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Queen Mary University of LondonQueen Mary University of London
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Dr Ranjan Vepa
BTech(IITMadras) MASc(Wat) PhD(Stan)


Research Overview

The research is dedicated to the study of dynamics and its control of robotics and biomedical systems with applications in mobile robots, aerospace vehicles and UAVs, jet engines and energy systems. Other applications of this work are to wind turbine and compressor control, maximum power point tracking, flow control over smart flaps and the control of biodynamic systems. They can be conveniently grouped into two classes:

1) Optimal Control of Physically Uncertain Robot Systems & UAVs

The primary topics in this area are:

i) Modeling and control of space robots, mobile robots, hybrid electric vehicles/aircraft, UAVs and power trains;

ii) Design of brain & neuro-controlled prosthetic robot limbs for rehabilitation: The focus here is on integration of artificial and biological neural networks
iii) Dynamics & control of renewable and sustainable energy systems: The optimal use and regulation of alternate power sources such as fuel cells in hybrid electric/ robot vehicle power trains; modeling of solar cells, fuel cell degradation and health monitoring for automotive and robot applications, independent propulsion control and its integration with nonlinear control of vehicles in all flight/motion regimes with an emphasis on fault detection in sensors and actuators and control law reconfiguration.
iv) Design build and test plasma actuators for flow control and space applications: application to active flow control around mobile robots and spacecraft propulsion, feedback control of aerofoil section shape in subsonic and transonic flow for UAV, airship & turbo-machine applications

2) Non-linear Filtering of Dynamic Systems

The following applications of non-linear filtering are also being investigated:

i) Structural Health Monitoring: In this activity observer and Kalman filter based crack detection filters are designed and applied to crack detection and isolation in aeroelastic, aircraft and vehicle structures such as nacelles, casings, turbine rotors and rotor blades for health monitoring and control; Feedback control of crack propagation and compliance compensation in cracked vibrating structures is also investigated; Another issue is the modeling of damage in laminated composite plates and nonlinear flutter analysis.
ii) Vision based Control and Navigation: Vision based, GPS integrated, autonomous navigation and nonlinear dynamic inversion control of mobile robots, and space robots;

Research Area

  • Dynamic modeling control and simulation in engineering systems


Modeling and control of space robots, mobile robots, hybrid electric vehicles/aircraft, UAVs and power trains

The use of manipulators attached to satellites has several applications in outer space. At present, complex tasks such as debris removal need to be carried out by robotic manipulators. However the fact that the satellite's inertia properties will change as it grabs pieces of debris implies that the stability margins of the satellite are dynamically changing. The dynamic coupling between the spacecraft and the attached manipulator poses a number of dynamic, kinematic as well as manipulation and control issues. The space manipulators are designed with the idea of having a flying robotic manipulator in space which can perform tasks that are risky or unsafe for humans to do. A typical example of a CUBESAT with a manipulator arm is illustrated in fig. 1.

Fig. 1 Side-view of a typical CUBESAT with a manipulator arm

Orbiting manipulators are patently different from traditional manipulators as they continuously experience gravitational and reaction forces. Gravity gradient moments have significant influence on the equilibrium stability of the satellite with manipulator. In the fig. 2 are shown a typical Debra-Delp stability region (shaded) of a satellite in terms of the Smelt parameters ki and the corresponding configuration parameter stability diagram for a two-link manipulator.

StabilityBoundaryMonteCarlo1.tif ParameterSpaceStability01.tif

Fig. 2 Debra-Delp stability region and the corresponding configuration parameter stability diagram for two link manipulator

This project is designed to enhance the stability of a satellite carrying a robotic manipulator using active control techniques.


Design of neuro-controlled prosthetic robot limbs for rehabilitation:

The focus is of this research is on the electrical interfacing and the transference of control signals from biological neural networks to artificial neural networks. Neuro-computer interfacing and issues such as software based artificial synapses, controlling essential tremor as well as cerebellar, dystonic or Parkinsonian tremor are targeted. Upper and lower limb prosthesis, the automatic control of walking with artificial limbs and the use of biosensors and transducers in dealing with limb prostheses form the basis for the design of the control system for prosthetic limbs.

Of particular interest in this area is the artificial neural network based control of systems which are normally controlled by model predictive control based on unscented Kalman filtering of nonlinear model of prosthetic limb motions. The problem is nonlinear and it involves the design of interfaces to physiological systems. The fig. 3 illustrates a typical four degree of upper arm dynamic model of a manipulator that can be controlled by artificial neural networks and could respond to EMG command and other signals appearing at the neuro-muscular interfaces.

Fig. 3 A typical four degree dynamic model of an actively controlled prosthetic upper arm

Dynamics & control of renewable and sustainable energy systems:  (with application to hybrid power trains, fuel cell control and fault detection and isolation)
In this work a new nonlinear H∞ estimation algorithm is applied to Proton Exchange Membrane Fuel Cell (PEMFC). It is well known that the traditional H∞ estimator for a linear system consists of an optimal full state estimate estimator. In this work, the adaptive method is coupled with the unscented Kalman filter (UKF) and is used to estimate the states of polymer electrolyte membrane fuel cell.
The work is being used in the development of hybrid power trains for automotive applications and for the health monitoring of fuel cells.
See also:
In other applications such as wind turbine, the design of a nonlinear rotor side controller is developed for a wind turbine generator based on nonlinear, H2 optimal control theory. The objective is to demonstrate the synthesis of a Maximum Power Point Tracking (MPPT) algorithm.

Design build and test plasma actuators for flow control and space applications:
In this project we are seeking to build the prototype of a dielectric barrier discharge (DBD) actuator for use with the feedback control of aerofoil section shape in subsonic and transonic flow for UAV, airship & turbo-machine applications. Our primary interest is to control the boundary layer while executing the bio-mimetic morphing and aerodynamic shape control of an aerofoil section.
Structural Health Monitoring: A filter based approach
In this work the notion of a crack detection filter is introduced and algorithms for the design of such filters presented. The concept is based on the design of observers that sensitive or insensitive to the presence of a crack in a structure. It arises from an application of fault detection filters to structures with cracks and is a novel and new concept. The feasibility of designing crack detection filters for structural health monitoring applications is then demonstrated.

SEMS division: