21 research outputs found
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