Abstract
A Mixed Logic Dynamic (MLD) model and control method based on mode selection are proposed for the Buck convertor. In establishing the hybrid system model, the factors such as the inductor current are neglected, and the Model Predictive Control (MPC) is used to switch the most favorable working state of the control target. Since the modeling process ignores the inductance and current, it is necessary to convert the optimization prediction control resulting to avoid the problem that the model is inconsistent with the control object. The method proposed in this paper uses fewer auxiliary logic variables and mixed logic variables in the modeling process, simplifying the model and improving the solution speed. This method can not only make the Buck converter work in the Continuous Current Mode (CCM) but also work in the Discontinuous Current Mode (DCM), extending the adjustment range of the Buck converter. The simulation results show that the proposed method has a better control performance than the traditional MLD model.
Highlights
DC-DC converters have been greatly used in daily life. e traditional DC-DC converter modeling methods mostly use the average and approximate ones to obtain the linear model of the converter, such as the state-space small signal averaged model. e linear models and theories are used to design the pulse width modulation- (PMW-) based controllers, whether the controller is Model Predictive Control (MPC), neural networks, fuzzy control, or others [1,2,3,4]
E hybrid modeling of the converter is accurate in the sense of no approximation or linearization used; its performance does not depend on the working point
Aiming at the modeling control problem by the Buck converter, this paper proposes a mode selected Mixed Logic Dynamic (MLD) (MSMLD) modeling and control method. e control of the object system is realized through the establishment of the MLD model, the predictive control, and the transformation of predictive control results under constraints
Summary
DC-DC converters have been greatly used in daily life. e traditional DC-DC converter modeling methods mostly use the average and approximate ones to obtain the linear model of the converter, such as the state-space small signal averaged model. e linear models and theories are used to design the pulse width modulation- (PMW-) based controllers, whether the controller is MPC, neural networks, fuzzy control, or others [1,2,3,4]. Ren et al proposed a simplified MLD modeling method in which he uses fewer logic variables to reduce the solution time and uses the PI compensator to adjust the current reference value in the outer loop to reduce the steady-state error of the output voltage [5]. This method limits the operating range of the DC-DC converter due to the constraints of the model when the converter is controlled, so that the system cannot switch from the CCM mode to the DCM mode. E equation to state for each state can be written as x_(t) Anx(t) + Bn, n 1, 2, 3,
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