Microprocessor based signal processing techniques for system identification and adaptive control of DC-DC converters

PhD ThesisMany industrial and consumer devices rely on switch mode power converters (SMPCs) to provide a reliable, well regulated, DC power supply. A poorly performing power supply can potentially compromise the characteristic behaviour, efficiency, and operating range of the device. To ensure accurate regulation of the SMPC, optimal control of the power converter output is required. However, SMPC uncertainties such as component variations and load changes will affect the performance of the controller. To compensate for these time varying problems, there is increasing interest in employing real-time adaptive control techniques in SMPC applications. It is important to note that many adaptive controllers constantly tune and adjust their parameters based upon on-line system identification. In the area of system identification and adaptive control, Recursive Least Square (RLS) method provide promising results in terms of fast convergence rate, small prediction error, accurate parametric estimation, and simple adaptive structure. Despite being popular, RLS methods often have limited application in low cost systems, such as SMPCs, due to the computationally heavy calculations demanding significant hardware resources which, in turn, may require a high specification microprocessor to successfully implement. For this reason, this thesis presents research into lower complexity adaptive signal processing and filtering techniques for on-line system identification and control of SMPCs systems. The thesis presents the novel application of a Dichotomous Coordinate Descent (DCD) algorithm for the system identification of a dc-dc buck converter. Two unique applications of the DCD algorithm are proposed; system identification and self-compensation of a dc-dc SMPC. Firstly, specific attention is given to the parameter estimation of dc-dc buck SMPC. It is computationally efficient, and uses an infinite impulse response (IIR) adaptive filter as a plant model. Importantly, the proposed method is able to identify the parameters quickly and accurately; thus offering an efficient hardware solution which is well suited to real-time applications. Secondly, new alternative adaptive schemes that do not depend entirely on estimating the plant parameters is embedded with DCD algorithm. The proposed technique is based on a simple adaptive filter method and uses a one-tap finite impulse response (FIR) prediction error filter (PEF). Experimental and simulation results clearly show the DCD technique can be optimised to achieve comparable performance to classic RLS algorithms. However, it is computationally superior; thus making it an ideal candidate technique for low cost microprocessor based applications.Iraq Ministry of Higher Educatio

Real time hardware implementation of discrete sliding mode fuzzy controlled buck converter using digital signal processor

This paper deals with the real time hardware implementation of discrete sliding mode fuzzy control (DSMFC) for buck converter using digital signal processor (DSP). Applications like electric vehicle suspension control, flight dynamic control, robot position control and engine throttle position control; sliding mode control (SMC) plays a major role. Hardware realization is difficult with SMC strategy due to the continuous gain change results in chattering problem and actuator or contact may break. To resolve this problem the fuzzy logic (FL) approach has combined with the robust technique discrete sliding mode control (DSMC) to develop a new strategy for DSMFC. The mathematical modeling of the controller is done using MATLAB/Simulink software and practical design of the converter is also realized. The robustness of the controller is proved by introducing sudden change in input voltage as well as load with the help of switching circuit in hardware realization. The obtained practical results are verified by comparing with the simulation output and reference value

Discussion of the technology and research in fuel injectors common rail system

Common rail is one of the most important components in a diesel and gasoline direct injection system. It features a high-pressure (100 bar) fuel rail feeding solenoid valves, as opposed to a low-pressure fuel pump feeding unit injectors. Third-generation common rail diesels now feature piezoelectric injectors for increased precision, with fuel pressures up to 2,500 bar. The purpose of this review paper is to investigate the technology and research in fuel injectors common rail system. This review paper focuses on component of common rail injection system, pioneer of common rail injection, characteristics of common rail injection system, method to reduce smoke and NOx emission simultaneously and impact of common rail injection system. Based on our research, it can be concluded that common rail injection gives many benefit such as good for the engine performance, safe to use, and for to reduce the emission of the vehicle. Fuel injection common rail system is the modern technology that must be developed. Nowadays, our earth is polluting by vehicle output such as smoke. If the common rail system is developed, it can reduce the pollution and keep our atmosphere clean and safe

High efficiency smart voltage regulating module for green mobile computing

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In this thesis a design for a smart high efficiency voltage regulating module capable of supplying the core of modern microprocessors incorporating dynamic voltage and frequency scaling (DVS) capability is accomplished using a RISC based microcontroller to facilitate all the functions required to control, protect, and supply the core with the required variable operating voltage as set by the DVS management system. Normally voltage regulating modules provide maximum power efficiency at designed peak load, and the efficiency falls off as the load moves towards lesser values. A mathematical model has been derived for the main converter and small signal analysis has been performed in order to determine system operation stability and select a control scheme that would improve converter operation response to transients and not requiring intense computational power to realize. A Simulation model was built using Matlab/Simulink and after experimenting with tuned PID controller and fuzzy logic controllers, a simple fuzzy logic control scheme was selected to control the pulse width modulated converter and several methods were devised to reduce the requirements for computational power making the whole system operation realizable using a low power RISC based microcontroller. The same microcontroller provides circuit adaptations operation in addition to providing protection to load in terms of over voltage and over current protection. A novel circuit technique and operation control scheme enables the designed module to selectively change some of the circuit elements in the main pulse width modulated buck converter so as to improve efficiency over a wider range of loads. In case of very light loads as the case when the device goes into standby, sleep or hibernation mode, a secondary converter starts operating and the main converter stops. The secondary converter adapts a different operation scheme using switched capacitor technique which provides high efficiency at low load currents. A fuzzy logic control scheme was chosen for the main converter for its lighter computational power requirement promoting implementation using ultra low power embedded controllers. Passive and active components were carefully selected to augment operational efficiency. These aspects enabled the designed voltage regulating module to operate with efficiency improvement in off peak load region in the range of 3% to 5%. At low loads as the case when the computer system goes to standby or sleep mode, the efficiency improvent is better than 13% which will have noticeable contribution in extending battery run time thus contributing to lowering the carbon footprint of human consumption

Microprocessor based signal processing techniques for system identification and adaptive control of DC-DC converters

Many industrial and consumer devices rely on switch mode power converters (SMPCs) to provide a reliable, well regulated, DC power supply. A poorly performing power supply can potentially compromise the characteristic behaviour, efficiency, and operating range of the device. To ensure accurate regulation of the SMPC, optimal control of the power converter output is required. However, SMPC uncertainties such as component variations and load changes will affect the performance of the controller. To compensate for these time varying problems, there is increasing interest in employing real-time adaptive control techniques in SMPC applications. It is important to note that many adaptive controllers constantly tune and adjust their parameters based upon on-line system identification. In the area of system identification and adaptive control, Recursive Least Square (RLS) method provide promising results in terms of fast convergence rate, small prediction error, accurate parametric estimation, and simple adaptive structure. Despite being popular, RLS methods often have limited application in low cost systems, such as SMPCs, due to the computationally heavy calculations demanding significant hardware resources which, in turn, may require a high specification microprocessor to successfully implement. For this reason, this thesis presents research into lower complexity adaptive signal processing and filtering techniques for on-line system identification and control of SMPCs systems. The thesis presents the novel application of a Dichotomous Coordinate Descent (DCD) algorithm for the system identification of a dc-dc buck converter. Two unique applications of the DCD algorithm are proposed; system identification and self-compensation of a dc-dc SMPC. Firstly, specific attention is given to the parameter estimation of dc-dc buck SMPC. It is computationally efficient, and uses an infinite impulse response (IIR) adaptive filter as a plant model. Importantly, the proposed method is able to identify the parameters quickly and accurately; thus offering an efficient hardware solution which is well suited to real-time applications. Secondly, new alternative adaptive schemes that do not depend entirely on estimating the plant parameters is embedded with DCD algorithm. The proposed technique is based on a simple adaptive filter method and uses a one-tap finite impulse response (FIR) prediction error filter (PEF). Experimental and simulation results clearly show the DCD technique can be optimised to achieve comparable performance to classic RLS algorithms. However, it is computationally superior; thus making it an ideal candidate technique for low cost microprocessor based applications.EThOS - Electronic Theses Online ServiceIraq Ministry of Higher EducationGBUnited Kingdo

Modelling and optimisation of solar voltaic system using fuzzy logic

There is considerable increase in residential solar grid connected installations with many advantages offered by solar energy. As more solar panels are connected to grid, the Solar Inverter between solar panels and grid have to perform at optimum levels. Modern Inverters consist of DC-DC Converter and DC-AC Inverter. One problem associated with Inverter design is voltage fluctuation, this defect lies in the DC-DC converter Maximum power tracking (MPPT) algorithms responsible for extracting maximum power from the solar panels. The defect is due to large sampling number required for conventional MPPT algorithm. This thesis has proposed a new MPPT algorithm based on Mamdani Fuzzy logic. In research we use 5 parameter one diode model for solar cell modelling. The P-V/I-V characteristics curve is generated. The P-V characteristics curves sectioned and input membership and output membership functions is created. And unique fuzzy rules is used to optimize fuzzy controller output. Mamdani Fuzzy logic algorithm is compared to traditional PI controller hill climbing method. When small sampling number is used hill climbing method response is slow and good at tracking. When big sampling number is used hill climbing method response is fast and not good at tracking. The voltage also fluctuates when sampling number is big. Fuzzy logic provides a compromised solution with best response time and moderate tracking accuracy compared to hill climbing method. Fuzzy Logic based DC-DC converter together with PLL and Recursive Discrete Fourier Transform (RDFT) DC-AC inverter synchronization algorithm is employed and simulated in matlab. The MPPT simulation is conducted for a realistic 2.5KW solar panels in a 8 x 2 Matrix. In addition the MPPT algorithm is analyzed to see if it performs under power quality and voltage level tolerance of utility grid requirements. The Fuzzy Logic MPPT is excellent at tracking power. When temperature is fixed and irradiance is varied, the maximum tracking error is 5.2% in all scenarios with one exception. When irradiance is fixed and temperature varied, the maximum tracking error is 1.98%. Furthermore the Fuzzy Logic MPPT meets the power quality and voltage level tolerance requirements of utility grid for irradiance over 600 W/m2. Power quality and voltage level tolerance requirements for irradiance under 600 W/m2 is not critical as this is outside twilight conditions. Out of all the Synchronization algorithm identified in this Thesis, RDFT achieves synchronization very quickly and in addition it suppresses harmonics and noise. The possibility of future study to extend MPPT is also briefly discussed. The extension of future study is using Takagi-Sugeno fuzzy logic. Takagi-Sugeno uses more sophisticated inference and rule evaluation mathematics

System identification and adaptive current balancing ON/OFF control of DC-DC switch mode power converter

PhD ThesisReliability becomes more and more important in industrial application of Switch Mode Power Converters (SMPCs). A poorly performing power supply in a power system can influence its operation and potentially compromise the entire system performance in terms of efficiency. To maintain a high reliability, high performance SMPC effective control is necessary for regulating the output of the SMPC system. However, an uncertainty is a key factor in SMPC operation. For example, parameter variations can be caused by environmental effects such as temperature, pressure and humidity. Usually, fixed controllers cannot respond optimally and generate an effective signal to compensate the output error caused by time varying parameter changes. Therefore, the stability is potentially compromised in this case. To resolve this problem, increasing interest has been shown in employing online system identification techniques to estimate the parameter values in real time. Moreover, the control scheme applied after system identification is often called “adaptive control” due to the control signal selfadapting to the parameter variation by receiving the information from the system identification process. In system identification, the Recursive Least Square (RLS) algorithm has been widely used because it is well understood and easy to implement. However, despite the popularity of RLS, the high computational cost and slow convergence speed are the main restrictions for use in SMPC applications. For this reason, this research presents an alternative algorithm to RLS; Fast Affline Projection (FAP). Detailed mathematical analysis proves the superior computational efficiency of this algorithm. Moreover, simulation and experiment result verify this unique adaptive algorithm has improved performance in terms of computational cost and convergence speed compared with the conventional RLS methods. Finally, a novel adaptive control scheme is designed for optimal control of a DC-DC buck converter during transient periods. By applying the proposed adaptive algorithm, the control signal can be successfully employed to change the ON/OFF state of the power transistor in the DC-DC buck converter to improve the dynamic behaviour. Simulation and experiment result show the proposed adaptive control scheme significantly improves the transient response of the buck converter, particularly during an abrupt load change conditio

Design of robust controllers for telecom power supplies

A Telecom power supply is studied and analyzed from control system viewpoint. It consists of three stages: AC/DC rectifier, a backup battery, and a Telecom load. The AC/DC rectifier stage can be composed of paralleled DC/DC converters preceded by paralleled AC/DC converters. However, paralleled DC/DC converters are only considered in this thesis because they constitute the main dynamics in practice. A system of paralleled DC/DC converters operating in continuous inductor current mode with either voltage mode control or peak current mode control are modeled and analyzed using state-space representation. The H∞ control design is used in order to guarantee the robust stability and robust performance of the system in spite of different uncertainties. Also the H∞ loop-shaping design is used to design robust controllers in the presence of uncertainties. μ-analysis is used to evaluate the robustness of the system. Simulation results are presented to demonstrate the control design procedure and to compare between the two approaches presented. A Telecom power system can be composed of voltage-loop and current-loop subsystems. The multi-input-multi-output proportional-integral-derivative (PID) controller is first designed achieving robust stability and robust performance of the voltage-loop. Then, the multi-input-multi-output proportional-integral (PI) controller for current-loop is designed to achieve robust stability and robust performance of the overall system. μ-analysis is used to evaluate the robustness of PID and PI controllers. Simulation results are also presented to demonstrate and validate the control design. The required output characteristic of a Telecom power system contains three modes of operation: constant-voltage, modified constant-power, and constant-current modes. This nonlinear operation can be achieved by using the fuzzy-logic approach. A fuzzy PID-like controller is implemented to achieve the robust output voltage in spite of load disturbances. A fuzzy PI-like controller is implemented to ensure the overload protection reaching the optimal output characteristic of a Telecom power system. Also the internal-model control (IMC) method is applied to basic DC/DC converters: buck, boost, and buck-boost converters. IMC scheme is used to improve the dynamic performance of basic converters by achieving a robust output voltage against line and load disturbances. Simulations show good dynamic performance of the IMC controller.reviewe

A family of Lyapunov-based control schemes for maximum power point tracking in buck converters

summary:This paper presents a novel family of Lyapunov-based controllers for the maximum power point tracking problem in the buck converter case. The solar power generation system here considered is composed by a stand-alone photovoltaic panel connected to a DC/DC buck converter. Lyapunov function candidates depending on the output are considered to develop conditions which, in some cases, can be expressed as linear matrix inequalities; these conditions guarantee that the output goes asymptotically to zero, thus implying that the MPPT is achieved. Simulation and real-time results are presented, which validate the effectiveness of the proposals