Digital Signal Processor Board Research Articles

Development of a DAQ system for a plasma display panel-based X-ray detector (PXD)

Recently, a novel plasma display panel (PDP)-based X-ray detector (PXD) was developed. The goal of this study is to develop a data acquisition system for use with the PXD as an imaging detector. Since the prototype detector does not have any barrier ribs or a switching device in a detector pixel, a novel pixelation scheme—the line-scan method—is developed for this new detector. To implement line scanning, a multichannel high-voltage switching circuit and a multichannel charge-acquisition circuit are developed. These two circuits are controlled by an FPGA-based digital signal processing board, from which the information about the charge and position of each pixel can be sent to a PC. FPGA-based baseline compensation and switching noise rejection algorithms are used to improve the signal-to-noise ratio (SNR). The characteristic curve of the entire PXD system is acquired, and the correlation coefficients between the X-ray dose, and the signal intensity and the SNR were determined to be approximately 0.99 and 52.9, respectively.

Bioreactor profile control by a nonlinear auto regressive moving average neuro and two degree of freedom PID controllers

This paper presents the use of nonlinear auto regressive moving average (NARMA) neuro controller for temperature control and two degree of freedom PID (2DOF-PID) for pH and dissolved oxygen (DO) of a biochemical reactor in comparison with the industry standard anti-windup PID (AWU-PID) controllers. The process model of yeast fermentation described in terms of temperature, pH and dissolved oxygen has been used in this study. Nonlinear auto regressive moving average (NARMA) neuro controller used for temperature control has been trained by Levenberg–Marquardt training algorithm. The 2DOF-PID controllers used for pH and dissolved oxygen have been tuned by MATLAB's auto tune feature along with manual tuning. Random training data with input varying from 0 to 100l/h have been obtained by using NARMA graphical interface. The data samples used for training, validation and testing are 20,000, 10,000 and 10,000 respectively. Random profiles have been used for simulation. The NARMA neuro controller and the 2DOF-PID controllers have shown improvement in rise time, residual error and overshoot. The proposed controllers have been implemented on TMS320 Digital Signal Processing board using code composure studio. Arduino Mega board has been used for input/output interface.

Study of On-Line Detection of Voltage Transient Disturbance Based on DSP and Wavelet

In this paper, a set of voltage disturbance detection device based on DSP2812 was designed and a method of transient voltage disturbance detection based on DSP and Wavelet Transform was studied. The device collects electrical signal through a Hall sensor and the parallel A/D converter and regards TMS320F2812, a kind of high-performance digital signal processor (DSP), as a core data processing unit. Discrete Wavelet Transform (DWT) algorithm on DSP board was carried out to detect transient voltage disturbance. Software modules including the main program module, A/D module, interrupt module, communication module and so on was designed. The DWT algorithm on DSP board which could detect transient voltage disturbance on line was carried out based on the strong operation ability of DSP and the high effectiveness of DWT algorithm. This device can simultaneously realize power acquisition and voltage disturbance analysis in real-time. Contrast tests show that the device is of high-precision, of high-data-processing-speed and has a capability of voltage disturbance detecting in real-time.

Simulator of the SAR Echo Based on FPGA

The echo simulator has great significance to the research on synthetic aperture radar (SAR), but massive computation and longer time are needed. In order to realize SAR echo simulation fast, the field programmable gate array (FPGA) is adopted as the kernel chirp to design the digital signal processing board to be specially used in SAR echo simulation. The simulation algorithm is realized on the board by programming. The application result shows that the realization of SAR echo simulator based on FPGA can greatly accelerate the simulation speed and significantly reduce energy consumption.

Characteristic Study and Time-Domain Discrete- Wavelet-Transform Based Hybrid Detection of Series DC Arc Faults

DC arc fault introduces major safety concerns in a wide variety of components in dc networks. However, the randomness and instability of dc arc makes it difficult to be detected. In this paper, an experimental system was designed and tested at different load current, dc source voltage, and gap length to evaluate the impact of each parameter to the dc arc. Based on the experimental results, characteristics in the electrical behavior were studied and fault detection oriented analysis was conducted. A detection algorithm utilizing both time and time-frequency domain characteristics was proposed to differentiate between dc arc fault and normal condition. The detection algorithm was then realized on a digital signal processing board and tested to verify the effectiveness. Experimental results show that the proposed algorithm can detect arc fault in a timely manner and is free of nuisance trip from normal circuit operations such as load change condition.

Visible Light Communications: 170 Mb/s Using an Artificial Neural Network Equalizer in a Low Bandwidth White Light Configuration

In this paper, we experimentally demonstrate for the first time an on off keying modulated visible light communications system achieving 170 Mb/s using an artificial neural network (ANN) based equalizer. Adaptive decision feedback (DF) and linear equalizers are also implemented and the system performances are measured using both real time (TI TMS320C6713 digital signal processing board) and offline (MATLAB) implementation of the equalizers. The performance of each equalizer is analyzed in this paper using a low bandwidth (4.5 MHz) light emitting diode (LED) as the transmitter and a large bandwidth (150 MHz) PIN photodetector as the receiver. The achievable data rates using the white spectrum are 170, 90, 40 and 20 Mb/s for ANN, DF, linear and unequalized topologies, respectively. Using a blue filter to isolate the fast blue component of the LED (at the cost of the power contribution of the yellowish wavelengths) is a popular method of improving the data rate. We further demonstrate that it is possible to sustain higher data rates from the white light with ANN equalization than the blue component due to the high signal-to-noise ratio that is obtained from retaining the yellowish wavelengths. Using the blue component we could achieve data rates of 150, 130, 90 and 70 Mb/s for the same equalizers, respectively.

Development of Real-Time Adaptive Noise Canceller and Echo Canceller

In this paper, the adaptive cancellation structure is first developed based on the LMS algorithm and FIR adaptive filtering. Then the novel practical noise and echo cancellation systems are built using the proposed adaptive technique and implemented using TX320TMS67C13 DSKs, which are Texas Instruments’ Digital Signal Processing (TI DSP) boards. Although adaptive filtering is an exciting topic in which many real-life applications can be explored [1]-[6], [9], building such a real-time system is often challenging due to the use of theoretical math, advanced DSP knowledge and practical industrial hands-on experience [1],[4]-[6],[9]. Therefore, this paper indicates that it is possible to apply traditional mathematics in adaptive filtering theory to real-time practical DSP systems. With the MATLAB software tool, we can simulate and verify various adaptive filtering designs first. Then, development and implementation of different noise or echo cancellation systems with adaptive filtering techniques can be successfully performed using the floating-point digital signal processor, TX320TMS67C13 DSK. Furthermore, it can be shown that TX320TMS67C13 DSKs with their stereo channels offer more effective and flexible tools for various noise cancellation applications.

Implementation of a new fuzzy vector control of induction motor

The aim of this paper is to present a new approach to control an induction motor using type-1 fuzzy logic. The induction motor has a nonlinear model, uncertain and strongly coupled. The vector control technique, which is based on the inverse model of the induction motors, solves the coupling problem. Unfortunately, in practice this is not checked because of model uncertainties. Indeed, the presence of the uncertainties led us to use human expertise such as the fuzzy logic techniques. In order to maintain the decoupling and to overcome the problem of the sensitivity to the parametric variations, the field-oriented control is replaced by a new block control. The simulation results show that the both control schemes provide in their basic configuration, comparable performances regarding the decoupling. However, the fuzzy vector control provides the insensitivity to the parametric variations compared to the classical one. The fuzzy vector control scheme is successfully implemented in real-time using a digital signal processor board dSPACE 1104. The efficiency of this technique is verified as well as experimentally at different dynamic operating conditions such as sudden loads change, parameter variations, speed changes, etc. The fuzzy vector control is found to be a best control for application in an induction motor.

Development of adaptive perturb and observe‐fuzzy control maximum power point tracking for photovoltaic boost dc–dc converter

This study presents an adaptive perturb and observe (P&O)-fuzzy control maximum power point tracking (MPPT) for photovoltaic (PV) boost dc–dc converter. P&O is known as a very simple MPPT algorithm and used widely. Fuzzy logic is also simple to be developed and provides fast response. The proposed technique combines both of their advantages. It should improve MPPT performance especially with existing of noise. For evaluation and comparison analysis, conventional P&O and fuzzy logic control algorithms have been developed too. All the algorithms were simulated in MATLAB-Simulink, respectively, together with PV module of Kyocera KD210GH-2PU connected to PV boost dc–dc converter. For hardware implementation, the proposed adaptive P&O-fuzzy control MPPT was programmed in TMS320F28335 digital signal processing board. The other two conventional MPPT methods were also programmed for comparison purpose. Performance assessment covers overshoot, time response, maximum power ratio, oscillation and stability as described further in this study. From the results and analysis, the adaptive P&O-fuzzy control MPPT shows the best performance with fast time response, less overshoot and more stable operation. It has high maximum power ratio as compared to the other two conventional MPPT algorithms especially with existing of noise in the system at low irradiance.

Flexible test bed for the behavioural modelling of power amplifiers

Purpose – The paper aims to focus on the memory-polynomial model (MPM) as special case of Volterra series, implemented in hardware. The behavior of the MPM is fully proved through a comparison with AM-AM and AM-PM measured data. The results show that this simulation technique is able to prove the effectiveness of the MPM implementation as behavioural model for high power radiofrequency amplifiers. The system is able to compensate perturbations caused by modern communication systems. Design/methodology/approach – The implementation uses Matlab-Simulink, and its digital signal processing (DSP) builder. The first stage allows developing the model in Matlab using the DSP builder blockset through the signal compiler block. Then, the design is downloaded to the DSP board. Findings – The paper demonstrates a proper behavior of the MPM as a truncation of the Volterra series, with respect to different inputs. This is a key point, because the series truncations allow first to implement this model in real time and second to obtain a correct precision, for instance when modeling amplification of digital signals in high frequency. Originality/value – The global system approach permits to easily develop, simulate, and validate a wireless system. The efficiency of a complete connected solution based on Agilent Technologies tools, combining simulations and measurements under true operating conditions, seems to be clearly demonstrated.

Sensored Field Oriented Control of a Robust Induction Motor Drive Using a Novel Boundary Layer Fuzzy Controller

Physical sensors have a key role in implementation of real-time vector control for an induction motor (IM) drive. This paper presents a novel boundary layer fuzzy controller (NBLFC) based on the boundary layer approach for speed control of an indirect field-oriented control (IFOC) of an induction motor (IM) drive using physical sensors. The boundary layer approach leads to a trade-off between control performances and chattering elimination. For the NBLFC, a fuzzy system is used to adjust the boundary layer thickness to improve the tracking performance and eliminate the chattering problem under small uncertainties. Also, to eliminate the chattering under the possibility of large uncertainties, the integral filter is proposed inside the variable boundary layer. In addition, the stability of the system is analyzed through the Lyapunov stability theorem. The proposed NBLFC based IM drive is implemented in real-time using digital signal processor (DSP) board TI TMS320F28335. The experimental and simulation results show the effectiveness of the proposed NBLFC based IM drive at different operating conditions.

Real-Time Monitoring in Passive Optical Networks Using a Superluminescent LED With Uniform and Phase-Shifted Fiber Bragg Gratings

This paper presents a monitoring system for tree-structured passive optical access networks. The emitted light of a superluminescent LED is utilized as the monitoring source. The light signal that propagates along the fiber to the customer site is then reflected by a uniform or phase-shifted fiber Bragg grating (FBG), which is employed near the end of the customer site. The wavelength optimization concept was demonstrated, where one center wavelength or Bragg wavelength is shared by two types of monitoring FBGs. Each FBG represents the distinct location of the optical network unit (ONU) to be monitored. This technique improves the number of monitored ONUs twofold, since a single Bragg wavelength can be utilized to monitor two independent customers. The results were analyzed using a digital signal processing board that displays the reflection spectra of the FBGs. After identifying the faulty branch, an optical time domain reflectometer can be activated for fault localization. The system is capable of monitoring up to 128 customers while maintaining the bit error rate at 10−9. This real-time, centralized monitoring system demonstrates a low-power and cost efficient monitoring system with low bandwidth requirements.

A MRAS-based stator resistance and speed estimation for sensorless vector controlled IPMSM drive

In this paper, model reference adaptive system (MRAS) technique has been used for speed estimation in sensorless speed control of interior permanent magnet synchronous motor (IPMSM) with space vector pulse width modulation (SVPWM). Most of the current researches studying the MRAS technique are based on non-saliency PMSM model and ignore the difference between d- and q-axes inductances. This paper studies a novel MRAS observer, considering the saliency of PMSM. However, this sensorless speed control shows great sensitivity to stator resistance and system noise, particularly, during low-speed operation. A novel stator resistance estimator is incorporated into the sensorless drive to compensate the effects of stator resistance variation. A stability-analysis method of this novel MRAS estimator is shown. Stable and efficient estimation of rotor speed at low region will be guaranteed by simultaneous identification of IPMSM. The stability of proposed stator resistance estimator is checked through Popov's hyperstability theorem. The proposed observer is experimentally tested using a 1.1-kW motor drive; stable operation at very low speeds under different loading conditions is demonstrated. The real time implementation concept on the digital signal processor (DSP) board of the VFOC design and SVPWM inverter technique are illustrated. Results show that the proposed MRAS technique can satisfactorily estimate the position and speed of PMSM with saliency.

Sliding Mode Speed Control for Induction Motor Drives with State-Dependent Gain Method

The main obstacle of conventional sliding mode control is caused by discontinuous function of high control activity which is known as chattering phenomenon. In this research, the chattering phenomenon is significantly reduced by a newly developed algorithm. A fast sigmoid function with varying boundary layer algorithm is designed as a state-dependent to replace the discontinuous function in conventional sliding mode control. It is known that the switching gain of sliding mode control is proportional to the chattering level, and normally a large switching gain is applied to handle the uncertainties. This research proposes a state-dependent sliding mode control which is the switching gain and boundary layer is proportional to the sigmoid function of the sliding mode controller. As a result, the boundary layer and the switching gain will change depend on uncertainties of the motor drives system. The induction motor is controlled by vector control strategy, using indirect field orientation and Space Vector Pulse Width Modulation technique. Experimental result have proved that the proposed state-dependent sliding mode control able to deal with external load disturbances as well as effectively free from chattering phenomenon compared to conventional sliding mode control. The proposed algorithm and the vector control strategy are developed in digital signal processing board. The results have confirmed that the state-dependent sliding mode control is superior with regard to external load disturbances and variation in the reference speed setting when compared to conventional sliding mode control and fixed boundary layer sliding mode control.

Neuro-Dynamic Programming in Control of the Ball and Beam System

This paper presents a new approach to the control problem of the ball and beam system, with a Neuro-Dynamic Programming algorithm implemented as the main part of the control system. The controlled system is included in the group of underactuated systems, which are nonlinear dynamical objects with the number of control signals smaller than the number of degrees of freedom. This results in problems in the formulation of a stable control algorithm, that guarantees stabilization of the ball in the desired position on the beam. The type of ball and beam material has a noticeable influence on the difficulties in stabilization of the ball, because of a smaller rolling friction and big inertia of the used metallic ball in comparison to other, for example made of non-metallic materials. The main part of the proposed discrete control system is the Neuro-Dynamic Programming algorithm in a Dual-Heuristic Dynamic Programming configuration, realized in a form of two neural networks: the actor and the critic. Neuro-Dynamic Programming algorithms use the Reinforcement Learning idea for adaptation of artificial neural network weights. Additional elements of the control system are the PD controller and the supervisory term, that ensures stability of the closed system loop. The control algorithm works on-line and does not require a preliminary learning phase of the neural network weights. Performance of the control algorithm was verified using the physical system controlled by the dSpace digital signal processing board.

Modified FxLMS Algorithm for Active Noise Control and Its Real-Time Implementation

This paper presents a modified filtered-x least mean square (FxLMS) algorithm to improve the stability of active noise control (ANC) system in realistic environment. A real-time ANC system employing modified FxLMS is designed and implemented on digital signal processor (DSP) board. The ANC system is evaluated for cancelling various tonal frequency noises in the range from 100 to 500 Hz and the performance is measured in terms of sound pressure level (SPL) attenuation. Experiment results show that a quiet zone with maximum 20 dB SPL attenuation can be generated around the location of error microphone.

DSP BASED IMPLEMENTATION OF FIELD ORIENTED CONTROL OF THREE-PHASE INDUCTION MOTOR DRIVES

The objective of this paper is to presents a practical implementation of field oriented control of three-phase induction motor based on Space Vector Pulse Width Modulation technique using Digital Signal Processing (DSP) board TMS320F2812. The control algorithm for the drive application is built with Code Composer Studio version 3.1. The motor control is divided into two control loops; inner current loop and outer speed control loop using PI controller. The rotor flux quantities are estimated using computational rotor time constant, rotor angular velocity and stator current. As a feedback of field oriented control, an incremental encoder is attached at the motor shaft and a Hall effect current sensor is used to detect the sent current to the motor. The performance of the drives system is tested under different speed command and load disturbances

R&D of an LLRF control system for a 162.5 MHz radio frequency system

This paper describes a low level radio frequency control system that was developed by the Institute of Modern Physics Chinese Academy of Sciences, and will be used in Injector II of the China-ADS project. The LLRF control system consists of an RF modulated front end, fast analog-to-digital converter (ADC) modules, and a digital signal processing board based on a field programmable gate array. The system has been tested on a room temperature cavity with 12-hr, and the results illustrate that the stability of amplitude and phase achieved ±0.32% and ±0.35 degrees, respectively.

Controller design for an electric power steering system based on LQR techniques

PurposeThis paper aims to present a linear quadratic regulator (LQR) employed to improve performance of an electrical power steering (EPS) system.Design/methodology/approachGenerally, EPS is a full electric system having an electrical motor which provides the assist torque on the steering mechanism in order to reduce the workload and to enhance the steering feel of the driver during the steering process. Since the torque sensors are considerably expensive, the authors present a control strategy that eliminates the driver torque sensor by introducing a torque estimator. Three main technical areas are described in this paper. First, the principle and structure of EPS are presented including the dynamic model. Second, LQR and Kalman filter techniques are employed to derive an optimal controller for the EPS system. Finally, the simulations and hardware results are depicted.FindingsThe combined tools of Matlab/Simulink and dSPACE provide the environment for modelling the controller in software and applying it to the actual hardware via a digital signal processing board based on the DS1401 MicroAutoBox. The controller is evaluated via simulation results, dSPACE hardware results, and verified on vehicle testing data.Originality/valueThis paper presents a controller design for an EPS system based on the LQR techniques. Within the controller concept shown, elimination of the driver torque sensor offers advantages in terms of both cost and mechanical performance. Simulations and measured data prove the good functionality of the controller proposed.

Voltage Control by DQ Frame Technique of SVPWM AC- DC Converter

This article presents a simulation model of Space vector Pulse Width Modulation (SVPWM) Rectifier using MATLAB/Simulink which ability is to stabilize an output voltage of 500 Vdc from a 3 phase 300V system using a decoupling feed-forward control method by dq frame technique. The model is tested due to a variation of ± 10% of rated input voltage. From the simulation model, it can use for implementation into a real-time control system by Digital Signal Processing Board (such as DS1104). Together, it also can be designed into a real circuit easily and effectively. The experimental results show that the SVPWM Rectifier which is presented in this paper has an adequate performance which can be applied widely