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Precision motion control is often challenged by asynchronous sensor update and quantization noise, causing abrupt and untimely state variation to limit the machine precision. To provide smooth and accurate sensor interpretation, this study developed a novel event-triggered sub-count estimation method that addresses continuity on system states. By enforcing such state continuity on important properties...
Soil contamination is an enormous problem in China and severely threatens environmental quality and food safety. Desorption of contaminants from soil is a critical process controlling the availability of soil contaminants and thus the risk associated with contaminated soil. All the currently adopted desorption models greatly simplify desorption by assuming that desorption is a simple reverse of adsorption...
This paper proposes a suboptimal nonlinear model predictive control (NMPC) algorithm based on Genetic Algorithm (GA). A nonlinear programming problem is solved online in NMPC. GA has been successfully applied to nonlinear programming problems where other decent-based methods have often failed. In this paper GA is used to optimize the control sequence per sampling time. In order to reduce the computational...
In this paper, a model predictive controller for time delay capsubot system is presented. Linearized dynamics is used to predictive future system behavior and a control law is derived from a quadratic cost function penalizing the system tracking error and the control effort. It is noted that model predictive control has advantages over state feedback law because of consideration of constraints on...
The prominent virtues of grey prediction are small information, few data and a little of computation. The conventional PID controller has strong robustness, sophisticated technology and simple structure, so it has been used widely in the process control. With the adjustable role of feedback response of biological immune systems, the capability of simulating non-linear functions with fuzzy rationalizing...
Linear auto-regression moving average with extra input (ARMAX) model for air temperature system in a naturally ventilated greenhouse was developed. Outside air temperature, relative humidity, global solar radiation and wind speed were used as disturbing input variables of the model, while inside temperature was used as output variable of the model. Based on energy and mass flows equations, statistic...
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