Covid-19 mandatory self-quarantine wearable device for authority monitoring with edge ai reporting & flagging system

A mandatory self-quarantine is necessary for those who return from overseas or any red zone areas. It is important that the self-quarantine is conducted without the non-adherence issue occurring and causes the self-quarantine individual to be the carrier of the COVID-19 in the community. To navigate and resolve this issue, most countries have implemented a series of COVID-19 monitoring and tracing systems. However, there are some restrictions and limitation which can lead to intentional non-adherence. The quarantined individuals can still travel within the community by removing the wristband or simply providing an incorrect contact status in the tracing application. In this paper, a novel configuration for mandatory self-quarantine system is proposed. It will enable interaction between the wearable and contact tracing technologies to ensure that the authorities have total control of the system. The hardware of the proposed system in the wearable device is low in cost, lightweight and safe to use for the next user after the quarantine is completed. The software (software and database) that linked between the quarantine user and normal user utilizes edge artificial intelligence (AI) for reporting and flagging mechanisms

Automatic control of color sorting and pick/place of a 6- dof robot arm

This work focuses on the implementation and design of a six degree of freedom, 6-DOF control of automatic color sorting and pick and place tasks for a robot arm using wireless controlling interface – Blynk apps. The robot arm able to differentiate the colors of the object (input) and categories or classified the object to the correct places. The main target of this project is to provide a stable, efficient, and precision results without any vibration or jittering from the servo motor during controlling the robot arm. In this work, six servo motors were used to realize the real robotic arm for industrial use. Five servos were operated to control the entire robot arm motion including the base, shoulder, and elbow as well as one servo is reserved for the positioning of the end effector. Two input variables namely TSC3200 Color Sensors & HC-SR04 Ultrasonic Sensors were employed as the input for the robot arm. The output variable mainly focused on the servo motor as the links for the robot arm to reposition and change the motion for the entire system

Data-based PID control of flexible joint robot using adaptive safe experimentation dynamics algorithm

This paper proposes the data-based PID controller of flexible joint robot based on adaptive safe experimentation dynamics (ASED) algorithm. The ASED algorithm is an enhanced version of SED algorithm where the updated tuning variable is modified to adapt to the change of the objective function. By adopting the adaptive term to the updated equation of SED, it is expected that the convergence accuracy can be further improved. The effectiveness of the ASED algorithm is verified to tune the PID controller of flexible joint robot. In this flexible joint control problem, two PID controllers are utilized to control both rotary angle tracking and vibration of flexible joint robot. The performance of the proposed data-based PID controller is assessed in terms of trajectory tracking of angular motion, vibration reduction and statistical analysis of the pre-defined control objective function. The simulation results showed that the data-based PID controller based on ASED is able to produce better control accuracy than the conventional SED based method

Parametric modelling of pedal pressing activities during road traffic delay

Traffic congestion in big cities in Malaysia has become a common scenario among the communities. The journey between homes to working place twice a day at considerable distances is no longer a strange situation. Being in traffic for hours in a sitting position requires recurrent tasks of manual pressing the pedal and brake excessively and if they are done without the correct sitting posture, it may trigger fatigue faster, particularly for the leg and back of the driver. In the long term, it will negatively affect the health of the driver, particularly in the form of physical, psychological, and emotional. Therefore, this paper is trying to investigate the recurrent brake pedal pressings as well as the leg postures while driving in traffic jam. The research is started with the experimental setup and data acquisition on brake pedal pressing as well as leg posture followed by the modelling and analysis of the obtained data using particle swarm optimization (PSO) modelling technique. The validation step was then executed to verify the model derived using open-loop and closed-loop performance analysis. The results show that the pedal pressing force of leg posture can be closely represented using 2nd order transfer function and mimics the actual pedal pressing pattern during road traffic delay

Hybrid genetic manta ray foraging optimization and its application to interval type 2 fuzzy logic control of an inverted pendulum system

This paper presents an improvised version of Manta-Ray Foraging Optimization (MRFO) by using components in Genetic Algorithm (GA). MRFO is a recent proposed algorithm which based on the behaviour of manta rays. The algorithm imitates three foraging strategies of this cartilaginous fish, which are chain foraging, cyclone foraging and somersault foraging to find foods. However, this optimization algorithm can be improved in its strategy which increases its accuracy. Thus, in this proposed improvement, mutation and crossover strategy from GA were adopted into MRFO. Crossover operation is a convergence action which is purposely to pull the agents towards an optimum point. At the meanwhile, mutation operation is a divergence action which purposely to spread out the agents throughout wider feasible region. Later, the algorithms were performed on several benchmark functions and statically tested by using Wilcoxon signed-rank test to know their performances. To test the algorithm with a real application, the algorithms were applied to an interval type 2 fuzzy logic controller (IT2FLC) of an inverted pendulum system. Result of the test on benchmark functions shows that GMRFO outperformed MRFO and GA and it shows that it provides a better parameter of the control system for a better response

Hybrid bacterial foraging sine cosine algorithm for solving global optimization problems

This paper proposes a new hybrid algorithm between Bacterial Foraging Algorithm (BFA) and Sine Cosine Algorithm (SCA) called Hybrid Bacterial Foraging Sine Cosine Algorithm (HBFSCA) to solve global optimization problems. The proposed HBFSCA algorithm synergizes the strength of BFA to avoid local optima with the adaptive step-size and highly randomized movement in SCA to achieve higher accuracy compared to its original counterparts. The performances of the proposed algorithm have been investigated on a set of single-objective minimization problems consist of 30 benchmark functions, which include unimodal, multimodal, hybrid, and composite functions. The results obtained from the test functions prove that the proposed algorithm outperforms its original counterparts significantly in terms of accuracy, convergence speed, and local optima avoidance

Sit-to-Stand and Stand-to-Sit Control Mechanisms of Two-Wheeled Wheelchair

This paper presents a mechanism for standing and sitting transformation of a wheelchair using a two-wheeled inverted pendulum concept with reduced torque requirement, in simulation studies. The motivation of this work is to design a compact standing mechanism to help an elderly/disabled person with functional limitation in lower extremities to maneuver in small and confined spaces and enable them to perform standard daily life routines independently. The wheelchair system at the upright standing position is tested with different travel distances, and the challenge is to control both sit-to-stand and stand-to-sit operations in a stable manner using flexible-joint humanoid. An additional spring/damping element is incorporated at each wheel to provide a comfortable ride for the user especially during stand-to-sit transformation task. A PD-fuzzy control with modular structure is implemented, and the performance of the system is observed through visual nastran 4d (vn4d) visualization software and simulation in matlab. The stand-to-sit performance tests have shown more than 38% reduction in tilt and back seat angles fluctuation in linear travel motion using a suspension system, while the initial tilt torque needed is 50% less than the amount required in previous designs

Two-Wheeled Wheelchair Stabilization Control Using Fuzzy Logic Controller Based Particle Swarm Optimization

Designing a control strategy of two-wheeled wheelchair is a very challenging task due to the unstable and highly nonlinear system. In the paper the system is modeled by mimicking a double-link inverted pendulum concept and the mathematical equations is derived using Euler-Lagrange method. Then the state-space representation is applied to the Simulink block diagram in Matlab. The control parameter of the system is compared between trial-and-error method and Particle Swarm Optimization (PSO) algorithm. This strategy is to find the optimal value for the system to get better performance. The system will be simulated using Fuzzy Logic Control (FLC) and FLC-PSO using Matlab/Simulink environment. Simulation results show that the FLC-PSO is better than FLC in terms of overshoot and settling time

Simulation and Control of Multipurpose Wheelchair for Disabled/elderly Mobility

This paper presents investigations into the development of modelling and control strategies for a multipurpose wheelchair as mobile transporter for elderly and disabled people. The research is aimed at helping people with physical weakness/disabilities in their upper and lower extremities to move independently without human intervention. A novel reconfiguration which allows multi-task operations in the same wheelchair system with improved design is modelled in Visual Nastran 4D (VN4D) software. A modular fuzzy logic control mechanism with integrated phases is introduced for the overall operations and two-wheeled stabilization of the wheelchair. It is shown that the proposed modular fuzzy control approach is able to ensure system stability while performing multipurpose tasks such as manoeuvrability on flat surfaces, stairs climbing (ascending and descending), standing in the upright position on two wheels and transformation back to standard four wheels with up to 50% less initial torque in comparison to previous designs

A Novel Hybrid Spiral-Dynamics Bacterial-Foraging Algorithm for Global Optimization with Application to Control Design

This paper presents a hybrid optimization algorithm referred to as Hybrid spiral dynamics bacterial foraging (HSDBF). The algorithm synergizes spiral adaptive simplified bacterial foraging algorithm (BFA) and spiral dynamics inspired optimization algorithm (SDA). The standard BFA has better exploitation strategy while SDA has superior exploration approach and stable convergence when approaching the optimum value. The hybrid algorithm preserves the strengths of BFA and SDA, thus producing better results. Moreover, it has simple structure and involves less computational burden. Several unimodal and multimodal benchmark functions are employed to test the algorithm in determining the global optimum point. Furthermore, the proposed method is applied to a proportional-derivative (PD) controller optimization for a flexible manipulator system (FMS). The results show that HSDBF outperforms BFA in all test functions and successfully optimizes the PD controller