@Article{iasc.2020.012549,
AUTHOR = {Qiming Zou, Ling Wang, Jie Liu, Yingtao Jiang},
TITLE = {A Progressive Output Strategy for Real-time Feedback Control Systems},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {26},
YEAR = {2020},
NUMBER = {3},
PAGES = {631--639},
URL = {http://www.techscience.com/iasc/v26n3/39997},
ISSN = {2326-005X},
ABSTRACT = {The real-time requirements imposed on a feedback control system are often hard to be met, 
as the controller spends a disproportionately large amount of time waiting for a control cycle 
to reach its final state. When such a final state is established, multiple tasks have to be 
prioritized and launched altogether simultaneously, and the system is given an extremely 
short time window to generate its output. This huge gap between the wait and action times, 
perceived as a load unbalancing problem, hinders a control decision to be made in real time. 
To address this challenging problem, in this paper, we present a progressive output strategy 
that divides a control cycle into a few fine-grained control intervals, and the entire workload 
is scheduled across these control intervals. Dubbed as Progressive Output Strategy (PROS), 
this approach actively requests intermediate states be created between adjacent control 
cycles in an adaptive manner. Specifically, as the sensing information is arriving, a system 
that adopts PROS can generate a series of intermediate solutions that eventually converge 
to the final optimal control signal. This way, the controller will no longer waste its time idling 
while waiting for the arrival of all the data for one-shot decision-making. Rather the system 
actually cuts down the waiting time and is able to act on the intermediate data/states 
throughout the entire control cycle. Experimental results have confirmed that adopting the 
PROS in a feedback control loop can evenly distribute the workload over a control cycle, and 
thus, the time delay is reduced by as much as two orders of magnitude, which is essential to 
meet the most stringent timing requirements.},
DOI = {10.32604/iasc.2020.012549}
}