Implementation of an extended prediction self-adaptive controller using LabVIEW (TM)

The implementation of the Extended Prediction Self-Adaptive Controller is presented in this paper. It employs LabVIEWTM graphical programming of industrial equipment and it is suitable for controlling fast processes. Three different systems are used for implementing the control algorithm. The research regarding the controller design using graphical programming demonstrates that a single advanced control application can run on Windows, real time operating systems and FPGA targets without requiring significant program modifications. The most appropriate device may be selected according to the required processing time of the control signal and of the application. A relevant case study is used to exemplify the procedure

A Portable Implementation on Industrial Devices of a Predictive Controller Using Graphical Programming

This paper presents an approach for developing an Extended Prediction Self-Adaptive Controller employing graphical programming of industrial standard devices, for controlling fast processes. For comparison purposes, the algorithm has been implemented on three different FPGA (Field Programmable Gate Arrays) chips. The paper presents research aspects regarding graphical programming controller design, showing that a single advanced control application can run on different targets without requiring significant program modifications. Based on the time needed for processing the control signal and on the application, one can efficiently and easily select the most appropriate device. To exemplify the procedure, a conclusive case study is presented

Systematic design of the lead-lag network method for active damping in LCL-filter based three phase converters

Three-phase active rectifiers guarantee sinusoidal input currents and unity power factor at the price of a high switching frequency ripple. To adopt an LCL-filter, instead of an $L$-filter, allows using reduced values for the inductances and so preserving dynamics. However, stability problems can arise in the current control loop if the present resonance is not properly damped. Passive damping simply adds resistors in series with the LCL-filter capacitors. This simplicity is at the expense of increased losses and encumbrances. Active damping modifies the control algorithm to attain stability without using dissipative elements but, sometimes, needing additional sensors. This solution has been addressed in many publications. The lead-lag network method is one of the first reported procedures and continues being in use. However, neither there is a direct tuning procedure (without trial and error) nor its rationale has been explained. Thus, in this paper a straightforward procedure is developed to tune the lead-lag network with the help of software tools. The rationale of this procedure, based on the capacitor current feedback, is elucidated. Stability is studied by means of the root locus analysis in $z$-plane. Selecting the lead-lag network for the maximum damping in the closed-loop poles uses a simple optimization algorithm. The robustness against the grid inductance variation is also analyzed. Simulations and experiments confirm the validity of the proposed design flow

Identification and modelling of two phase dc-dc boost converter based on autoregressive moving average with exogenous, output-error and transfer function model structures

This research presents the identification and modelling of a two-phase DC-DC boost converter based on the autoregressive moving average with exogenous (ARMAX), output-error (OE) and transfer function (TF) model structures for low-voltage applications. The goals that led to this study were to reduce the time taken to design the controller and analyse the output of constant Kp and Ki generated from the auto tuning method. A two-phase boost converter employs as 180-degree phase shift from each phase to drive the power switch. This research focused more on the system identification approach to generate mathematical models from the open-loop response. The generated models were from the TF, ARMAX and OE model structures. The mathematical models were generated from the pulse-width modulation (PWM) input and voltage output of the two-phase boost converter itself in the time domain data. After the best model order was found to replace the two�phase boost converter with a mathematical model, the controller design took place. Some closed-loop blocks were designed for the mathematical models in MATLAB/Simulink software, which were also used to perform the auto-tuning of the proportional-integral (PI) controller. However, tuning methods such as the Ziegler-Nichols and the Cohen-Coon methods are more time-consuming. After the best values for constants Kp and Ki were determined, the values were used in the real hardware to analyse the output responses. The findings showed that Kp and Ki from the TF model showed 19% overshoot compared with those of the ARMAX and OE models, which were 25.36% and 24.6%, respectively. All of the output responses from the different Kp and Ki values resulted in less than 5% ripple voltage. It can be concluded that the best model from the system identification approach was the TF system model, since it had the lowest overshoot and the lowest percentage of output voltage rippl

FPGA v/s DSP Performance Comparison for a VSC-Based STATCOM Control Application

Munoz, JA (Munoz, Javier A.); Baier, CR (Baier, Carlos R.). Univ Talca, Dept Ind Technol, Talca 747C, ChileDigital signal processors (DSPs) and field-programmable gate arrays (FPGAs) are predominant in the implementation of digital controllers and/or modulators for power converter applications. This paper presents a systematic comparison between these two technologies, depicting the main advantages and drawbacks of each one. Key programming and implementation aspects are addressed in order to give an overall idea of their most important features and allow the comparison between DSP and FPGA devices. A classical linear control strategy for a well-known voltage-source-converter (VSC)-based topology used as Static Compensator (STATCOM) is considered as a driving example to evaluate the performance of both approaches. A proof-of-concept laboratory prototype is separately controlled with the TMS320F2812 DSP and the Spartan-3 XCS1000 FPGA to illustrate the characteristics of both technologies. In the case of the DSP, a virtual floating-point library is used to accelerate the control routines compared to double precision arithmetic. On the other hand, two approaches are developed for the FPGA implementation, the first one reduces the hardware utilization and the second one reduces the computation time. Even though both boards can successfully control the STATCOM, results show that the FPGA achieves the best computation time thanks to the high degree of parallelism available on the device

Random Finite Sets Based Very Short-Term Solar Power Forecasting Through Cloud Tracking

Tracking clouds with a sky camera within a very short horizon below thirty seconds can be a solution to mitigate the effects of sunlight disruptions. A Probability Hypothesis Density (PHD) filter and a Cardinalised Probability Hypothesis Density (CPHD) filter were used on a set of pre-processed sky images. Both filters have been compared with the state-of-the-art methods for performance. It was found that both filters are suitable to perform very-short term irradiance forecasting