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Artificial Neural Network based controller design for SMPS
Abstract
This paper presents a novel approach to design a controller for a half-bridge converter based Switched Mode Power Supply of 150W rating. A half-bridge converter is designed for obtaining a stiffly regulated DC output voltage of 5V irrespective of load and supply voltage variations, with an artificial neural network (ANN) based controller. The duty ratio of the controller is determined by this ANN depending on the input voltage and the output load conditions. Data collection for training the ANN was done using a PID controller-based approach in which the transfer function for the SMPS was derived by performing the large signal and small signal analyses and appropriate parameter values for the PID controller were calculated. For different load and input supply voltage conditions, the output voltage was regulated by making use of the PID controller and appropriate duty ratios were arrived at. These 150 data points were used for the training the proposed ANN with four hidden layers. The trained neural network was further utilized in arriving at the duty ratio value directly by sensing the input voltage and load current and it is found to yield stiffly regulated voltage irrespective of supply voltage and load variations where the error is within 8%.
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Analogue control of monolithic DC/DC converters is coming to a limit due to high switching frequency and a request for large regulation bandwidth. Digital control is now experimented for low-power low-voltage switch-mode power supply. Digital implementation of analogue solutions does not prove real performances. Other digital controllers have been experimented but applied to discrete converters. This paper compares a classical digital controller to a possible alternative strategy. Sensitivity functions are used to compare controller performances. RST algorithm determined by robust pole assignment shows better performances
This paper presents a new method and system for the parameter extraction and dynamic auto-tuning of low power digitally controlled dc-dc switch-mode power supplies (SMPS). During a short-lasting test phase, SMPS parameters, such as output capacitance and load, are estimated by examining the amplitude and frequency of intentionally introduced limit cycle oscillations. Then, accordingly, the digital compensator of SMPS is automatically tuned to improve the output regulation and dynamic performance. The effectiveness of the method is demonstrated on an experimental 200 kHz, 12V-to-5 V, 10 W, digitally controlled buck converter
This paper proposes a simple autotuning technique for digitally controlled dc-dc synchronous buck converters. The proposed approach is based on the relay feedback method and introduces perturbations on the output voltage during converter soft-start. By using an iterative procedure, the tuning of PID parameters is obtained directly by including the controller in the relay feedback and by adjusting the controller parameters based on the specified phase margin and control loop bandwidth. A nice property of the proposed solution is that output voltage perturbations are introduced while maintaining the closed-loop control of the digitally controlled converters. The proposed algorithm is simple, requires small tuning times and it is compliant with the cost/complexity constraint of integrated digital ICs. Experimental investigation has been performed using discrete components, implementing the digital control in a field programmable gate array (FPGA). Simulation and experimental results of a 1.5 V-5 A synchronous buck converter confirm the effectiveness of the proposed solution
A new large-signal nonlinear control technique is proposed to
control the duty-ratio d of a switch such that in each cycle the average
value of a switched variable of the switching converter is exactly equal
to or proportional to the control reference in the steady-state or in a
transient. One-cycle control rejects power source perturbations in one
switching cycle; the average value of the switched variable follows the
dynamic reference in one switching cycle; and the controller corrects
switching errors in one switching cycle. There is no steady-state error
nor dynamic error between the control reference and the average value of
the switched variable. Experiments with a constant frequency buck
converter have demonstrated the robustness of the control method and
verified the theoretical predictions. This new control method is very
general and applicable to all types of pulse-width-modulated,
resonant-based, or soft-switched switching converters for either voltage
or current control in continuous or discontinuous conduction mode.
Furthermore, it can be used to control any physical variable or abstract
signal that is in the form of a switched variable or can be converted to
the form of a switched variable
We introduce Adam, an algorithm for first-order gradient-based optimization
of stochastic objective functions. The method is straightforward to implement
and is based an adaptive estimates of lower-order moments of the gradients. The
method is computationally efficient, has little memory requirements and is well
suited for problems that are large in terms of data and/or parameters. The
method is also ap- propriate for non-stationary objectives and problems with
very noisy and/or sparse gradients. The method exhibits invariance to diagonal
rescaling of the gradients by adapting to the geometry of the objective
function. The hyper-parameters have intuitive interpretations and typically
require little tuning. Some connections to related algorithms, on which Adam
was inspired, are discussed. We also analyze the theoretical convergence
properties of the algorithm and provide a regret bound on the convergence rate
that is comparable to the best known results under the online convex
optimization framework. We demonstrate that Adam works well in practice when
experimentally compared to other stochastic optimization methods.
This paper shows an auto-tuning system for digitally controlled switch-mode power supplies (SMPS) that automatically adjusts parameters of PID compensator based on pre-specified bandwidth requirements. The PID compensator parameters are determined from intentionally introduced limit cycle oscillations (LCOs) through two consecutive auto-tuning procedures. First, the placement of poles and zeros is defined from LCOs at the corner frequency of the power stage. Then, the gain of the PID compensator is found from the oscillations occurring at the desired crossover frequency of the system. The proposed auto-tuning procedure is verified through Matlab/Simulink simulations that show fast load transient response and short settling time
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