydraulic systems, and specifically for digital pump/motors. This work investigates a 4-quadrant 3-piston digital pump/motor utilizing two electrically controlled high speed on/off valves per displacement chamber. The test unit was simulated, built, and experimentally tested. Simulation and experimental results showed the importance of valve response times on the overall performance and efficiency of the digital pump/motor, where a small error in the delay in the valve opening or closing could lead to significant energy losses. To minimize the impact of valve variability, a real-time valve correction algorithm was developed to account for the error in valve timing. The algorithm uses the pressure readings at the low and high pressure ports to detect the time at which the pressure ripple occurred and then obtain the delay in the valve timing. It calculates the turn-on and turn-off valve delay times in all displacement chambers in a three-piston pump with two valves per chamber, detecting a total of 12 valve delay times. The code was tested for sequential flow diverting and sequential flow limiting operating modes at a wide range of displacement (25% to 100%) with pressures ranging from 25 bar to 105 bar and shaft speeds up to 700 rpm (limited by the valves speed). It was also tested for flow diverting mode and gave good results for displacements between 70% and 100%. The error in the calculated delay times was below 5% in all of the tested conditions, providing major improvements to the digital pump system, and to digital hydraulics in general.
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Kim, Youngki, Shankar Mohan, Jason B. Siegel, and Anna G. Stefanopoulou. "Maximum Power Estimation of Lithium-Ion Batteries Accounting for Thermal and Electrical Constraints." In ASME 2013 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/dscc2013-3935.

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Enforcement of constraints on the maximum deliverable power is essential to protect lithium-ion batteries from over-charge/discharge and overheating. This paper develops an algorithm to address the often overlooked temperature constraint in determining the power capability of battery systems. A prior knowledge of power capability provides dynamic constraints on currents and affords an additional control authority on the temperature of batteries. Power capability is estimated using a lumped electro-thermal model for cylindrical cells that has been validated over a wide range of operating conditions. The time scale separation between electrical and thermal systems is exploited in addressing the temperature constraint independent of voltage and state-of-charge (SOC) limits. Limiting currents and hence power capability are determined by a model-inversion technique, termed Algebraic Propagation (AP). Simulations are performed using realistic depleting currents to demonstrate the effectiveness of the proposed method.
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Kalanovic, V. D., K. Padmanabhan, and C. H. Jenkins. "A Discrete Cell Model for Shape Control of Precision Membrane Antennae and Reflectors." In ASME 1999 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/imece1999-0548.

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Abstract The potential for placing large precision reflectors in space is currently being investigated through the use of inflatable membrane structures. Their capacity for reducing launch mass and stowed volume is being exploited. However, on-orbit performance will require an understanding of the various influences on the deployment, inflation, and service of the membrane, and the associated effects on reflector surface precision. Nonlinear controllers developed to improve performance of such systems are often dependent on state estimation and parameter identification procedures. The existence of these procedures, within the control strategy, increases the size of the algorithms, limiting the system performance in real-time. The research presented has as a main objective to create an intelligent controller, based on feedback error learning, which is capable of extracting performance information from precision large membrane deployables, and subsequently using this information to achieve maximum surface precision. This paper presents a method to spatially discretize a doubly-curved membrane model into N = m × n spring-mass-damper cells. A recursive algorithm is developed and used in a simulator to predict the surface profile of the membrane. Each cell is connected to a feedback error learning controller in order to extract local state estimations. Simulation results are then compared to finite element predictions. The discrete cell model is shown to be simple enough for real-time control strategies, and potential methods for sensing/actuating to close the loop are discussed.
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Xiong, Qiuchi, Xiaofan Li, Dillon Martin, Sijing Guo, and Lei Zuo. "Semi-Active Control for Two-Body Ocean Wave Energy Converter by Using Hybrid Model Predictive Control." In ASME 2018 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/dscc2018-9157.

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Model predictive control (MPC) has been considered as one important feed-forward optimal control strategy for ocean wave energy converter (WEC) targeted on power maximization. The capability of MPC to handle system constraints (ex. stroke, velocity, actuator limitations), and the availability to provide optimal solution for linear system provide potential for the implementation of such algorithm in the WEC control. However, currently, only active MPC control has been introduced for single and two-body WECs. Such control strategy may introduce negative power during the optimization process, since the power take-off (PTO) damping has no constraint. In this paper, we proposed a hybrid MPC strategy in limiting both the PTO damping force and PTO damping to avoid negative power generation during cost function minimization (negative power minimization) for the two-body WEC. The problem is formulated into a quadratic programming (QP) problem targeted at power maximization. However, the standard QP problem formulation cannot be directly applied to the semi-active control problem due to the PTO damping constraints. Therefore, the problem is reformulated as a Mixed-integer Quadratic Programming (MIQP) problem, which contains logical switch to select constraint matrices based on the sign of the relative velocity between the buoy and submerged body. The optimal solution is compared with those of the active MPC control strategy and the passive model with the same irregular wave input.
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Russell, David W. "On the Control of Dynamically Unstable Systems Using a Self Organizing Black Box Controller." In ASME 7th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2004. http://dx.doi.org/10.1115/esda2004-58290.

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Many systems are difficult to control by conventional means because of the complexity of the very fabric of their being. Some systems perform very well under some conditions and then burst into wild, maybe even chaotic, oscillations for no apparent reason. Such systems exist in bioreactors, electro-plating and other application domains. In these cases a model may not exist that can be trusted to accurately replicate the dynamics of the real-world system. BOXES is a well known methodology that learns to perform control maneuvers for dynamic systems with only cursory a priori knowledge of the mathematics of the system model. A limiting factor in the BOXES algorithm has always been the assignment of appropriate boundaries to subdivide each state variable into regions. In addition to suggesting a method of alleviating this weakness, the paper shows that the accumulated statistical data in near neighboring states may be a powerful agent in accelerating learning, and may eventually provide a possible evolution to self-organization.
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Gaston, John R., W. Brian Piercy, and C. Scott Harclerode. "Integrated Turbine-Compressor Controls Retrofit for an Olefins Unit." In ASME 1995 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/95-gt-349.

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The Olefins Unit that is the subject of this case study has been operating for 25 years. Recently, the unit initiated a control system retrofit program to increase availability, save energy, and improve access to operating information. New control systems were installed on the ethylene, propylene and furnace gas compressor trains. The gas compression equipment consists of single and multi-case compressor trains driven by steam and gas turbines and electric motors. Significant control system improvements were made to the turbine/compressor speed/load regulation and temperature limiting. The systems also execute “safety system” logic for process and machinery protection. In addition to integrated turbine compressor control, the strategy that incorporates all control functions for the entire compresor train, a new anti-surge algorithm is included. To meet more stringent availability requirements imposed by integration, a triple modular redundant (TMR) system structure is employed. The surge algorithm described in this paper accurately predicts where surge occurs, regardless of changes in gas composition and conditions (e.g., molecular weight, temperature, etc.), and allows the integrated controls to compensate accordingly. A PC workstation-based operator display is provided for enhanced operator awareness of machinery conditions. This paper describes the requirements and implementation of this new approach to control.
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