In this study, a novel data-driven direct automatic tuning scheme is proposed for the general form of fixed-structure digital controllers of hybrid systems. The controller is directly auto-tuned while it interacts wit...
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In this study, a novel data-driven direct automatic tuning scheme is proposed for the general form of fixed-structure digital controllers of hybrid systems. The controller is directly auto-tuned while it interacts with the real plant;no modelling or plant identification procedure is involved. The auto-tuning problem is formulated as a controller parameter optimisation problem, which is solved using a quasi-Newton method. A new method for calculating the gradient of the objective function from closed-loop experiment data is proposed to reduce the sensitivity to the initial values of the parameters. Domain knowledge of controller design based on pole placement and internal model principle is introduced as a priori information to further improve the performance of the auto-tuning. Numerical simulations are conducted to demonstrate the effectiveness of the proposed scheme and performances of different objective functions are evaluated. The performance of the proposed scheme is compared with the standard relay feedback and iterative feedback tuning methods. Reliable controllers can be obtained automatically by using the proposed scheme;the only remaining task of the control engineer is to estimate the order of the plant by counting the number of independent energy storage elements.
This study exhibits the optimum design procedure to tune controllerparameters for grid-connected distributed generation system based on cuckoo search algorithm (CSA). To investigate the effectiveness of proposed algo...
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This study exhibits the optimum design procedure to tune controllerparameters for grid-connected distributed generation system based on cuckoo search algorithm (CSA). To investigate the effectiveness of proposed algorithm, a grid-tied photovoltaic (PV) system consisting of two power electronic converters controlled by five proportional integral (PI) controllers is chosen. Setting proper values for all the PI controllers is a complicated task, notably when the system is non-linear. In this study, response surface methodology (RSM) is used to develop the mathematical design of the PV system which is required to apply the optimisation algorithm. To minimise the design efforts of RSM, an alternate approach based on artificial neural network is introduced to develop the mathematical model of the PV system which is another salient feature of this research. Moreover, two modifications in the CSA are proposed to extract optimum parameters for the controllers which are found suitable in power system applications. Both the transient and dynamic performances of the system with the optimum values obtained through CSA are studied for different types of grid fault conditions using PSCAD/EMTDC. The design values are compared with values obtained through genetic algorithm and bacterial foraging optimisation. Experimental validation is also given for the proposed method.
Quasi-steady-state (QSS) large-signal models are often taken for granted in the analysis and design of DC-DC switching converters, particularly for varying operating conditions. In this study, the premise for the QSS ...
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Quasi-steady-state (QSS) large-signal models are often taken for granted in the analysis and design of DC-DC switching converters, particularly for varying operating conditions. In this study, the premise for the QSS is justified quantitatively for the first time. Based on the QSS, the DC-DC switching converter under varying operating conditions is reduced to the linear time varying systems model. Thereafter, the QSS concept is applied to analysis of frequency-domain properties of the DC-DC switching converters by using three-dimensional Bode plots, which is then utilised to the optimisation of the controllerparameters for wide variations of input voltage and load resistance. An experimental prototype of an average-current-mode-controlled boost DC-DC converter is built to verify the analysis and design by both frequency-domain and time-domain measurements.
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