Annual: 2019

📁High Performance Computing

👤Amarzish Qadeer

(Riphah International University, Faisalabad)

📅Jul 01, 2019

👤Amarzish Qadeer

(Riphah International University, Faisalabad)

📅Jul 01, 2019

👀 1500 💬 2

**EM051 » Obtaining the PRBS Repsone of System**

In our project, we will be provided with a black box and we have to determine its response by using pseudo random binary sequence method which is one of the many methods used for system identification. The input which was being generated and output which is obtained from plant are then transferred to computer for computation in MATLAB.

System identification is the science of building mathematical models of dynamic systems from observed input-output data. It can be seen as the interface between the real world of applications and the mathematical world of control theory and model abstractions. As such, it is an ubiquitous necessity for successful applications.

In this case we are considering Black-box identification – determine model structure and

estimate parameters from data.

PRBS is generated in the FPGA and applied as input to the system under test through a

comparator. Comparator gives +1V if PRBS signal is high and -1V if PRBS signal is low.

The systems responds to this signal and gives an analog output. ADC samples the output of

the system at a frequency of 249kHz. ADC used was the embedded ADC on the Spartan 3E kit. The sampled output and the corresponding input is sent in a single packet to PC via the Ethernet port.

The C# application on PC gathers all the packets and save the input and output data in different files.

**DESCRIPTION:**

In our project, we will be provided with a black box and we have to determine its response by using pseudo random binary sequence method which is one of the many methods used for system identification. The input which was being generated and output which is obtained from plant are then transferred to computer for computation in MATLAB.

System identification is the science of building mathematical models of dynamic systems from observed input-output data. It can be seen as the interface between the real world of applications and the mathematical world of control theory and model abstractions. As such, it is an ubiquitous necessity for successful applications.

In this case we are considering Black-box identification – determine model structure and

estimate parameters from data.

PRBS is generated in the FPGA and applied as input to the system under test through a

comparator. Comparator gives +1V if PRBS signal is high and -1V if PRBS signal is low.

The systems responds to this signal and gives an analog output. ADC samples the output of

the system at a frequency of 249kHz. ADC used was the embedded ADC on the Spartan 3E kit. The sampled output and the corresponding input is sent in a single packet to PC via the Ethernet port.

The C# application on PC gathers all the packets and save the input and output data in different files.

Block diagram of a general system identification experiment

**Objectives**

a)Obtainment of PRBS response of a given plant.

b)System identification algorithm.

=> Complete and standalone embedded system.

There may be similar implementations on other platforms like for effective computations of Analog Capture Circuit but they couldn't perform well due to less processing speed and their inability to simultaneously receive input and at the same time provide some necessary response after doing some processing.

In our project, we will be using fast computations of FPGA and ability to use different processing algorithms simultaneously by using virtues of PRBS.

For transmission of data we will use Ethernet on FPGA circuit.

Versatile number of FPGA inputs, connectivity with different boards like ADC ( Analog to Digital Converter ) will be used effectivity to achieve the objectives of project.

We will try to implement System identification in real time environment and in short time using FPGA .

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🕒 Jan 09, 2020 09:23 AM

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🕒 Nov 20, 2019 12:41 PM