A comparative study of PSO, GSA and SCA in parameters optimization of surface grinding process

The selection of parameters in grinding process remains as a crucial role to guarantee that the machined product quality is at the minimum production cost and maximum production rate. Therefore, it is required to utilize more advance and effective optimization methods to obtain the optimum parameters and resulting an improvement on the grinding performance. In this paper, three optimization algorithms which are particle swarm optimization (PSO), gravitational search, and Sine Cosine algorithms are employed to optimize the grinding process parameters that may either reduce the cost, increase the productivity or obtain the finest surface finish and resulting a higher grinding process performance. The efficiency of the three algorithms are evaluated and comparedwith previous results obtained by other optimization methods on similar studies.The experimental results showed that PSO algorithm achieves better optimization performance in the aspect of convergence rate and accuracy of best solution.Whereas in the comparison of results of previous researchers, the obtained result of PSO proves that it is efficient in solving the complicated mathematical model of surface grinding process with different conditions

Modelling and PSO Fine-tuned PID Control of Quadrotor UAV

This paper describes nonlinear dynamics model of x-configuration quadrotor using Newton-Euler modelling technique. To stabilize quadrotor attitude (roll (ϕ), pitch (θ), yaw (ψ)) during hovering, a PID controller is proposed. There is individual PID controller for each roll, pitch, yaw and z where 12 parameters consist of kp, ki, and kd are fine-tuned using particle swarm optimization algorithms. From the simulation, the sum absolute error fitness function give the best optimize result where quadrotor achieve zero steady state error for hovering with 18.9% overshoot, and 4.42s settling time. Accordingly, for attitude stabilization, roll angle, pitch angle, and yaw angle converge to the set point, zero approximately with settling time 2.76s, 0.1s and 3.2s respectively

A comparative study of PSO, GSA and SCA in parameters optimization of surface grinding process

The selection of parameters in grinding process remains as a crucial role to guarantee that the machined product quality is at the minimum production cost and maximum production rate. Therefore, it is required to utilize more advance and effective optimization methods to obtain the optimum parameters and resulting an improvement on the grinding performance. In this paper, three optimization algorithms which are particle swarm optimization (PSO), gravitational search, and Sine Cosine algorithms are employed to optimize the grinding process parameters that may either reduce the cost, increase the productivity or obtain the finest surface finish and resulting a higher grinding process performance. The efficiency of the three algorithms are evaluated and comparedwith previous results obtained by other optimization methods on similar studies.The experimental results showed that PSO algorithm achieves better optimization performance in the aspect of convergence rate and accuracy of best solution.Whereas in the comparison of results of previous researchers, the obtained result of PSO proves that it is efficient in solving the complicated mathematical model of surface grinding process with different conditions

Stopwatch Verification Platform The Development Of An Automated Device For Stopwatch Calibration

Stopwatch is designed to quantify the elapses time between the start activation and deactivation. To ensure the precision of the time taken, calibration of the device is essential. National Institute of Standard and Technology (NIST) has provide complete guidelines on the stopwatch and timer calibration. However, the standards guidelines usually use manual calibration personnel hence may possibly cause inefficiency for calibration works. The 'Stopwatch Verification Platform' is a prototype aimed to replace the manual handling of digital stopwatch calibration with an automated timer-controlled device, without interfering with NIST recommended practice. The 'Stopwatch Verification Platform' is able to automatically trigger start and stop the reference and test stopwatches by integrating with precise timer controller and specific relay connections. The timer controller circuitry is integrated with the reference stopwatch circuitry, with 0.001 second resolutionIt is capable in verifying more units of stopwatches by using one reference. The measurement procedures do not contradict with the NIST recommended practice. This prototype does not alter the uncertainties calculation because it is a well-developed standard formula which is set by international standard

Path tracking controller of an autonomous armoured vehicle using modified Stanley controller optimized with particle swarm optimization

This study presents the development and optimization of a proposed path tracking controller for an autonomous armoured vehicle. A path tracking control is developed based on an established Stanley controller for autonomous vehicles. The basic controller is modified and applied on a non-linear, 7degree-of-freedom armoured vehicle model, and consists of various modules such as handling model, tire model, engine, and transmission model. The controller is then optimized using particle swarm optimization algorithm to select the optimum set of controller parameters. The main motivation of this study is that implementation of path tracking control on an autonomous armoured vehicle is still very limited and it is important to have a specific study on this field due to the different dynamics and properties of the armoured vehicle compared to normal passenger vehicles. Several road courses are considered and the performance of the developed controller in guiding the vehicle along these courses was compared against the original Stanley Controller. It was found that the optimized controller managed to improve the overall lateral error throughout the courses with 24–96% reduction in lateral error. Also, the optimization for the proposed controller was found to converge faster than its counterpart with up to 93% better solution

PID Control Tuning via Particle Swarm Optimization for Coupled Tank System

This paper presents the use of meta-heuristic technique to obtain three parameters (KP, KI and KD) of PID controller for Coupled Tank System (CTS). Particle Swarm Optimization (PSO) is chosen and Sum Squared Error is selected as objective function. This PSO is implemented for controlling desired liquid level of CTS. Then, the performances of the system are compared to various conventional techniques which are Trial and Error, Auto-Tuning, Ziegler-Nichols (Z-N) and Cohen-Coon(C-C) method. Simulation is conducted within Matlab environment to verify the transient response specifications in terms of Rise Time (TR), Settling Time (TS), Steady State Error(SSE) and Overshoot (OS). Result obtained shows that performance of CTS can be improved via PSO as PID tuning methods

Cost-Effective Interfaces with Arduino-LabVIEW for an IOT-Based Remote Monitoring Application

To date, research efforts have demonstrated the stimulated need for the Internet of Things (IoT) based monitoring device in their laboratory. The benefits of remote laboratories in overcoming time constraints and the disadvantages of usability of conventional laboratories are well known. In addition to the current control engineering laboratories, a remote lab that incorporates an industry-relevant method has been established to assist in the understanding of data acquisition with cost-effective platform integration. However, one of the greatest challenges is the creation of a low-cost and user-friendly remote laboratory experiment that is ideal for interacting with the actual laboratory via a mobile device. The main objective of this work is therefore to build a remote laboratory system based on the IoT using the LabVIEW-Arduino interface with the example of proportional-integral-derivative (PID) tuning scheme for the LD-Didactic temperature plant. The practical work would include the implementation of the low-cost Arduino module connecting the actual plant to mobile devices. In addition, interfaces have been built using the Blynk application to allow communication between the end user and the laboratory equipment. In line with the Industrial Revolution 4.0 (IR 4.0), the proposed study structure called for the digitization of the current laboratory experiment method

Cuckoo Search Approach for Cutting Stock Problem

Cutting Stock Problem has been used in many industries like paper, glass, wood and etc. Cutting Stock Problem has helped industries to reduce trim loss and at the same time meets the customer’s requirement. The purpose of this paper is to develop a new approach which is Cuckoo Search Algorithm in Cutting Stock Problem. Cutting Stock Problem with Linear Programming based method has been improved down the years to the point that it reaches limitation that it cannot achieve a reasonable time in searching for solution. Therefore, many researchers have to turn to metaheuristic algorithms as a solution to the problem which also makes these algorithms become famous. Cuckoo Search Algorithm is selected because it is a new algorithm and outperforms many algorithms. Hence, this paper intends to experiment the performance of Cuckoo Search in Cutting Stock Problem

A Brief Review of Cuckoo Search Algorithm (CSA) Research Progression from 2010 to 2013

Cuckoo Search Algorithm is a new swarm intelligence algorithm which based on breeding behavior of the Cuckoo bird. This paper gives a brief insight of the advancement of the Cuckoo Search Algorithm from 2010 to 2013. The first half of this paper presents the publication trend of Cuckoo Search Algorithm. The remaining of this paper briefly explains the contribution of the individual publication related to Cuckoo Search Algorithm. It is believed that this paper will greatly benefit the reader who needs a bird-eyes view of the Cuckoo Search Algorithm’s publications trend

E-Water Level: Educational Kit For Testing Student Knowledge On Transient Response Using Water Level Control

Control Principle course is a part of syllabus in the diploma or degree in Electrical Engineering programme where students are exposed to topics such as time response analysis. One of the topics in this course is Transient Response analysis where it requires students to calculate the characteristic of the response based on set of formula. One of the difficulty encounters in delivering this topic is students having difficulty to relate the theory with the application as most theoretical part of this topic does not explain on how the transient response graph is obtained in the first place. In order to address this problem, this paper proposed E-Water Level educational kit that can be used by student in order to understand independently the transient response analysis by applying theory on the water level control application where the student knowledge on Transient Response parameters are tested, namely the delay time, rise time, damping ratio and setting time. The system consists of Arduino Microcontroller, water tank, water pump, relay, ultrasonic sensor and electronic display. The novelty of this educational kit is that the educational kit is adaptive in bridging the gap between theory and application in which the data is generated by real application of water level and the answers for the questions are automatically generated based on the data obtained. Thus, each student will experience different set of question