Muhammad Bilal Kadri

Prince Sultan University

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Co-Authors

Sofia Yousuf

Karachi Institute of Economics and Technology

Fahad Tanveer

Karachi Institute of Economics and Technology

Hamid Saeed Khan

Iqra University

Waqar A. Khan

Saveetha University

Syed Asad Hussain

Okanagan University College

Aqsa Raees

National University of Sciences and Technology

Sameer Qazi

Iqra University

Syed Asad Hussain

Wildlife Institute of India

A.L. Dexter

University of Oxford

Syed Muhammad Atif

Good Samaritan Hospital

Cooperative Institutions

National University of Sciences and Technology

Karachi Institute of Economics and Technology

NED University of Engineering and Technology

University of the Sciences

COMSATS University Islamabad

National University of Science and Technology

Khalifa University of Science and Technology

Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology

American Petroleum Institute

University of Engineering and Technology Lahore

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A ubiquitous architecture for wheelchair fall anomaly detection using low-cost embedded sensors and isolation forest algorithm

Computers & Electrical Engineering (2022)

Sofia Yousuf Sheikh Muhammad Bilal Kadri

Isolation

10.1016/j.compeleceng.2022.108518

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Citations (8)

Cumulative Vehicle Routing Problems

InTech eBooks (2008)

mdat Kara Bahar Yeti Muhammad Bilal Kadri

Vehicle Routing Problem

10.5772/5812

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Citations (60)

Sensor fusion of INS, odometer and GPS for robot localization

Sofia Yousuf Muhammad Bilal Kadri

This paper presents data fusion of three sensors Inertial Navigation System (INS), Global positioning systems (GPS) and odometer for determining the correct location of a differential drive mobile robot. The data from INS and odometer is combined using Kalman Filter (KF) based sensor fusion technique. The KF filtered signal and the GPS signal is fused by assigning weights. The proposed technique is tested in simulation. Mathematical models of the three sensors as well as the robot model is developed in MATLAB/Simulink environment to generate the data for simulation purpose. It has been demonstrated that with the proposed sensor fusion architecture exact geo-location of a differential drive wheeled robot can be determined to a greater degree of accuracy in an indoor or outdoor environment.

Odometer

Sensor Fusion

Differential GPS

GPS/INS

SIGNAL (programming language)

10.1109/spc.2016.7920715

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Citations (26)

A Ubiquitous Architecture for Wheelchair Fall Anomaly Detection Using Low-Cost Embedded Sensors and Isolation Forest Algorithm

SSRN Electronic Journal (2022)

sofia Yousuf Muhammad Bilal Kadri

In healthcare domain, the fall detector systems represent a viable solution for assisting the independent living for the elderly and disabled people. Also, in the past decades, the wearable sensors have gained much popularity and therefore, embedded motion sensors in the wearables have made these applications more flexible for the users. This paper presents a wheelchair fall detector system by considering falls as the anomaly in contrast to the Activities of Daily Living (ADLs). First, a heterogeneous dataset comprising of motion patterns from the publicly available SisFall dataset and the data from wheelchair prototype is constructed. The concept of sensor fusion is adopted to construct a multi-dimensional training data from the best features selected ranked by the ReliefF algorithm. An Isolated Forest (IF) based fall detection classifier, i.e., the anomaly detector is proposed trained on the available set of features to detect the fall events. Moreover, the design of the ubiquitous architecture incorporating the proposed fall detection scheme is presented. The proposed fall detection method is compared with threshold-based and other one-class anomaly detection methods for fall anomaly detection. The experimental results show that the accuracy obtained with the proposed method (i.e., the g-mean score) was achieved up-to ~96%.

Isolation

10.2139/ssrn.4178994

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Citations (0)

Disturbance rejection in information-poor systems using an adaptive model-free fuzzy controller

Muhammad Bilal Kadri A.L. Dexter

Designing controllers to reject disturbances, which cannot be accurately measured or estimated, is a challenging problem in real applications where the behaviour of the system is both non-linear and uncertain. Control schemes based on internal model control (IMC) can only be used to reject disturbances in non-linear systems if they do not affect the relationship between the controlled variable and the control signal i.e. they are additive input disturbances or output disturbances. An accurate model of the relationship between the disturbance and the controlled variable is required in feedforward control schemes. In this paper, an adaptive model-free fuzzy controller is designed to offer good control performance for non-linear uncertain plants in the face of input disturbances which affect the relationship between the controlled variable and the control signal. The controller is a T-S fuzzy model whose output parameters are updated on-line using feedback error learning. Three ways of incorporating the inaccurate measurements of the disturbance are considered :(1) The measured disturbance is one of the inputs of the fuzzy controller (2) The fuzzy controller is used in an IMC scheme, in which the measured disturbance is an input of the internal model. (3) The measured disturbance is fed into both the fuzzy controller and the internal model of the IMC scheme. A computer simulation, which is based on a modified Hammerstein model of the behaviour of the cooling coil in an air-conditioning system, is used to test the performance of each version of the control scheme. Results are presented, which show that feedforward of the disturbance provides the best control.

Feed forward

Internal model

10.1109/nafips.2009.5156409

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Citations (11)

Fuzzy based tuning of a sensor fusion based low cost attitude estimator

Fahad Tanveer Muhammad Bilal Kadri Nasir Aziz Zaid Pirwani

A fuzzy based tuning mechanism of the Kalman filter (KF), for the purpose of attitude estimation using low cost Micro-Electro-Mechanical System (MEMS) sensors is proposed. The conceived system is fitted with three axis gyroscope, accelerometer and magnetometer as the sensor suite. The filter's dynamics is based on a quaternion based attitude propagation model using rate gyros; with the other two sensors providing a complementary attitude estimate. The measurement and process covariance of the filter are tuned using a Takagi-Sugeno based fuzzy logic model based on the perceived system dynamics and filter divergence indicators. The performance of the developed system shows better attitude estimation and convergence [9]properties than a conventional KF based attitude estimation system.

Sensor Fusion

10.1109/intech.2016.7845076

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Citations (3)

Seamless Connections: Harnessing Machine Learning for MAC Optimization in Home Area Networks

Electronics (2023)

Bilal Khan Muhammad Bilal Kadri

The latest technologies and communication protocols are arousing a keen interest in automation, in which the field of home area networks is the most prominent area to work upon toward solving the issues and challenges faced by wireless home area networks regarding adaptability, reliability, cost, throughput, efficiency, and scalability. However, managing the immense number of communication devices on the premises of a smart home is a challenging task. Moreover, the Internet of Things (IoT) is an emerging global trend with billions of smart devices to be connected in the near future resulting in a huge amount of diversified data. The continuous expansion of the IoT network causes complications and vulnerabilities due to its dynamic nature and heterogeneous traffic. In the applications of IoT, the wireless sensor network (WSN) plays a major role, and to take benefits from WSN, medium access control (MAC) is the primary protocol to optimize, which helps in allocating resources to a huge number of devices in the smart home environment. Furthermore, artificial intelligence is highly demanded to enhance the efficiency of existing systems and IoT applications. Therefore, the purpose of this research paper is to achieve an optimized medium access control protocol through machine learning. The machine learning classifier, e.g., random forest (RF) and linear regression model, is adopted for predicting the features of home area networks. The proposed technique is helpful and could overcome the demerits of existing protocols in relation to scalability, throughput, access delay, and reliability and help in achieving an autonomous home area network (HAN).

Home Automation

Adaptability

10.3390/electronics12194082

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Citations (0)

Control of under-actuated two-link ROBOT with hybrid LQ-fuzzy controller

Syed Asad Hussain Muhammad Bilal Kadri

This paper presents flexible two-link ROBOT arm control methodology using fuzzy logic controller with state-estimation arrangement. In order to drive the fast and slow subsystems, a singular perturbation scheme has been established, that also reduces spillover effect. The estimation based compensator damps out the noise/ vibration of the complex nonlinear system. Setpoint tracking is achieved by employing fuzzy logic controller (slow-subsystem). The simulation results of hybrid LQ-fuzzy controller provide robustness without increasing the order of the overall system. The proposed control scheme outperforms traditional control approaches such as PD, LQR or LQG solution.

Set point

Robustness

10.1109/icreate.2014.6828361

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Citations (1)

Adaptive online fuzzy controller for a coupled tank system

Muhammad Umair Arif Danish Karim Iqbal Muhammad Bilal Kadri

In process control, precise level control of liquid in reaction vessels and storage tanks is essential. This work attempts the designing, testing, developing and controlling of a coupled tank model using an online self-tuning model free fuzzy controller. This controller is able to intelligently learn, adapt and tune it-self such that it can track the desired set point with minimal error by adapting its rule consequents using plant's qualitative information only. Simulation results on some non-linear plants and experimental results on the real non-linear coupled tank system show that the error arising at the plant output can be greatly minimized if the correct value of monotonicity is identified. Real time controlling of this non-linear system by the adaptive fuzzy controller without any prior knowledge is evidence enough of the strength of this controller.

Open-loop controller

10.1109/inmic.2014.7097362

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Citations (2)

Notice of Violation of IEEE Publication Principles: Optimal control synthesis for UAV

Syed Asad Hussain Muhammad Bilal Kadri

Notice of Violation of IEEE Publication Principles

"Optimal Control Synthesis for UAV"
by Syed Asad Hussain and Muhammad Bilal Kadri
in the 2013 Proceedings of the International Conference on Computer,Control & Communication (IC4)

After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.

This paper contains significant portions of original text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission.

"H2 and H~ Robust Autopilot Synthesis for Longitudinal Flight of a Special Unmanned Aerial Vehicle: A Comparative Study"
by F. Santoso, M. Liu, and G. Egan,
in IET Control Theory and Applications, Vol 2, No 7, 2008.

This paper present a method for the solution of the fundamental output feedback H ₂ (linear quadratic Gaussian or LQG) and H _∞ control problem (with frequency weights for performance enhancement and loop shaping) for unmanned aerial vehicle (UAV), P-15035 aircraft that has elevon control. Aim is to put together a state-space elucidation of optimal controller, under less restrictive condition of relationships. H ₂ (Linear quadratic Gaussian or LQG) and H _∞ controllers are realized to overcome uncertainties of real environment. Simulation results illustrate that robust performance is realized with reasonably good stability performance. Developments / progress through this research can the incorporated in intended autopilots.

Permission

Autopilot

10.1109/ic4.2013.6653743

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