Drone use to combat COVID-19: Adaptive tuning proposal of the control system under variable load

2021 ◽  
Vol 19 (6) ◽  
pp. 901-908
Author(s):  
Ivan Canal ◽  
Manuel Reimbold ◽  
Mauricio Campos
Robotica ◽  
1994 ◽  
Vol 12 (6) ◽  
pp. 553-561 ◽  
Author(s):  
D. T. Pham ◽  
S. J. Oh

SummaryThis paper describes an adaptive control system for an articulated robot with n joints carrying a variable load. The robot is a complex nonlinear time-varying MIMO plant with dynamic interaction between its inputs and outputs. However, the design of the control system is relatively straightforward and does not require any prior knowledge about the plant. This is because the control system is based on using neural networks which can capture the dynamic characteristics of the plant automatically. Three neural networks are employed in total, the first to learn the dynamics of the robot, the second to model its inverse dynamics and the third, a copy of the second neural network, to control the robot.


2004 ◽  
Vol 37 (6) ◽  
pp. 1009-1014
Author(s):  
Yasser M. Abdallah ◽  
Waldemar C. Leite Filho

Author(s):  
Antonio Piacentino ◽  
Fabio Cardona

The many comprehensive approaches formulated for the optimization of large industrial energy systems have been rarely applied to small and medium scale units, because of the difficulties in handling a continuously variable energy demand and of the lower margins for energy and emissions saving. Today, the growing interest for decentralised energy systems in the civil sector stimulates major efforts for the optimization of such plants, with a particular focus on the control system and on a management strategy able to exploit the opportunities existing in the free energy market. In this paper a methodology is proposed for the optimization of design and operation of variable demand systems supplying different non-storable products. In such systems, efficiency penalty due to off-design operation is usually assumed as a key issue; the proposed method, however, introduces an original and meaningful interpretation of the capital depreciation cost and keeps into account the possibility for grid connected power systems to produce surplus electricity to be sold. The proposed optimization process, based on the Lagrange multipliers method, assumes either an economic indicator (the Net Present Value, NPV or the Net Cash Flow, NCF) or a function depending only on fuel consumption (as usually proposed in literature) as objective function. Main advantages of the proposed method are the high level of integration between the optimization of design and operation and the possibility to automate the algorithm in order to drive a real-time optimized control system aiming to achieve the maximum profitability or the maximum primary energy saving.


Author(s):  
W. J. Abramson ◽  
H. W. Estry ◽  
L. F. Allard

LaB6 emitters are becoming increasingly popular as direct replacements for tungsten filaments in the electron guns of modern electron-beam instruments. These emitters offer order of magnitude increases in beam brightness, and, with appropriate care in operation, a corresponding increase in source lifetime. They are, however, an order of magnitude more expensive, and may be easily damaged (by improper vacuum conditions and thermal shock) during saturation/desaturation operations. These operations typically require several minutes of an operator's attention, which becomes tedious and subject to error, particularly since the emitter must be cooled during sample exchanges to minimize damage from random vacuum excursions. We have designed a control system for LaBg emitters which relieves the operator of the necessity for manually controlling the emitter power, minimizes the danger of accidental improper operation, and makes the use of these emitters routine on multi-user instruments.Figure 1 is a block schematic of the main components of the control system, and Figure 2 shows the control box.


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