3 research outputs found
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
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
Hub Angle Control for A Single Link Flexible Manipulator Based on Cuckoo Search Algorithm
Flexible manipulators are one of the promising
devices that can be applied in many fields especially in
automation and manufacturing fields as they are designed to
reduce energy consumption and increase the speed of operation.
However, agitation process experienced in the complex
structure of the system which causes unwanted vibration will
affect the precision of operation. Thus, an efficient control
system is required to make them functional. Therefore, the
development of an accurate model of flexible manipulator was
presented prior to establishing active vibration control to
suppress the vibration and increase efficiency of the system.
This paper presents the development of a Proportional-IntegralDerivative controller based on cuckoo search algorithm for a
single link flexible manipulator system. Initially, the system was
modelled using input and output experimental data of the hub
angle. System identification was implemented via swarm
intelligence algorithm known as cuckoo search algorithms based
on auto regressive with exogenous model structure. Then, the
performance of proposed algorithms was validated based on
three robustness methods known as mean squared error, pole
zero diagram stability and correlation tests. The simulation
results showed superior performance of cuckoo search
algorithm by achieving lowest mean squared error, good
correlation tests and high root locus stability. Then, the cuckoo
search model was implemented in the proposed control scheme
with the aim of accurate positioning at the end point of flexible
manipulator