Maximum power point tracking （MPPT） control of a photovoltaic system based on dual carrier chaotic search

The output power of the photovoltaic (PV) array changes with the change in external environment and load.Therefore,maximum power point tracking (MPPT) technology is needed to maximize the efficiency of...     

Intrinsic Power Management Strategy based improvement of power stability in a single-phase AC–DC converter system

Nowadays the size of the use of electronic devices like laptops, cell phone chargers, electric vehicles and UPS is rapidly increasing. So AC–DC converters need to incorporate the power factor correction along with voltage regulation. There are many AC–DC converter control methods available, but these methods do not perform well. Therefore In this paper, a smooth transformation on switching will be characterized by a high power factor in a single phase AC–DC converter by the use of intrinsic power management strategy. The proposed AC–DC converter's circuit topology is obtained by integrating a boost and buck converter. The Boost Converter's switching frequency does power factor correction to get less current harmonics at the input line. In this single phase AC–DC converter, the buck-boost converter is an important component that increases system power quality based on advanced PWM technique. So in this work, the Intrinsic Power Management Strategy (IPMS) is proposed to enhance the control over the DC–DC converter performance during unstable or transient operation. Rather than making a quick Pulse Width Modulation (PWM) signal, the computerized signal processor just creates a moderate changing DC signal to decide the PWM ramp function. The power factor correction model has been created and simulated by utilizing MATLAB programming. The simulation model demonstrates that the power factor is improved and the converter has regulated DC output voltage. To validate this simulation, a 1000 W prototype converter has been developed to feed a DC motor and the analysis of the results are presented.     

Design of power controller in CDMA system with power and SIR error minimization

In this paper, an uplink power control problem is considered for code division multiple access (CDMA) systems. A distributed algorithm is proposed based on linear quadratic optimal control theory. The proposed scheme minimizes the sum of the power and the error of signal-to-interference ratio (SIR). A power controller is designed by constructing an optimization problem of a stochastic linear quadratic type in Krein space and solving a Kalman filter problem.     

A type-2 fuzzy logic controller design for buck and boost DC–DC converters

Conventional (type-1) fuzzy logic controllers have been commonly used in various power converter applications. Generally, in these controllers, the experience and knowledge of human experts are needed to decide parameters associated with the rule base and membership functions. The rule base and the membership function parameters may often mean different things to different experts. This may cause rule uncertainty problems. Consequently, the performance of the controlled system, which is controlled with type-1 fuzzy logic controller, is undesirably affected. In this study, a type-2 fuzzy logic controller is proposed for the control of buck and boost DC–DC converters. To examine and analysis the effects of the proposed controller on the system performance, both converters are also controlled using the PI controller and conventional fuzzy logic controller. The settling time, the overshoot, the steady state error and the transient response of the converters under the load and input voltage changes are used as the performance criteria for the evaluation of the controller performance. Simulation results show that buck and boost converters controlled by type-2 fuzzy logic controller have better performance than the buck and boost converters controlled by type-1 fuzzy logic controller and PI controller.     

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.     

Model predictive control of a DC–DC converter for battery emulation

A battery emulator is used instead of a real traction battery to supply an electric motor inverter on a test bed for hybrid and electric powertrains under deterministic conditions. The use of virtual battery models eliminates the need for expensive battery prototypes. Virtual battery properties such as chemistry, state of charge or state of health can be changed instantly. However, the control of a battery emulator is a challenging problem. Very fast reference tracking is required for battery impedance emulation but motor inverters act as constant power loads that have a negative influence on the tracking performance and can even lead to instability. In this paper an MPC strategy is proposed for solving this problem. Scheduling of local controllers is utilized in order to handle the nonlinear and destabilizing load. Furthermore, a fast algorithm is presented that allows real-time MPC subject to input and output constraints. Experimental results obtained with a battery emulator supplying an electric drive inverter demonstrate the performance of the stabilizing controller.     

Simplifying ADRC design with error‑based framework: case study of a DC–DC buck power converter

In this work, the problem of designing a robust control algorithm for a DC-DC buck power converter is investigated. The applied solution is based on a recently proposed error-based version of the active disturbance rejection control (ADRC) scheme, in which the unknown higher-order terms of the reference signal are treated as additional components of the system “total disturbance”. The motivation here is to provide a practical following of a reference voltage trajectory for the buck converter in specifc cases where neither the analytical form of the desired signal nor its future values are known a’priori, hence cannot be directly used for control synthesis. In this work, the application of the error-based ADRC results in a practically appealing control technique, with compact structure, simplifed control rule, and intuitive tuning (inherited from the conventional output-based ADRC scheme). Theoretical, numerical, and experimental results are shown to validate the efcacy of the error-based ADRC in buck converter control, followed by a discussion about the revealed theoretical and practical limitations of this approach.     

Analysis and design of a high efficiency bidirectional DC–DC converter for battery and ultracapacitor applications

This paper presents a high efficiency non-isolated bidirectional converter which can be employed as an interface circuit between ultracapacitors or batteries and DC bus voltage. All semiconductor devices in the proposed converter are soft switched while the control circuit remains PWM. So, the energy conversion through the converter is highly efficient. The proposed converter acts as a zero-voltage transition (ZVT) buck to charge an ultracapacitor or battery and acts as a ZVT boost to discharge an ultracapacitor or battery. The performance of the proposed converter with respect to abrupt load and operating mode change is shown through computer simulation results. The results confirm the aforementioned advantages and features of the proposed converter.     

Analysis and design of single-phase power factor corrector with genetic algorithm and adaptive neuro-fuzzy-based sliding mode controller using DC–DC SEPIC

This paper proposes a methodology for single-phase power factor correction with DC–DC single-ended primary inductance converter (SEPIC) using cascade control strategy which comprises of genetic algorithm-based outer PI controller and an inner current controller which uses an adaptive neuro-fuzzy inference system-based sliding mode controller. DC–DC SEPIC is a fourth-order converter, and in order to reduce the complexity in controller design, reduced-order model of the original higher-order system is obtained by using Type-I Hankel matrix method. The performance of the proposed system is analysed using MATLAB/Simulink-based simulation studies. In order to ensure the robustness of the proposed controller, the performance parameters such as percentage total harmonic distortion, power factor, % voltage regulation, and % efficiency are analysed. From the simulation results, it is inferred that the proposed method provides efficient tracking of output voltage and effective source current shaping for load, line, and set point variations.

     

Robust digital control of a DC–DC buck converter with low frequency samplings

A robust DC?CDC converter which can covers extensive load change and also input voltage changes with one controller is needed. Then the demand to suppress output voltage change becomes still severer. We propose an approximate 2-degree-of-freedom (2DOF) digital controller which realized start-up response and dynamic load response independently. The controller makes a control bandwidth wider, and at the same time makes variations of the output voltage small at sudden changes of a load and an input voltage. In this paper, a new approximate 2DOF digital control system with additional zeros is proposed. Using the additional zeros, the second-order differential transfer characteristics between equivalent disturbances and a output voltage are realized. Therefore, the new controller makes variations of the output voltage smaller and the sudden changes of the load and the input voltage. This controller is actually implement on a DSP and is connected to the DC?CDC converter. Experimental results demonstrate that this type of digital controller can satisfy given severe specifications with low frequency sampling.     

Sensorless wind energy conversion system maximum power point tracking using Takagi–Sugeno fuzzy cerebellar model articulation control

In this paper, we propose a sensorless wind energy conversion system (WECS) maximum wind power point tracking using Takagi–Sugeno fuzzy cerebellar model articulation control (T-S CMAC). The main objective of the WECS is to achieve maximum power transfer under various wind speeds without actual measurement of the wind velocity. We first represent the WECS, which uses a permanent magnet synchronous generator (PMSG), as a nonlinear dynamical model. To carry out the T-S CMAC design, we rewrite the WECS model as a T-S fuzzy representation. The T-S CMAC design is inspired by the architectural similarity of the T-S fuzzy control and CMAC where accordingly the PDC design control gains and weighting parameter are augmented into a single vector. The advantages of this approach are 3-fold: (i) increases accuracy of CMAC initial weights – we assign the initial weights of CMAC using the control gains solved by the LMIs from the PDC design; (ii) introduces adaptive ability in LMI-based design – the CMAC design allows time-varying parameters in the system; and (iii) relaxes assumption on system uncertainty – we drop the assumption that a strict upper bound on system uncertainty is known. Numerical simulations under various wind speeds show exponential convergence results which further verify the theoretical derivations.     

Design methodology and fabrication process of a microinductor for the next generation of DC–DC power converters

Magnetic materials used in cored microinductors to supersede ferrite in the 0.5-10 MHz frequency range are investigated in this article. The performance of electrodeposited nickel–iron, cobalt–iron–copper alloys and the commercial alloy Vitrovac 6025 have been assessed through their inclusion within a custom-made solenoid microinductor. Although the present inductor achieves 77% power efficiency at 500 KHz for 24.7 W/cm3 power density, an optimized process predicts a power efficiency of 97% for 30.83 W/cm3 power density. The main issues regarding microinductor design and performance are discussed.     

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.     

Structure and stability analysis of a Takagi–Sugeno fuzzy PI controller with application to tissue hyperthermia therapy

 In this paper, we first reveal the analytical structure of a simple Takagi–Sugeno (TS) fuzzy PI controller relative to the linear PI controller. The fuzzy controller consists of two linear input fuzzy sets, four TS fuzzy rules with linear consequent, Zadeh fuzzy logic AND and the centroid defuzzifier. We prove that the fuzzy controller is actually a nonlinear PI controller with the gains changing with process output. Utilizing the well-known small Gain Theorem in control theory, we then derive sufficient conditions for global stability of the fuzzy control systems involving the TS fuzzy PI controller. Finally, as an application demonstration, we apply the fuzzy PI controller to control issue temperature, in computer simulation, during hyperthermia therapy. The relationship between heat energy and tissue temperature is represented by a linear time-varying model with a time delay. The sufficient conditions for global stability are used to design a stable fuzzy control system. Our simulation results show that the fuzzy PI control system achieves satisfactory temperature control performance. The control system is robust and stable even when the model parameters are changed suddenly and significantly.     

Posture control of robot manipulators with fuzzy voice commands using a fuzzy coach–player system

This paper presents a method of controlling robot manipulators with fuzzy voice commands. Recently, there has been some research on controlling robots using information-rich fuzzy voice commands such as 'go little slowly' and learning from such commands. However, the scope of all those works was limited to basic fuzzy voice motion commands. In this paper, we introduce a method of controlling the posture of a manipulator using complex fuzzy voice commands. A complex fuzzy voice command is composed of a set of fuzzy voice joint commands. Complex fuzzy voice commands can be used for complicated maneuvering of a manipulator, while fuzzy voice joint commands affect only a single joint. Once joint commands are learned, any complex command can be learned as a combination of some or all of them, so that, using the learned complex commands, a human user can control the manipulator in a complicated manner with natural language commands. Learning of complex commands is discussed in the framework of fuzzy coach–player model. The proposed idea is demonstrated with a PA-10 redundant manipulator.     

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.     

Teaching–learning based optimization algorithm based fuzzy-PID controller for automatic generation control of multi-area power system

This paper deals with the design of a novel fuzzy proportional–integral–derivative (PID) controller for automatic generation control (AGC) of a two unequal area interconnected thermal system. For the first time teaching–learning based optimization (TLBO) algorithm is applied in this area to obtain the parameters of the proposed fuzzy-PID controller. The design problem is formulated as an optimization problem and TLBO is employed to optimize the parameters of the fuzzy-PID controller. The superiority of proposed approach is demonstrated by comparing the results with some of the recently published approaches such as Lozi map based chaotic optimization algorithm (LCOA), genetic algorithm (GA), pattern search (PS) and simulated algorithm (SA) based PID controller for the same system under study employing the same objective function. It is observed that TLBO optimized fuzzy-PID controller gives better dynamic performance in terms of settling time, overshoot and undershoot in frequency and tie-line power deviation as compared to LCOA, GA, PS and SA based PID controllers. Further, robustness of the system is studied by varying all the system parameters from −50% to +50% in step of 25%. Analysis also reveals that TLBO optimized fuzzy-PID controller gains are quite robust and need not be reset for wide variation in system parameters.     

Modelling and experimental verification of the effect of parasitic elements on the performance of an active-clamped current-fed DC–DC converter

Current-fed DC–DC converter has received a lot of attention recently for the fuel cell power source applications. This is due to its attractive features, such as low input current ripple, high voltage conversion ratio and high efficiency. Unfortunately, a high voltage stress across the switches and hard switching is the main drawback of the current-fed topologies. Therefore, an active clamp circuit is often implemented to suppress any voltage overshoot across the switches and achieving zero-voltage switching. In this paper, based on detailed analysis on the converter performance it was found that parasitic elements of the converter can have a large impact on promising features of current-fed converters with an active clamp. This has not been reported in the literature. It has been shown through an in-depth analysis on the converter that particularly during the switch overlap period the parasitic elements create undesirable oscillations leading to additional circulating energy that adds to the conduction losses of the converter. It also results in voltage ringing across the clamp switch, oscillations in the current through the clamp circuit and high voltages across the bridge switches, even when the switches are conducting. Based on this finding a number of modifications have been proposed and these have been verified by thorough simulation and experiment.