Advances in power electronics and digital control open a new horizon in the control of power converters. Particularly, modelpredictivecontrol has been developed for control applications in industrial electronics and...
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Advances in power electronics and digital control open a new horizon in the control of power converters. Particularly, modelpredictivecontrol has been developed for control applications in industrial electronics and power systems. This study presents a comprehensive study on recent achievements of model predictive control algorithms to overcome the challenges in the real-time implementation of power converter control, which is the lowest level control of hierarchical control in microgrids. The study shows that most of these alternate solutions can enhance system reliability, stability, and efficiency. The control platform devices for the real-time implementation of these algorithms are compared. The related issues are discussed and classified, respectively. Finally, a summary is provided, leading to some further research questions and future work.
The use of linear parameter varying (LPV) prediction models has been proven to be an effective solution to develop modelpredictivecontrol (MPC) algorithms for linear and non-linear systems. However, the computationa...
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The use of linear parameter varying (LPV) prediction models has been proven to be an effective solution to develop modelpredictivecontrol (MPC) algorithms for linear and non-linear systems. However, the computational effort is a crucial issue for LPV-MPC, which has severely limited its application especially in embedded control. Indeed, for dynamical systems of dimension commonly found in embedded applications, the time needed to form the quadratic programming (QP) problem at each time step, can be substantially higher than the average time to solve it, making the approach infeasible in many control boards. This study presents an algorithm that drastically reduces this computational complexity for a particular class of LPV systems. They show that when the input matrix is right-invertible, the rebuild phase of the QP problem can be accelerated by means of a coordinate transformation which approximates the original formulation. Then they introduce a variant of the algorithm, able to further reduce this time, at the cost of a slightly increased sub-optimality. The presented results on vehicle dynamics and electrical motor control confirm the effectiveness of the two novel methods, especially in those applications where computational load is a key indicator for success.
BACKGROUND:Recent progress in the development of clinically accurate continuous glucose monitors (CGMs), automated continuous insulin infusion pumps, and controlalgorithms for calculating insulin doses from CGM data ...
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BACKGROUND:Recent progress in the development of clinically accurate continuous glucose monitors (CGMs), automated continuous insulin infusion pumps, and controlalgorithms for calculating insulin doses from CGM data have enabled the development of prototypes of subcutaneous closed-loop systems for controlling blood glucose (BG) levels in type 1 diabetes. The use of a new personalized modelpredictivecontrol (MPC) algorithm to determine insulin doses to achieve and maintain BG levels between 70 and 140 mg/dl overnight and to control postprandial BG levels is presented.
METHODS:Eight adults with type 1 diabetes were studied twice, once using their personal open-loop systems to control BG overnight and for 4 h following a standardized meal and once using a closed-loop system that utilizes the MPC algorithm to control BG overnight and for 4 h following a standardized meal. Average BG levels, percentage of time within BG target of 70-140 mg/dl, number of hypoglycemia episodes, and postprandial BG excursions during both study periods were compared.
RESULTS:With closed-loop control, once BG levels achieved the target range (70-140 mg/dl), they remained within that range throughout the night in seven of the eight subjects. One subject developed a BG level of 65 mg/dl, which was signaled by the CGM trend analysis, and the MPC algorithm directed the discontinuance of the insulin infusion. The number of overnight hypoglycemic events was significantly reduced (p = .011) with closed-loop control. Postprandial BG excursions were similar during closed-loop and open-loop control.
CONCLUSION:modelpredictive closed-loop control of BG levels can be achieved overnight and following a standardized breakfast meal. This "artificial pancreas" controls BG levels as effectively as patient-directed open-loop control following a morning meal but is significantly superior to open-loop control in preventing overnight hypoglycemia.
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