Khalid Munawar

Higher-order sliding mode based lateral guidance for unmanned aerial vehicles

A nonlinear sliding mode based scheme is developed for lateral guidance of unmanned aerial vehicles. The guidance and control system is considered as an inner and outer loop design problem, the outer guidance loop generates commands for the inner control loop to follow. Control loop dynamics is considered during derivation of the guidance logic, along with saturation constraints on the guidance commands. A nonlinear sliding manifold is selected for guidance logic design, the guidance loop generates bank angle commands for the inner roll control loop to follow. The real twisting algorithm, a higher order sliding mode algorithm is used for guidance logic design. Existence of the sliding mode along with boundedness of the guidance command is proved to ensure that controls are not saturated for large track errors. The proposed logic also contains an element of anticipatory or feed-forward control, which enables tight tracking for sharply curving paths. Efficacy of the proposed method is verified by flight testing on a scaled YAK-54 unmanned aerial vehicle. Flight results demonstrate robustness and effectiveness of the proposed guidance scheme in the presence of disturbances.

An intelligent adaptive filter for fast tracking and elimination of power line interference from ECG signal

The ECG (Electrocardiogram) signal reflects the electrical activity of the heart. Since amplitude of ECG signal is of order of few mV, it is susceptible to many types of noises and amongst which the most disturbing is power line interference (PLI). Variations in frequency of PLI further complicate the problem which can be taken care by implementation of adaptive notch filter (ANF). ANF normally requires a reference input which is not possible in all cases. In this paper, we have proposed an intelligent adaptive filter which does not require a reference input. Proposed method first detects the frequency of PLI noise then adaptively tracks and eliminates PLI from ECG signal.

4D Trajectory Generation for Guidance Module of a UAV for a Gate-to-gate Flight in Presence of Turbulence

Robotic air vehicles are used increasingly in delivering goods especially for safety-of-life applications. This paper discusses a guidance module for trajectory generation of such vehicles. An offline algorithm is developed using a navigation model to produce the required trajectory in the form of time-tagged longitude, latitude and altitude. The process is an essential requirement when an operator has to program a robotic vehicle to travel on the desired course. This problem is addressed scarcely in the relevant literature. The waypoints are generated for all phases of flight and then modified to cater for the wind disturbance parameters obtained from current meteorological information. The waypoints are uploaded to the vehicles flight control system memory and reside there for the vehicle to follow. This paper also renders the generated trajectory on Google Earth® using Matlab/Simulink® to test the closed-loop performance. Furthermore, a Dryden wind model is utilized to generate a modified trajectory for turbulent conditions. An operator can make adjustments in the required initial heading angle so the vehicle lands at its destination even in turbulent weather. An empirical formula is also proposed for this purpose. Further work includes design of a control system to follow the generated waypoints.

Robust vehicle localization with GPS dropouts

Vehicle navigation systems rely on the correct positioning information and GPS is the best solution. However, in situations of GPS outage, like in tunnels and dense woods, the vehicle can lose track quickly. Modern vehicle navigation systems are mostly based on the vehicle dynamics; proprietary algorithms keep navigating for quite some time. But these solutions are expensive and add much to a vehicles cost. This paper proposes a Kalman filter based dead-reckoning algorithm that fuses GPS information with the orientation information from a cheap IMU/INS, and the vehicles speed accessed from its ECU. This low-cost system uses GPS and IMU/INS in a loosely coupled manner along with vehicles speed and keeps supplying a quite accurate position information with GPS outage for significantly long intervals. With proper tuning and initialization, the proposed scheme has a potential to keep working in a completely GPS-denied situation.

Resource-optimized bare-metal DSP implementation of UAV flight control software

A Flight Control System (FCS) of an autonomous Unmanned Aerial Vehicle (UAV) is highly time sensitive as it is required to efficiently integrate various sub-systems running at different speeds. Moreover, functional accuracy has to be maintained while sharing the memory, computing and peripheral resources. A real-time implementation of a complete FCS in a tight closed loop on a TI® DSP microcontroller (Delfino® Dual-Core F28377D) without kernel support is described. The bare-metal embedded code developed for this application achieves the required timing constraints through efficient use of flexible memory organization, timer interrupts and CPU resource sharing. The developed system has been functionally verified to autonomously control the intended UAV in the desired manner through extensive real-time Hardware-In-Loop (HIL) simulations. The current archetype can run at 50 Hz with extensive data logging, communication, navigation and control algorithms engaging only one DSP core.

Distributed Average Tracking in Multi-Agent Coordination: Extensions and Experiments

This paper addresses the distributed average tracking (DAT) problem for a group of agents to track the average of multiple time-varying reference signals, each of which is available to only one agent, under local interaction with neighbors and an undirected graph. We consider three cases: 1) DAT for single-integrator dynamics with a chain of integrators in algorithm design; 2) DAT with swarm behavior for single-integrator dynamics; and 3) DAT with swarm behavior for double-integrator dynamics. First, a continuous distributed algorithm with a chain of two integrators is proposed for single-integrator dynamics, where each agent needs its own and its neighbors’ filter outputs obtained through communication besides its absolute position, local relative positions, reference signal, and reference velocity. The introduced algorithm can deal with a wide class of reference signals with steady deviations among reference velocities. Then, two swarm-based DAT algorithms for, respectively, single- and double-integrator dynamics are presented. In the first swarm-based algorithm for single-integrator dynamics, each agent needs to measure the relative positions between itself and its neighbors, while in the second swarm-based algorithm for double-integrator dynamics, relative velocity information is required too. In both cases, the information can be obtained through local sensing. If correct initialization constraints can be achieved, the center of the agents will track the average of the reference signals and the agents will maintain connectivity and avoid interagent collision. Numerical simulations are also presented to illustrate the theoretical results. Finally, the algorithms presented in this paper are experimentally implemented and validated on a multirobot platform.

An Overview of Localization Methods for Multi-Agent Systems

Localization of mult i-agent systems is a fundamental requirement for multi-agent systems to operate and cooperate properly. The problem of localization can be divided into two categories; one in which a -priori informat ion is available and the second where the global position is to be asce rtained without a-priori informat ion. This paper gives a comprehensive survey of localization techniques that exist in the literature for both the categories with the objectives of knowing the current state-of-the-art, helping in selecting the proper approach in a given scenario and promoting research in this area. A detailed description of methods that exist in the literature are provided in considerable detail. Then these methods are compared, and their weaknesses and strengths are discussed. Finally, some future research recommendations are drawn out of this survey.