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In the research, aiming at high positioning quality for LED chips under the variable system parameters, a real-time and robust visual positioning method is presented. At first, to solve the problems of delay in image system and measuring deviation in encoder, an adaptive dual rate Kalman filter technology is designed to estimate the accurate location of LED chip in real time. After sensitivity analysis, the changes of system parameters during manufacturing have a significant influence on estimation effect. Accordingly, an adaptive recursive least squares algorithm is integrated into the above estimation process to determine the system parameters timely and precisely. In the end, through experimental verification, the described method can guarantee the acceptable positioning effect and adapt to the variations of system parameters., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 ISA. Published by Elsevier Ltd. All rights reserved.)

In this paper, an improved finite-control-set model predictive control method is proposed for active front-end rectifiers where the computational effort and parameter mismatch problems are taken into account simultaneously. Specifically, a desired voltage vector which only requires one exploration is directly selected by using a single cost function, and the process of selection of the desired voltage vector is optimized by using a sector distribution method. Meanwhile, a model reference adaptive system-based online parameter identification approach is presented to alleviate the parameter mismatch problem. The advantages of the proposed method summarized as follows: First, the proposed algorithm reduces the eight possible voltage vectors to one. The exhaustive exploration can be avoided while the control performance is not deteriorated. Second, the proposed controller can mitigate performance degradation caused by the model parameter mismatch. Simulation results under various parameters operating conditions are presented to demonstrate the efficacy of the proposed method., (Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.)