Ranjan Vepa

Nonlinear, Optimal Control of a Wind Turbine Generator

In this paper, the design of a nonlinear rotor-side controller (RSC) 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. In the case of a doubly fed induction generator, it is essential that the RSC and the MPPT algorithm are synthesized concurrently as the nonlinear perturbation dynamics about an operating point is either only just stable or unstable in most real generators. The algorithm is validated based on using nonlinear estimation techniques and maximizing an estimate of the actual power transferred from the turbine to the generator. The MPPT algorithm is successfully demonstrated both in the case when no disturbances were present, as it is a prerequisite for successful implementation, and in cases when significant levels of wind disturbances are present.

Adaptive State Estimation of a PEM Fuel Cell

In this paper, the adaptive method is coupled with the unscented Kalman filter (UKF) and is used to estimate the states of polymer electrolyte membrane fuel cell. Our aim is to establish the superiority of the adaptive UKF over the standard UKF with no adaptation of the process noise covariance matrix. For purposes of estimation certain internal states such as the liquid water mass in the anode and cathode channel, liquid water volumes and pressures in the gas diffusion layers, and the stack temperature are assumed to have reached steady state. When this is done and fuel-cell measurements are made of the stack voltage, the relative humidity in the anode and cathode channels, the stack temperature, and the stack current, one can set up a nonlinear observer model. The model facilitates the estimation of the states and key parameters of fuel-cell stack in real time. The estimated states converge and subsequent simulations with these states incorporated into the model demonstrate good performance characteristics, such as the stack voltage and output power. By comparing the estimated stack voltage with and without adaptation it is shown that the adaptive state estimation method is superior to the case without adaptation.

Aeroelastic Analysis of Wing Structures Using Equivalent Plate Models

In this paper we formulate the Reissner-Mindlin first order shear deformation model based governing equation for a non-isotropic plate. The governing equations are cast as a set of coupled Helmholtz equations which are then expressed as integral equations where the Green’s functions are expressed in terms of the traditional Hankel functions of the first kind. The integral equations are then solved to determine the static and dynamic influence coefficients which are inverted to generate the stiffness and dynamic matrices. In order to demonstrate the application of these computations we consider the aeroelastic analysis of a wing structure, modeled as an equivalent plate. The unsteady aerodynamic generalized loads are estimated by employing the Doublet-Lattice method which is coupled with the compatible numerical evaluation of the structure’s dynamic influence coefficient matrix without any need for independent vibration analysis. We have demonstrated that by employing appropriate equivalent anisotropic plate models, and a variant of the classical Nyquist plot to assess the relative stability of the system, it is possible to capture, simulate and predict all the instability features of real aircraft wings. These models are proving to be particularly useful in the synthesis of active controllers for smart structures.

Nonlinear Unscented

In this paper, a new nonlinear q controller synthesis algorithm is applied to suspension and tracking control of a mobile vehicle. It is well known that the traditional H∞ controller for a linear system consists of a full-state estimate-based linear feedback control law and an H∞ state estimator. The feedback control law is synthesized by solving an algebraic Riccati equation, whereas the estimator is similar in form to a Kalman filter (KF). The nonlinear controller is obtained by synthesizing a “frozen” or “semifrozen” estimated state optimal control law, replacing the estimator by a nonlinear filter, and obtaining the estimates by applying the unscented transformation. The resulting controller is a nonlinear controller. The results indicate that, in the case of the closed-loop nonlinear H∞ controller, the estimator tracks the platform position to within 2% of the setpoint. When the H∞ estimator is combined with methods involving the control law synthesis based on replacing the nonlinear optimal control problem by a sequence of linear optimal control problems, a powerful computational tool may be established for synthesizing control laws for a variety of nonlinear controller synthesis applications.

H_{\infty}

In this paper an adaptive unscented Kalman filter based mixing filter is used to develop a high-precision kinematic satellite aided inertial navigation system with a modern receiver that incorporates carrier phase smoothing and ambiguity resolution. Using carrier phase measurements with multiple antennas, in addition to a set of typical pseudo-range estimates that can be obtained from a satellite navigation system such as GPS or GLONASS, the feasibility of generating high precision estimates of the typical outputs from an inertial navigation system is demonstrated. The methodology may be developed as a stand-alone system or employed in conjunction with a traditional strapped down inertial navigation system for purposes of initial alignment. Moreover the feasibility of employing adaptive mixing facilitates the possibility of using the system in an interoperable fashion with satellite navigation measurements.

Suspension and Tracking Control of Mobile Vehicles

In this study, satellite based pseudo-range measurements are integrated with accelerometer measurements made by six accelerometers located on the six faces of a cuboid, to independently measure the translational and rotational accelerations, and the pseudo-range. These measurements are then processed by an adaptive Unscented Kalman filter (UKF) to correct for the estimated errors and to obtain the required position and velocities at two independent locations. The relative position and velocity are then obtained by the application of standard vector identities. From these estimates, the position and velocity kinematics of prosthetic limbs and measurements of the joint angles, the true ambulatory position is estimated using a third independent UKF based estimator. The robotic limb joint offsets are assumed to be biased which are also estimated by the third UKF. The basic assumption is that the errors in the measurements are quite similar at the two locations and for this reason it is hypothesised that these errors would be reduced when the relative position and velocity were estimated. The results indicate that the steady-state ambulatory position error of the end-effector is reduced by more than 98%. 1. I N T R O D U C T I O N. To capture human body motion in an ambulatory situation without the need for external emitters or cameras, it is possible to use inertial sensors such as gyroscopes, ultrasonic velocity sensors, radar altimeters and accelerometers to estimate the relative position and orientation (Morris (1973), Bonato (2005), Foxlin (1996), Bachmann (2000), Molet, Boulic, and Thalmann (1999)). Magnetic sensors can enhance the accuracy of these estimates and provide stability in the horizontal plane by sensing the direction of the earth’s magnetic field (Zhu and Zhou (2004)). However in many situations involving prosthetic limbs it is not always possible to use magnetic sensors. A suitable alternative is to use satellite aided systems in much the same way as a TOM-TOM helps one to navigate on a motorway. Prosthetic limbs can be modelled as articulated rigid bodies in which the joints only have rotational degrees of freedom ; this is unlike human body joints which cannot be modelled as a pure kinematic chain with well-defined joints such as hinge-joints (Zatsiorsky (1998)). While satellite based navigation systems have been used to measure the relative attitude of a body by employing carrier phase

High-precision kinematic satellite and Doppler aided inertial navigation system

In this paper, a reinforcement learning algorithm is presented which is used to implement a fuzzy controller model for a given control problem based on the concept of ‘safety’. A concept of ‘safety’ is postulated and learned iteratively. It embodies the notion of cost as well as performance. The fuzzy controller model which is based on this notion of safety is closely related to the controllability of the system and takes the physical constraints of the controller into account.

Ambulatory Position Tracking of Prosthetic Limbs Using Multiple Satellite Aided Inertial Sensors and Adaptive Mixing

Introduction to Flight Vehicles Introduction Components of an Aeroplane Basic Principles of Flight Flying Control Surfaces: Elevator, Ailerons and Rudder Pilots Controls: The Throttle, the Control Column and Yoke, the Rudder Pedals and the Toe Brakes Modes of Flight Power Plant Avionics, Instrumentation and Systems Geometry of Aerofoils and Wings Chapter Highlights Exercises Answers to Selected Exercises References Basic Principles Governing Aerodynamic Flows Introduction Continuity Principle Bernoullis Principle Laminar Flows and Boundary Layers Turbulent Flows Aerodynamics of Aerofoils and Wings Properties of Air in the Atmosphere International Standard Atmosphere (from ESDU 77021, 1986) Generation of Lift and Drag Aerodynamic Forces and Moments Chapter Highlights Exercises Answers to Selected Exercises References Mechanics of Equilibrium Flight Introduction Speeds of Equilibrium Flight Basic Aircraft Performance Conditions for Minimum Drag Stability in the Vicinity of the Minimum Drag Speed Range and Endurance Estimation Trim Stability of Equilibrium Flight Longitudinal Static Stability Manoeuvrability Lateral Stability and Stability Criteria Experimental Determination of Aircraft Stability Margins Summary of Equilibrium- and Stability-Related Equations Chapter Highlights Exercises Answers to Selected Exercises References Aircraft Non-Linear Dynamics: Equations of Motion Introduction Aircraft Dynamics Aircraft Motion in a D Plane Moments of Inertia Eulers Equations and the Dynamics of Rigid Bodies Description of the Attitude or Orientation Aircraft Equations of Motion Motion-Induced Aerodynamic Forces and Moments Non-Linear Dynamics of Aircraft Motion and the Stability Axes Trimmed Equations of Motion Chapter Highlights Exercises References Small Perturbations and the Linearised, Decoupled Equations of Motion Introduction Small Perturbations and Linearisations Linearising the Aerodynamic Forces and Moments: Stability Derivative Concept Direct Formulation in the Stability Axis Decoupled Equations of Motion Decoupled Equations of Motion in terms of the Stability Axis Aerodynamic Derivatives Addition of Aerodynamic Controls and Throttle Non-Dimensional Longitudinal and Lateral Dynamics Simplified State-Space Equations of Longitudinal and Lateral Dynamics Simplified Concise Equations of Longitudinal and Lateral Dynamics Chapter Highlights Exercises Reference Longitudinal and Lateral Linear Stability and Control Introduction Dynamic and Static Stability Modal Description of Aircraft Dynamics and the Stability of the Modes Aircraft Lift and Drag Estimation Estimating the Longitudinal Aerodynamic Derivatives Estimating the Lateral Aerodynamic Derivatives Chapter Highlights Exercises Answers to Selected Exercises References Aircraft Dynamic Response: Numerical Simulation and Non-Linear Phenomenon Introduction Longitudinal and Lateral Modal Equations Methods of Computing Aircraft Dynamic Response System Block Diagram Representation Atmospheric Disturbance: Deterministic Disturbances Principles of Random Atmospheric Disturbance Modelling Application to Atmospheric Turbulence Modelling Aircraft Non-Linear Dynamic Response Phenomenon Chapter Highlights Exercises References Aircraft Flight Control Automatic Flight Control Systems: An Introduction Functions of a Flight Control System Integrated Flight Control System Flight Control System Design Optimal Control of Flight Dynamics Application to the Design of Stability Augmentation Systems and Autopilots Performance Assessment of a Command or Control Augmentation System Linear Perturbation Dynamics Flight Control Law Design by Partial Dynamic Inversion Design of Controllers for Multi-Input Systems Decoupling Control and Its Application: Longitudinal and Lateral Dynamics Decoupling Control Full Aircraft Six-DOF Flight Controller Design by Dynamic Inversion Chapter Highlights Exercises Answers to Selected Exercises References Piloted Simulation and Pilot Modelling Introduction Piloted Flight Simulation Principles of Human Pilot Physiological Modelling Human Physiological Control Mechanisms Spatial Awareness Chapter Highlights Exercises References Flight Dynamics of Elastic Aircraft Introduction Flight Dynamics of Flexible Aircraft Newton-Euler Equations of a Rigid Aircraft Lagrangian Formulation Vibration of Elastic Structures in a Fluid Medium Unsteady Aerodynamics of an Aerofoil Euler-Lagrange Formulation of Flexible Body Dynamics Application to an Aircraft with a Flexible Wing Vibrating in Bending and Torsion Kinetic and Potential Energies of the Whole Elastic Aircraft Euler-Lagrange Matrix Equations of a Flexible Body in Quasi-Coordinates Slender Elastic Aircraft Aircraft with a Flexible Flat Body Component Estimating the Aerodynamic Derivatives: Modified Strip Analysis Chapter Highlights Exercises Answers to Selected Exercises References Index

A Reinforcement Learning Algorithm based on Safety

Grasping of an object by robot hand is always challenging due to the uncertainties such as robot non-linearities, unstructured objects with unknown location and stiffness, unknown contact types. To address these challenges, the fundamental task is to achieve the mathematical model of the robot hand, collect information about the object and model the contact between the hand and the object. In this paper, mathematical model of a three fingered Barrett Hand is developed using the Lagrangian method. Joint and cartesian space motions are simulated on the basis of computed torque algorithm. A contact model is then developed for hand-object coupled system assuming that the object properties are well known. Contact model is also simulated under different environment stiffness. Simulation studies verify the joint and cartesian space motions along with the estimated contact force. Implementation of the control for optimizing the contact force will be presented soon.

Flight dynamics, simulation, and control : for rigid and flexible aircraft

An unsteady nonlinear and extended version of the Moore-Greitzer model is developed to facilitate the synthesis of a quasilinear stall vibration controller. The controller is synthesised in two steps. The first step defines the equilibrium point and ensures that the desired equilibrium point is stable. In the second step, the margin of stability at the equilibrium point is tuned or increased by an appropriate feedback of change in the mass flow rate about the steady mass flow rate at the compressor exit. The relatively simple and systematic non-linear modelling and linear controller synthesis approach adopted in this paper clearly highlights the main features on the controller that is capable of inhibiting compressor surge and rotating stall vibrations. Moreover, the method can be adopted for any axial compressor provided its steady-state compressor and throttle maps are known.