Non-singular terminal sliding-mode control of DC–DC buck converters

This paper presents a non-singular terminal sliding mode control (NTSMC) method for DC–DC buck converters. The NTSMC method eliminates the singularity problem which arises in the terminal sliding mode due to the fractional power and assures the finite time convergence of the output voltage error to the equilibrium point during the load changes. It is shown that the NTSMC method has the same finite time convergence as that of the terminal sliding mode control (TSMC) method. The influence of the fractional power on the state trajectory of the converter is investigated. It is observed that the slope of the sliding line becomes larger with decreasing value of the fractional power which leads to a faster transient response of the output voltage during the load changes. The theoretical considerations have been verified both by numerical simulations and experimental measurements from a laboratory prototype.     

Design of PWM with four transistor comparator for DC–DC boost converters

The DC-DC converter is used for different applications which needs higher voltages when compared to the input source. The boost converter is one of the most efficient methods to choose DC-DC Converter in different ways. The purpose of the proposed method is to reduce the area of VLSI design logic and power consumption. Boost converter topology is difficult because it has a large component. The proposed work of four transistor comparator based PWM (Pulse width Modulator) that can be used in DC-DC boost converter, which reduces the area, and power consumption of the entire system. This proposed work calculates the parameters of boost converter and the simulation performed using different duty cycle and parameters. Simulation results shows different duty cycles with different resistance and inductance parameters using boost converter. In addition to this the result carries out four transistor comparator output which is used to reduce the boost converter circuit design. PWM is based on the proposed four transistor comparator, which is used in the Cadence Virtuoso software using conventional CMOS technology.     

Design of intelligent power controller for DC–DC converters using CMAC neural network

DC–DC converters are the devices which can convert a certain electrical voltage to another level of electrical voltage. They are very popularly used because of the high efficiency and small size. This paper proposes an intelligent power controller for the DC–DC converters via cerebella model articulation controller (CMAC) neural network approach. The proposed intelligent power controller is composed of a CMAC neural controller and a robust controller. The CMAC neural controller uses a CMAC neural network to online mimic an ideal controller, and the robust controller is designed to achieve L ₂ tracking performance with desired attenuation level. Finally, a comparison among a PI control, adaptive neural control and the proposed intelligent power control is made. The experimental results are provided to demonstrate the proposed intelligent power controller can cope with the input voltage and load resistance variations to ensure the stability while providing fast transient response and simple computation.     

Robust constrained stabilization of boost DC–DC converters through bifurcation analysis

This paper proposes a new methodology for designing robust affine state-feedback control laws, so that wide-range safe and efficient operation of switched-mode DC–DC boost converters is guaranteed. Several undesirable nonlinear phenomena such as unstable attractors and subharmonic oscillations are avoided through bifurcation analysis based on the bilinear averaged model of the converter. The control design procedure also relies on constrained stabilization principles and the generation of safety domains using piecewise linear Lyapunov functions, so that robustness to supply voltage and output load variations is ensured, while input saturation is avoided and additional state constraints are also respected. The technique has been numerically and experimentally validated.     

A unified observer for robust sensorless control of DC–DC converters

Due to the large variety of converters' configurations, many different sensorless controllers are available in the literature, each one suited for a particular converter. The need for different configurations, especially on the same power supply, make it clear the advantage of having a shared control algorithm. This paper presents a unified nonlinear robust current observer for buck, boost and buck–boost converters in synchronous and asynchronous configurations. The unified observer speeds up the design, tuning and the implementation, and requires a memory cheaper code, easier to certify. Simulation and experimental results are presented to validate the approach in different scenarios.     

Output feedback controller design of Takagi–Sugeno fuzzy systems

This paper presents new systematic design methods of two types of output feedback controllers for Takagi–Sugeno (T–S) fuzzy systems, one of which is constructed with a fuzzy regulator and a fuzzy observer, while the other is an output direct feedback controller. In order to use the structural information in the rule base to decrease the conservatism of the stability analysis, the standard fuzzy partition (SFP) is employed to the premise variables of fuzzy systems. New stability conditions are obtained by relaxing the stability conditions derived in previous papers. The concept of parallel distributed compensation (PDC) is employed to design fuzzy regulators and fuzzy observers from the T–S fuzzy models. New stability analysis and design methods of output direct feedback controllers are also presented. The output feedback controllers design and simulation results for a nonlinear mass-spring-damper mechanical system show that these methods are effective.     

Robust control of mismatched buck DC–DC converters by PWM-based sliding mode control schemes

In this paper, two control methods are proposed to control mismatched dc–dc buck converters. In the first method, called Method I, a multiple surface sliding mode control is proposed to handle mismatched load uncertainty. A major problem associated with multiple surface sliding mode control viz. ‘explosion of terms’ is handled by a disturbance observer. Another method, Method II, based on simultaneous state and disturbance observer is proposed as a further improvement over Method I in terms of sensor requirement. The practical stability of the proposed schemes is proved. The performance of both the methods are assessed for regulation and tracking of output voltage under various uncertainties and is compared with a method based on extended state observer. It is shown by simulation and experimentation that the transient and steady state performance of both the controllers are satisfactory.     

Relaxed stability condition and state feedback H ∞ controller design for T-S fuzzy systems

In this paper, a fuzzy Lyapunov approach is presented for stability analysis and state feedback H _∞ controller design for T-S fuzzy systems. A new stability condition is obtained by relaxing the ones derived in previous papers. Then, a set of LMI-based sufficient conditions which can guarantee the existence of state feedback H _∞ controller for T-S fuzzy systems is proposed. In comparison with the existing literature, the proposed approach not only provides more relaxed stability conditions but also ensures better H _∞ performance. The effectiveness of the proposed approach is shown through two numerical examples. Recommended by Editor Young-Hoon Joo. Xiao-Heng Chang received the B.E. and M.S. degrees from Liaoning Technical University, China, in 1998 and 2004, respectively, and the Ph.D. degree from Northeastern University, China, in 2007. He is currently a Lecturer in the School of Information Science and Engineering, Bohai University, China. His research interests include fuzzy control and robust control as well as their applications. Guang-Hong Yang received the B.S. and M.S. degrees in Northeast University of Technology, China, in 1983 and 1986, respectively, and the Ph.D. degree in Control Engineering from Northeastern University, China (formerly, Northeast University of Technology), in 1994. He was a Lecturer/Associate Professor with Northeastern University from 1986 to 1995. He joined the Nanyang Technological University in 1996 as a Postdoctoral Fellow. From 2001 to 2005, he was a Research Scientist/Senior Research Scientist with the National University of Singapore. He is currently a Professor at the College of Information Science and Engineering, Northeastern University. His current research interests include fault-tolerant control, fault detection and isolation, nonfragile control systems design, and robust control. Dr. Yang is an Associate Editor for the International Journal of Control, Automation, and Systems (IJCAS), and an Associate Editor of the Conference Editorial Board of the IEEE Control Systems Society.     

Digital hysteresis sliding mode control for interleaved DC–DC converters

This paper presents a digital constant frequency sliding mode control (SMC) law for interleaved DC–DC converters. Constant switching frequency and interleaving are achieved by dynamically adjusting the hysteresis of the control signals generating comparators. The interleaving method neither imposes constraints on the number of required phases to obtain a specific output voltage nor uses quasi-SMC. Hence, the control scheme achieves high flexibility, robustness, and performance. Furthermore, a sliding mode observer (SMO) for reconstructing the inductor currents is proposed. Experimental results for a two-phase buck converter are reported. The control concept accomplishes an improved dynamic performance in comparison with quasi-SMC.     

Observer-based H∞ controller for 2-D T–S fuzzy model

This paper develops a method of fuzzy observer-based H_∞ controller design for two-dimensional (2-D) discrete Takagi–Sugeno (T–S) fuzzy systems. By reformulating the system, a linear matrix inequality (LMI)-based sufficient condition is derived. Then the fuzzy controller and the fuzzy observer can be independently designed, which guarantee an H_∞ noise attenuation γ of the whole system. Owing to the introduction of free matrices, the presented design method has a wider range of application and can guarantee a better H_∞ performance of the closed-loop fuzzy control system. Simulation results have demonstrated the effectiveness of the proposed method.     

Closed-loop analysis and control of a non-inverting buck–boost converter

In this article, a cascade controller is designed and analysed for a non-inverting buck–boost converter. The fast inner current loop uses sliding mode control. The slow outer voltage loop uses the proportional–integral (PI) control. Stability analysis and selection of PI gains are based on the nonlinear closed-loop error dynamics incorporating both the inner and outer loop controllers. The closed-loop system is proven to have a nonminimum phase structure. The voltage transient due to step changes of input voltage or resistance is predictable. The operating range of the reference voltage is discussed. The controller is validated by a simulation circuit. The simulation results show that the reference output voltage is well-tracked under system uncertainties or disturbances, confirming the validity of the proposed controller.     

Maximum power tracking of a generic photovoltaic system via a fuzzy controller and a two-stage DC–DC converter

This study presents a new two-stage DC–DC converter for maximum power point tracking (MPPT) and a voltage boost of a generic photovoltaic (PV) system. An intelligent MPPT of PV system based on fuzzy logic control (FLC) is presented to adaptively design the proposed fuzzy controlled MPPT controller (FC-MPPTC) while a voltage boost controller (VBC) is used to fix the output voltage to a voltage level that is higher than the required operating voltage to the back-end grid impedance. Modeling and simulation on the PV system and the DC–DC converter circuit are achieved by state-space and the software Powersim. The PV string considered has the rated power around 600?VA under varied partial shadings. The FC-MPPTC and VBC are designed and realized by a DSP module (TMS320F2812) to adjust the duty cycle in the two-stage DC–DC converter. A special FLC algorithm is forged to render an MPPT faster and more accurate than conventional MPPT technique, perturb and observe (P&O). The simulations are intended to validate the performance of the proposed FC-MPPTC. Experiments are conducted and results show that MPPT can be achieved in a fast pace and the efficiency reaches over 90?%, even up to 96?%. It is also found that the optimized tracking speed of the proposed FC-MPPTC is in fact more stable and faster than the general P&O method with the boost voltage capable of offering a stable DC output.     

State feedback control of interval type-2 Takagi–Sugeno fuzzy systems via interval type-2 regional switching fuzzy controllers

The interval type-2 Takagi–Sugeno fuzzy systems have been proposed to handle nonlinear systems subject to parameter uncertainties. In this paper, a new type of state feedback controller, namely, interval type-2 regional switching fuzzy controller, is proposed to conceive less-conservative stabilisation conditions, which is switched by basing on the values of system states. To further reduce the conservativeness in the stability analysis, the information of lower and upper membership functions is also considered. Stability conditions for the interval type-2 fuzzy closed-loop systems are presented in the form of linear matrix inequalities (LMIs). Simulation examples are provided to illustrate the effectiveness of the proposed method.     

Dynamic evolution control for synchronous buck DC–DC converter: Theory,model and simulation

This paper proposes a new control technique for synchronous buck DC–DC converter. Theory, design and implementation of the proposed control technique are provided. A new approach for converter controller synthesis based on dynamic evolution control theory is presented. In order to synthesize the converter controller, this method uses a simple analysis of nonlinear equation models of the converter. The synthesis process is simple and requires a quite low bandwidth for the controller. Therefore, this control method is suitable for digital control implementation. As an illustrative example, the synthesis of synchronous buck DC–DC converter controller is discussed in detail. The model of the synchronous buck DC–DC converter system was implemented using SimPowerSystems toolbox of MATLAB-SIMULINK. Performance of the proposed dynamic evolution control under step load change and step input voltage condition was investigated. Simulation results confirm that the proposed control method is superior to traditional PI based controller because of fast transient response and good disturbance rejection.     

Full-parameter constrained parsimonious subspace identification with steady-state information for DC–DC converters

A full-parameter constrained parsimonious subspace identification method that incorporates the steady-state a priori information of the system is proposed to model the DC–DC converters. A parsimonious model with fewer parameters is used to represent the system, and then an optimal weighted methods is used to estimate the system parameters matrices by taking into account both dynamical data and steady-state data. Compared with traditional data-driven methods for DC–DC converters, the subspace-based method can simultaneously estimate model structure and parameter with appropriate computational complexity. Moreover, compared with the traditional full-parameter constrained subspace approach, the proposed algorithm can accurately estimate the system parameters with a smaller variance. The experimental results on a DC–DC synchronous buck converter verify the effectiveness and superiority of the proposed method.     

Dempster–Shafer structure based fuzzy logic system for stochastic modeling

The Dempster–Shafer (D–S) theory of evidence is introduced to improve fuzzy inference under the complex stochastic environment. The Dempster–Shafer based fuzzy set (DFS) is first proposed, together with its union and intersection operations, to capture the principal stochastic uncertainties. Then, the fuzzy inference will be modified based on the extensional Dempster rule of combination. This new approach is able to capture the stochastic disturbance acting on fuzzy membership function, and provide a more effective inference under strong stochastic uncertainty. Finally, the numerical simulation and the experimental prediction of the wind speed are conducted to show the potential of the proposed method in stochastic modeling.