Performance Analysis of IOT based Flood Monitoring Framework in Sub-urban

Flooding is the most common natural catastrophe worldwide that occurred without warning which caused great destruction. The government has spent millions of monies on flood mitigation plans. Several systems had been proposed which some of them have been employed around the country. However, it is limited to selected areas due to high installation and maintenance costs. This paper investigates two potential real-time flood monitoring frameworks in the sub-urban area, which are simpler, inexpensive, and require minimum maintenance. The proposed flood monitoring system utilized wireless data transmission system that is either GSM SIM900A module or XBee Pro module. The data was sent to NodeREd for monitoring purposes. From the result, XBee Pro can send more, and faster data as compared to GSM module. The time delay is very much lower for XBee Pro whereby the difference of realtime data captured as compared to the setup time interval that had been set in the system. In terms of consistency and sensitivity, both systems have equal efficacy. In Summary, both systems are adequate to offer monitoring and immediate warning in real-time. However, XBee pro is preferable if the area has internet access. Meanwhile, if the internet service is limited, GSM module can be a good alternative since it does not need Internet access

Utilizing P-Type ILA in tuning Hybrid PID Controller for Double Link Flexible Robotic Manipulator

The usage of robotic manipulator with multi-link structure has a great influence in most of the current industries. However, controlling the motion of multi-link manipulator has become a challenging task especially when the flexible structure is used. Currently, the system utilizes the complex mathematics to solve desired hub angle with the coupling effect and vibration in the system. Thus, this research aims to develop the controller for double-link flexible robotics manipulator (DLFRM) with the improvement on hub angle position and vibration suppression. The research utilized DLFRM modeling based on NARX model structure estimated by neural network. In the controllers’ development, this research focuses on adaptive controller. PType iterative learning algorithm (ILA) control scheme is implemented to adapt the controller parameters to meet the desired performances when there are changes to the system. The hybrid PID-PID controller is developed for hub motion and end point vibration suppression of each link respectively. The controllers are tested in MATLAB/Simulink simulation environment. The performance of the controller is compared with the fixed hybrid PID-PID controller in term of input tracking and vibration suppression. The results indicate that the proposed controller is effective to move the double-link flexible robotic manipulator to the desired position with suppression of the vibration at the end of the double-link flexible robotic manipulator structure

Implementation of PID based controller tuned by Evolutionary Algorithm for Double Link Flexible Robotic Manipulator

The paper investigates the development of intelligent hybrid collocated and non-collocated PID controller for hub motion and end point vibration suppression of doublelink flexible robotic manipulator. The system was modeled using multi-layer perceptron neural network structure based on Nonlinear Autoregressive Exogenous (NARX) model. The hybrid controllers are incorporated with optimization algorithm that is ABC and PSO to find out the parameters of the PID controllers. Numerical simulation was carried out in MATLAB/Simulink to evaluate the system in term of tracking capability and vibration suppression for both links. Performance of the controllers are compared with the hybrid PID-PID Ziegler Nichols (ZN) controller in term of input tracking and vibration suppression. The results show that PSO revealed the superiority over ABC in controlling the system. The system managed to reach desired angle for both hub at lower overshoot using proposed method. Meanwhile, the vibration reduction shows great improvement for both link 1 and 2. This signifies that, the PSO algorithm is very effective in optimizing the PID parameters

Decentralized Intelligent PID based controller tuned by Evolutionary Algorithm for Double Link Flexible Robotic Manipulator with Experimental Validation

In this paper, a development of decentralized intelligent proportional–integral–derivative (PID) controller for multi input multi output (MIMO) controller of double link flexible robotics manipulator is presented. Simultaneous optimization method is implemented in optimizing the parameters. The controllers are incorporated with optimization algorithm that is PSO to find out the parameters of the PID controllers. Numerical simulation was carried out in MATLAB/Simulink to evaluate the system in term of tracking capability and vibration suppression for both links. The optimal values of PID controller parameters that were achieved via off-line tuning using PSO were tested experimentally on the DLFRM experimental test rig. Experimental results show that the proposed control algorithm managed to control the system to reach desired angle for both hub at lower overshoot. Meanwhile, the vibration reduction shows improvement for both link 1 and 2. This signifies that, the PSO algorithm is very effective in optimizing the PID parameters for double link flexible robotics manipulator

Optimization Of Pid Controller For Double-Link Flexible Robotic Manipulator Using Metaheuristic Algorithms

This paper investigates the optimization approach of PID controller for double-link flexible robotic manipulator using metaheuristic algorithm. This research focus on population-based metaheuristic that is particle swarm optimization (PSO) and artificial bees algorithm (ABC) to tune the PID control parameters of the system. In the tuning process, the number of iteration was set and the number of particles was varied. The tuning process was interrupted once the convergence value of Mean Square Error (MSE) was achieved. For PSO, it was found that when the number of iteration increased, or the number of particles were set to higher values, there were no significant improvement of MSE. Results showed that 25 iterations were required for MSE to converge for hub angle and 20 iterations were required for MSE to converge for endpoint acceleration. Meanwhile, it was discovered that ABC portrayed the same pattern with PSO whereby when the number of iteration increased or the number of colony sizes were set to higher values, there were no significant improvement of MSE. From the results, 15 iterations were required for MSE to converge for hub angle and 25 iterations were required for MSE to converge for end-point acceleration. The performance of the algorithm was validated by evaluating the performance of the controllers in comparison with the conventional controller that is Ziegler Nichols (ZN) in term of input tracking capability and vibration suppression for both links. The system managed to reach desired angle for both hub angle 1 and 2. Besides, vibration reduction shows great improvement for both link 1 and 2. This signifies that, the PSO and ABC algorithm are very effective in optimizing the PID parameters

Reliable Smart Pet Feeding Machine Using Arduino Uno Starter Kit

Pet feeding can be done manually by pet owners, or automatically with the help of the pet feeders. The main concerns here are to solve the issue of unavailability of pet owners and the hygiene aspect in pet feeding. The developed automated system enables pet owners to feed their pets while they are away. The main objective of operating this research is to develop an automated pet feeding device focusing on in house pets by utilizing Arduino Uno as its Central Processing Unit (CPU) or microcontroller which function to control a weight sensor (load cells) and a servo motor. Smart Pet Feeding Machine is an automated pet feeding device designed to run based on weight mechanism. It will automatically dispense pet foods when minimum amount of pet food weight is triggered and will automatically stop dispensing when it reaches maximum amount of weight. Its architectural design includes a vertical storage compartment to store pet foods, a square opening at the bottom of storage compartment as opening for dispensing, a motorized dispenser and an aluminium bowl to place dispensed pet foods. The motion of dispenser is operated by a servo motor attached to the dispenser

Reliable Smart Pet Feeding Machine Using Arduino Uno Starter Kit

Pet feeding can be done manually by pet owners, or automatically with the help of the pet feeders. The main concerns here are to solve the issue of unavailability of pet owners and the hygiene aspect in pet feeding. The developed automated system enables pet owners to feed their pets while they are away. The main objective of operating this research is to develop an automated pet feeding device focusing on in house pets by utilizing Arduino Uno as its Central Processing Unit (CPU) or microcontroller which function to control a weight sensor (load cells) and a servo motor. Smart Pet Feeding Machine is an automated pet feeding device designed to run based on weight mechanism. It will automatically dispense pet foods when minimum amount of pet food weight is triggered and will automatically stop dispensing when it reaches maximum amount of weight. Its architectural design includes a vertical storage compartment to store pet foods, a square opening at the bottom of storage compartment as opening for dispensing, a motorized dispenser and an aluminium bowl to place dispensed pet foods. The motion of dispenser is operated by a servo motor attached to the dispenser

Experimental Analysis of Ankle Foot Orthosis Using Pneumatic Artificial Muscle

Ankle Foot Orthosis (AFO) is a rehabilitation device which is used to assist patients with weakness over the ankle, foot and part of the leg especially when surgery is not warranted or during the recovery phase of the foot. In this research, the Pneumatic Artificial Muscle was used to develop and actuate the AFO to mimic the movement of the ankle, namely, plantarflexion, dorsiflexion and eversion. Gait pattern analysis was used to gauge the effectiveness of the AFO in human subjects. Two healthy subjects were recruited to simulate gait patterns. The gait analysis showed that the AFO actuated PAM was able to resist plantarflexion while assisting dorsiflexion. During the stance phase, the AFO were able to allow free ankle movement up to approximately 5° dorsiflexion. It also allowed approximately 9° eversion of the ankle from neutral position. Toe drag in the swing phase was avoided as the foot drop was prevented. In conclusion, the AFO performed well in providing support for a foot drop condition and this presents an opportunity for further testing in real patients with foot drop

Fuzzy-Pid Based Controler For Active Vibration Control Of Nonlinear Dynamic Systems

The light weight characteristic offered by flexible structures can be easily influenced to the excessive vibration and it also brings several problems including instability, fatigue, bending and low performance. Therefore, it is compulsory to suppress the undesired vibration of flexible structures due to sustain its performance. This paper presents the development of hybrid controller known as fuzzy-PID based controller for vibration suppression of the horizontal flexible plate structure. Initially, the experimental rig was designed and integrated with the instrumentation system for vibration data collection purpose. The vibration data obtained experimentally was used to model the dynamic system based on auto-regressive with exogenous input structure using evolutionary swarm algorithm. The model obtained in simulation environment was then used for the development of PID-Fuzzy based controller. The performance of proposed controller was validated by exerting two types of disturbances to the system for robustness verification. It was indicated that PID-fuzzy controller was achieved higher attenuation value at the first mode of vibration by achieving 32.14 dB attenuation in the system. The attenuation value has been reduced from 103.5 dB to 71.36 dB, equivalent to 31.05 % attenuation, after the introduction of vibration control. The mean squared error achieved by the controller is 0.0237, compared with 0.6655 before the activation of controlle