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Flotation process with model free adaptive control
2017 IEEE International Conference on Information and Automation (ICIA), 2017Flotation is a physical process to separate the useful mineral and gangue using the hydrophilicity or sparseness of the mineral itself or that from chemicals effects. Because of the non-linear, strong coupling, multivariate and time delay, it is hard to establish the quite accurate and effect model of flotation process, thus this paper proposes the ...
Wenqian Xue, Jialu Fan, Yi Jiang 0007
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Model‐free control of a seeded batch crystallizer
The Canadian Journal of Chemical Engineering, 2017AbstractAs the use of a batch crystallization process in several industrial applications is extensive, finding an effective control strategy is important to improve the product quality, which is typically characterized by a unimodal and narrow crystal size distribution (CSD) with a large mean crystal size.
Afsi, Nawel +3 more
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Design and Control of a Neonatal Incubator Using Model-Free Control
2021 29th Mediterranean Conference on Control and Automation (MED), 2021Prematurely newborn infants are unable to regulate their own body temperature. Therefore, these infants are placed in incubators where temperature is maintained at suitable levels. Because stability of temperature in the incubator is essential to the survival and recovery of the infant, a robust control system needs to be used in order to maintain it ...
Ali Ismail +3 more
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Model-free learning of wire winding control
2013 9th Asian Control Conference (ASCC), 2013In this paper we introduce a reinforcement learning approach to optimize the wire profile generated by an automated wire winding machine. The wire winder spools wire onto large bobbins, while trying to maintain an even wire profile across the bobbin. Uneven profiles that contain bumps or gaps (i.e.
Abdel Rodríguez +3 more
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A model-free decentralized control for robot manipulators
Proceedings of International Conference on Robotics and Automation, 2002A model-free robust/adaptive decentralized controller for nonlinear uncertain robot manipulators is presented. The proposed controller consists of a PD controller, a robust/adaptive controller and dynamic compensator. The dynamic compensator is online up-dated based on the Taylor expansion in terms of the historical information of the individual local ...
Lilong Cai, Xiaoqi Tang
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Event driven model free control of quadrotor
2013 IEEE International Conference on Control Applications (CCA), 2013In this paper we propose a new control approach, event driven model free control, which deals with the “tradeoff” between computational cost and system performance. The model free control scheme demands low computational resources and has high robustness, which is especially suitable for systems with complex dynamics and/or affected by disturbances ...
Wang, Jing +4 more
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Composition control for STEC plant by a model free control method
SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483), 2004Because of the use of binary mixtures ammonia and water as the working fluid in STEC, if the composition of ammonia is not high enough, the working fluid may condense in the turbine, which results in a fatal damage of turbine. Since controlled variable of vapor composition has a strong nonlinear relationship with state variables vapor pressure and ...
Zhao Zhong +2 more
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A Revisit to Model-Free Control
IEEE Transactions on Power Electronics, 2022Wanrong Li +3 more
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Model-Free Learning Control for processes with constrained incremental control
2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control, 2006This paper proposes a technique to design controllers for systems with constrained incremental control and input-output constraints called Model-Free Learning Control (MFLC). MFLC, which is based on Reinforcement Learning algorithms, is a simple approach without needing precise detailed information of the system.
S. Syafiie, F. Tadeo, E. Martinez
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Cooperative Adaptive Model-Free Control With Model-Free Estimation and Online Gain Tuning
IEEE Transactions on Cybernetics, 2022In this article, a distributed adaptive model-free control algorithm is proposed for consensus and formation-tracking problems in a network of agents with completely unknown nonlinear dynamic systems. The specification of the communication graph in the network is incorporated in the adaptive laws for estimation of the unknown linear and nonlinear terms,
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