scholarly journals Investigation of the mobile platform motion optimal control at energy performance index

PAMM ◽  
2009 ◽  
Vol 9 (1) ◽  
pp. 641-642
Author(s):  
Krzysztof Kalinski ◽  
Michal Mazur
2013 ◽  
Vol 198 ◽  
pp. 90-95 ◽  
Author(s):  
Krzysztof J. Kaliński ◽  
Cezary Buchholz

Current tendency in mechatronic design requires the use of comprehensive development of an environment, which gives the possibility to prototype, design, simulate and integrate with dedicated hardware. The paper discusses the Hardware-In-the-Loop Simulations (HILS) mechatronic technique [, used during the design of the surveillance system based on energy performance index [. The presented test configuration (physical controller emulated virtual research object) allows authors to verify responses (in the LabVIEW [) of the mobile platform model, to the optimal control commands (torques), generated by the Real Time controller. Defined energy performance index, supported by the correction velocities, controls the emulated platform while moving along three different trajectories. The demonstrated test results are compared with desired values obtained during numerical computation process of kinematic and dynamic equations of the presented model. The authors investigation of the HILS affected final optimisation of the motion surveillance system design. Real time requirements enforced authors to decrease sampling time of control command (signal generation frequency) and establish high performance execution strategy for on-line algorithm (algorithm execution performed both in Real Time processor and in the FPGA - Field Programmable Gate Array) [. The performed simulations confirmed that the HILS is a powerful technique, which improves system design making that more efficient and low cost consuming.


2006 ◽  
Vol 51 (12) ◽  
pp. 1903-1919 ◽  
Author(s):  
Mato Baoti ◽  
Frank J. Christophersen ◽  
Manfred Morari

Buildings ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 195
Author(s):  
Nam-Chul Seong ◽  
Jee-Heon Kim ◽  
Wonchang Choi

Optimizing the operating conditions and control set points of the heating, ventilation, and air-conditioning (HVAC) system in a building is one of the most effective ways to save energy and improve the building’s energy performance. Here, we optimized different control variables using a genetic algorithm. We constructed and evaluated three optimal control scenarios (cases) to compare the energy savings of each by varying the setting and number and type of the optimized control variables. Case 1 used only air-side control variables and achieved an energy savings rate of about 5.72%; case 2 used only water-side control variables and achieved an energy savings rate of 16.98%; and case 3, which combined all the control variables, achieved 25.14% energy savings. The energy savings percentages differed depending on the setting and type of the control variables. The results show that, when multiple control set points are optimized simultaneously in an HVAC system, the energy savings efficiency becomes more effective. It was also confirmed that the control characteristics and energy saving rate change depending on the location and number of control variables when optimizing using the same algorithm.


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