Qualification: 
M.Tech, B-Tech
mehermadhud@am.amrita.edu

Meher Madhu Dharmana currently serves as Assistant Professor (Sr.Gr.) at the Department of Electrical and Electronics Engineering at Amrita School of Engineering, Amritapuri. He has completed M. Tech. in Instrumentation and Control System.

Publications

Publication Type: Journal Article

Year of Publication Title

2018

A. R. S and Meher Madhu Dharmana, “Multi-terrain Multi-utility robot”, Procedia Computer Science, vol. 133, pp. 651-659, 2018.[Abstract]


One of the challenges facing while navigating a mobile robot over different terrains is the inability of the robot to adapt to different terrains. Most of the existing designs of the robots are designed for navigating on a specific terrain, so it is only applicable to a dedicated application. A single multi-purpose robot is cost-effective than multiple dedicated robots. To address the above mentioned problems an innovative design is proposed termed as Multi-terrain Multi-utility robot (MTMUR). This is a hybrid locomotion amphibious robot capable of moving over different terrains. It is a unique lightweight design similar to bi-copter and capable of moving on the ground and water using specially designed wheels with the help of float. This paper describes the design and analysis of air-land-water vehicle with a wall maneuvering capability. Its applications include search and rescue, mapping, surveillance and military purposes.

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2015

Meher Madhu Dharmana, Shashidhar, S., Kumar, S., and , “Embedded ANFIS as a Supervisory Controller for a 6-DOF Robotic Arm”, International Journal of Engineering Research, vol. 3, no. 5, pp. 318-320, 2015.[Abstract]


This paper implements multi-layered ANFIS controller in PIC16F886 micro-controller as a supervisory control for a 6 DOF robotic arm. The complexity in mathematical modelling demands for machine-learning techniques, which rely less on precise mathematical analysis. ANFIS is one such machine learning technique which helps in decision making for the control of robotic arms. Standard PD controllers could be used as servos to guarantee precise tracking. Based on real physical parameters of Dexter ER-1, a model is developed in Sim –Mechanics to capture the actual dynamics of robot arm. The time dependent reachable set is generated out of which it gave nearly 40,000 data samples. This data is used as inverse training data for ANFIS network and is implemented as a supervisory controller in microcontroller. The controller is tested with predefined paths and random position targets and results are shown to act satisfactorily.

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Publication Type: Conference Paper

Year of Publication Title

2017

V. Vidya, Poornachandran, P., Sujadevi, V. G., and Meher Madhu Dharmana, “Suppressing Parkinson's diseases induced involuntary movements using wearables”, in 2017 International Conference on Technological Advancements in Power and Energy ( TAP Energy), Kollam, India, 2017.[Abstract]


One of the biggest challenge faced by the subjects afflicted with Parkinson's disease (PD) is hand tremor. This prevents them from performing routine tasks such as eating, writing etc. As wearable technologies have evolved recently in terms of miniaturization, low power, low weight etc., It has universal adoption serving various purposes such as Fitness trackers, Smart watchers, personal safety devices etc. In this work, we propose and implemented a low-cost wearable assistive device for Parkinson's Disease patients. The device is developed with the aid of Coin type vibration motor and a micro controller for generating random vibration patterns by using Pulse Width Modulation. The induced vibration on the wrist distracts the patient's brain from the bio-mechanical feedback loop with the hand and reduces the hand tremor and improving the ability to grip or hold an object.

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2017

N. Shijith, Poornachandran, P., Sujadevi, V. G., and Meher Madhu Dharmana, “Spoofing technique to counterfeit the GPS receiver on a drone”, in 2017 International Conference on Technological Advancements in Power and Energy ( TAP Energy), Kollam, India, 2017.[Abstract]


As the drones are one among the fast-growing technologies, there is an increase in demand for it. There are wide range of use for the drones varying from entertainment purpose to search and rescue and many sophisticated versions are even used in war fronts. These technologies when used in public might create confusions or even destruction. In this paper we introduce a method to capture or re-route the unwanted drones entering our premises. As most of the modern drones are equipped with GPS for its co-ordinate acquisition and even for autopilot and return to home function and the signals are un-encrypted, there stand a chance for us to take over the drone with our signal, guiding it to our desired location and to land. A manipulated signal which resembles the original GPS signal must be used for this purpose. We require a machine which runs Linux and a Software Defined Radio for this purpose.

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2017

N. Shijith, Poornachandran, P., Sujadevi, V. G., and Meher Madhu Dharmana, “Breach detection and mitigation of UAVs using deep neural network”, in 2017 Recent Developments in Control, Automation Power Engineering (RDCAPE), Noida, India, 2017.[Abstract]


Unmanned Aerial Vehicles (UAV) has become ubiquitous. While there are several applications for UAV, it is also considered as a threat to the privacy and physical security. In this work we attempt to detect the invading UAV's with a goal of disabling them when they are invading a physical space. Identification of the UAV is performed by analyzing the live video feeds from cameras that are from Fixed CCTV cameras and surveillance drones. We propose to use image processing using convolutional neural network (CNN) for detecting the presence of the drones. Once the invading drone is identified, the information is sent to the Signal Jammer system. Our prototype shows very promising results that encourages us to pursue in building a real-world system.

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2017

H. Gopinath, Indu V., and Meher Madhu Dharmana, “Development of autonomous underwater inspection robot under disturbances”, in 2017 International Conference on Technological Advancements in Power and Energy ( TAP Energy), Kollam, India, 2017.[Abstract]


In the modern world, there are so many applications where Autonomous Underwater Inspection Robots are used. Applications like pipeline inspection, ship and flight wreck search, surveying seabed mosaics, etc. are few examples for that. How to utilize the control algorithm for stabilizing the underwater vehicle, so that they can perfectly execute the above applications is explained in this paper. Here a Time Delay Controller is used for the position and altitude control of an underwater inspection robot with disturbances. An Inertial Measurement Unit is used as the sensor since the controller used here needs the derivative of the system state to be known. The controller proposed here makes computations easier and it reduces the steady state error.

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2017

V. Vidya and Meher Madhu Dharmana, “Model reference based intelligent control of an active suspension system for vehicles”, in 2017 International Conference on Circuit ,Power and Computing Technologies (ICCPCT), Kollam, India, 2017.[Abstract]


An active suspension system is a kind of automotive suspension system which is used to enhance ride comfort, stability and safety while the load on the wheel and the suspension movement remain in safety limits. Several researches have been done in the past 15 decades in this field and many control methods were developed ranging from traditional controls to optimal and adaptive controllers. Robust and nonlinear control algorithms for suspension control are also notable now a days. Linear control schemes are robust and easy to implement but parameter uncertainty and nonlinear dynamics of actuator may reduce efficiency of such controllers. PID controllers are widely used control method because of its simplicity, but it lacks robustness in sudden changes in the parameters of a vehicle. Model predictive control is considered as one of the successful control scheme but due to multivariable interactions and time delay this control scheme is not effective in active suspension control. Nonlinear control schemes such as Artificial neural network controllers are more robust and efficient in Active suspension control. This paper come up with a model reference adaptive control scheme based on neural network for an Active suspension system. Modelling error is considered in this proposed control scheme to provide better adaptivity and stability for active suspension system under change in model parameters. A quarter car model with 2-DOF is selected for the analysis, which covers the vertical dynamics of vehicle. LQR is used as a benchmark controller and the performance of proposed controller is determined by carrying out computer simulations using MATLAB and SIMULINK

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2017

N. Shijith and Meher Madhu Dharmana, “Sonar based terrain estimation amp; automatic landing of swarm quadrotors”, in 2017 International Conference on Circuit ,Power and Computing Technologies (ICCPCT), Kollam, India, 2017.[Abstract]


This paper presents a method for emergency landing of a fleet of quadcopters on an unknown terrain using a sonar sensor. Quadcopters are equipped with sonar sensors for estimation of heights and the terrain is analysed. These data from the quadcopters are used for determining the landing area. Landing zone is considered in such a way that each quad is landed using lesser Energy. Multiple objective Swarm Optimisation technique (MOSO) is used for determining the landing surfaces and guiding each quad to its corresponding landing zones. Algorithms for terrain estimation, surface detection and landing are simulated for a swarm size of three.

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2017

G. Ganga and Meher Madhu Dharmana, “MPC controller for trajectory tracking control of quadcopter”, in 2017 International Conference on Circuit ,Power and Computing Technologies (ICCPCT), Kollam, India, 2017.[Abstract]


This paper focuses on trajectory tracking of quadcopter using a Model Predictive control (MPC). The main motive in using MPC is the ability to consider control and state constraints that occur in practical problems. In addition, MPC techniques consider a clear-cut performance criterion to be lessened during the control law computation. The trajectory tracking problem is solved using two approaches: PID controller and Linear MPC. The modeling of Quadcopter is developed using kinematic and dynamic equations. By making suitable assumptions, a simplified model is obtained, which is taken as the reference model for MPC. Simulation results are provided in order to show the effectiveness of both schemes. For comparison purpose only one degree of freedom, i.e., altitude is considered. The same methodology can be extended to other degrees of freedom(DOF). The results show that LMPC was able to achieve good tracking than the PID controller.

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2017

A. Alexander and Meher Madhu Dharmana, “Object detection algorithm for segregating similar coloured objects and database formation”, in 2017 International Conference on Circuit ,Power and Computing Technologies (ICCPCT), Kollam, India, 2017.[Abstract]


Recent advancement in the processing power of onboard computers has encouraged engineers to impart visual feedbacks into various systems like mechatronics and internet of things. Applications ranging from CCTV surveillance to target detection and tracking using UAVs, there is a wide variety of demand on image processing techniques in terms of computational time and quality. In this scenario, developing generalised algorithms which gives a freedom to user in choosing the trade-off between quality and quick response is a challenging task. In this paper a novel boundary detection algorithm for segregating similar coloured objects in an image is presented, which accommodates a degree of freedom in choosing resolution of object detection to the detection time. This method uses colour based segmentation as preprocessing technique to reduce overall computational complexity. It is independent of the shape (convex or non-convex) and size of the object. Algorithm is developed using Open-CV libraries and implemented for separating similar coloured vehicles from an image of different vehicles on road. Implementation results showing different choices of boundary tightness and computation times are showcased.

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2017

H. Gopinath, Indu V., and Meher Madhu Dharmana, “Autonomous underwater inspection robot under disturbances”, in 2017 International Conference on Circuit ,Power and Computing Technologies (ICCPCT), Kollam, India, 2017.[Abstract]


Autonomous underwater inspection robots are getting worldwide interest since they used for various applications like surveying seabed mosaics, shipwreck search, pipeline inspection etc. For performing the above applications, the control of position and altitude of underwater inspection robots are extremely significant as the worth of information obtained is very much reliant in the correctness of position control and tracking of the Autonomous underwater inspection robot. So a Time Delay Controller for the position and altitude control of an underwater inspection robot with disturbances is introduced. A TDC performs its best when the data acquisition rate is rapid. But for the control of underwater inspection robot, which uses a Doppler velocity log navigation system (DVL) as sensor, it can't maintain the data acquisition rate fast since DVL gives data at a poor acquisition rate, results in lessening the performance of TDC. So an integral sliding-mode controller is also provided to the typical TDC to avoid this problem and to improve the control precision even if the DVL navigation system is in operation. The controller proposed here makes computations easier and it reduces the steady state error.

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Publication Type: Journal

Year of Publication Title

2014

J. Freeman, Kiranlal, E. U., and Meher Madhu Dharmana, “ANFIS Based Control Architecture for Solar Energy Heliostats”. 2014.

Faculty Research Interest: