Evolutionary swarm algorithm for modelling and control of horizontal flexible plate structures

Numerous advantages offered by the horizontal flexible structure have attracted increasing industrial applications in many engineering fields particularly in the airport baggage conveyor system, micro hand surgery and semiconductor manufacturing industry. Nevertheless, the horizontal flexible structure is often subjected to disturbance forces as vibration is easily induced in the system. The vibration reduces the performance of the system, thus leading to the structure failure when excessive stress and noise prevail. Following this, it is crucial to minimize unwanted vibration so that the effectiveness and the lifetime of the structure can be preserved. In this thesis, an intelligent proportional-integral-derivative (PID) controller has been developed for vibration suppression of a horizontal flexible plate structure. Initially, a flexible plate experimental rig was designed and fabricated with all clamped edges boundary conditions at horizontal position. Then, the data acquisition and instrumentation systems were integrated into the experimental rig. Several experimental procedures were conducted to acquire the input-output vibration data of the system. Next, the dynamics of the system was modeled using linear auto regressive with exogenous, which is optimized with three types of evolutionary swarm algorithm, namely, the particle swarm optimization (PSO), artificial bee colony (ABC) and bat algorithm (BAT) model structure. Their effectiveness was then validated using mean squared error, correlation tests and pole zero diagram stability. Results showed that the PSO algorithm has superior performance compared to the other algorithms in modeling the system by achieving lowest mean squared error of 6103947.4 , correlation of up to 95 % confidence level and good stability. Next, five types of PID based controllers were chosen to suppress the unwanted vibration, namely, PID-Ziegler Nichols (ZN), PID-PSO, PID-ABC, Fuzzy-PID and PID-Iterative Learning Algorithm (ILA). The robustness of the controllers was validated by exerting different types of disturbances on the system. Amongst all controllers, the simulation results showed that PID tuned by ABC outperformed other controllers with 47.60 dB of attenuation level at the first mode (the dominant mode) of vibration, which is equivalent to 45.99 % of reduction in vibration amplitude. By implementing the controllers experimentally, the superiority of PID-ABC based controller was further verified by achieving an attenuation of 23.83 dB at the first mode of vibration and 21.62 % of reduction in vibration amplitude. This research proved that the PID controller tuned by ABC is superior compared to other tuning algorithms for vibration suppression of the horizontal flexible plate structure

Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure

This paper focused on modelling of a gradient flexible plate system utilizing an evolutionary algorithm, namely particle swarm optimization (PSO) and cuckoo search (CS) algorithm. A square aluminium plate experimental rig with a gradient of 30° and all edges clamped were designed and fabricated to acquire input-output vibration data experimentally. This input-output data was then applied in a system identification method, which used an evolutionary algorithm with a linear autoregressive with exogenous (ARX) model structure to generate a dynamic model of the system. The obtained results were then compared with the conventional method that is recursive least square (RLS). The developed models were evaluated based on the lowest mean square error (MSE), within the 95% confidence level of both auto and cross-correlation tests as well as high stability in the pole-zero diagram. Investigation of results indicates that both evolutionary algorithms provide lower MSE than RLS. It is demonstrated that intelligence algorithms, PSO and CS outperformed the conventional algorithm by 85% and 89%, respectively. However, in terms of the overall assessment, model order 4 by the CS algorithm was selected to be the ideal model in representing the dynamic modelling of the system since it had the lowest MSE value, which fell inside the 95% confidence threshold, indicating unbiasedness and stabilit

Effect of design parameters of serpentine-shaped flat plate solar collector under Malaysia climate conditions

Solar thermal energy plays a vital role in the industrial sector, especially for water heating applications. Further research to improve the efficiency of flat plate solar collectors by focusing on collector design modification is imperative. This research aimed to carry out an experimental investigation on comparative designs and fabrication approaches that deal with the analysis of flat plate solar collector thermal performance, thermal efficiency, the effect of various mass flow rates, and pressure drop analyses. In this paper, a different design modification of pipe collector with serpentine-shaped was established with different tube diameters (3/4-inch and 3/8-inch), and different pipe spacing (18.5 cm and 27.0 cm). Under the same heat radiation intensity and constant mass flow rate, a pipe collector with a tube diameter of 3/4-inch achieved 3.5% and 9.4% higher thermal performance and collector efficiency respectively compared to the tube diameter of 3/8-inch. Furthermore, the pipe collector with pipe spacing of 18.5 cm exhibited 4.3% and 12.6% higher thermal performance and collector efficiency respectively compared to pipe spacing of 27 cm. The relationship between collector efficiency and temperature difference was also investigated. Moreover, the effect of different mass flow rates was studied upon and it was found that a flow rate of 0.03 kg/s exhibited optimum thermal performance for the pipe collector. Additionally, a pressure drop was observed with the increase in flow rate, while decreases when the fluid temperature increase

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

PID controller based on bird mating optimizer for vibration cancellation of horizontal flexible plate

The flexible system has massive benefits compared to the rigid structure, which is lightweight, low energy consumption and high efficiency. However, the lightweight structure causes undesired vibrations on a system that could damage the structure. This paper proposes a modelling of horizontal flexible plate structure by utilizing bird mating optimizer algorithm and implementation of vibration control on the system in simulation environment. There are two main objectives of this project which are to model a horizontal flexible plate system and to design an accurate controller by eliminating the excessive vibration of the system in order to achieve high-performance efficiency. Initially, input–output experiment data is collected from previous researchers and utilized to model system development. Then, the linear autoregressive with exogenous (ARX) model is selected as a model structure for model development using system identification method via bird mating optimizer (BMO) algorithm. Thereafter, the developed models were evaluated by mean square error (MSE), correlation tests and pole-zero map. The finest model is identified based on the minimum MSE, stable in a pole-zero diagram and unbiased in correlation tests. Then, the mathematical transfer function of the best model is utilized for the development of the PID controller. The controller parameter is tuned using trial and error method. Finally, the developed controller was evaluated and accessed using two different disturbances known as single and multiple sinusoidal disturbances. The result shows a significant vibration reduction of 11.18 and 10.13% for single and multiple sinusoidal disturbances, respectively

Modelling of Flexible Manipulator System Using Flower Pollination Algorithm

The study of the flexible manipulator system (FMS) has attracted many researchers due to its superiority of light weight and faster system response. Flexible manipulator system is an improvement from its rigid structure, however it can be easily vibrated when it subjected to disturbance. If the advantages of FMS are not to be sacrificed, an accurate model and efficient control system must be developed. Thus, this study presents an approach of evolutionary swarm algorithm via flower pollination algorithm (FPA) to model the dynamic system of flexible manipulator structure. An experimental rig of flexible manipulator system was developed for input-output acquisition. Then, this input-output data was fed to system identification method to obtain a dynamic model of flexible manipulator system utilizing evolutionary algorithm with linear auto regressive with exogenous (ARX) model structure. The result obtained through flower pollination algorithm was then compared with conventional method known as least square (LS) algorithm in terms of mean square error (MSE), correlation test and pole-zero diagram. The best MSE achieved by LS modeling for endpoint acceleration and hub angle positioning are 0.0075 and 0.0028, respectively. While, the best MSE produced by flower pollination algorithm for endpoint acceleration and hub angle positioning are 0.0063 and 0.0020, respectively. It is reveals that the performance of intelligence algorithm is superior than conventional algorithm

A Single Objective Flower Pollination Algorithm for Modeling the Horizontal Flexible Plate System

Flexible plate structure is a chosen technology used for many applications since past decades ago. However, this structure has a disadvantage that needs to be avoided which is easy to vibrate. Thus, this project presents the modelling of horizontal flexible plate system using bio-inspired flower pollination algorithm. The objective is to obtain an accurate model of the real system in the simulated environment. The collected of real vibration data through experimental study was then utilized to develop the dynamic system model based on linear autoregressive with exogenous (ARX) model structure and optimized by flower pollination algorithm (FPA). The algorithm is a novel bio-inspired optimization algorithm that mimics the real-life processes of the flower pollination. The gained model in this simulation is approved utilizing the most minimal mean squared error, correlation tests, and pole zero graph stability due to check the robustness of the model. The performance of the developed model was then compared with the conventional algorithm known as recursive least square (RLS). The best model achieved in this study will be used as a platform of controller development using active vibration control technique

Intelligent Optimization of Force Tracking Parameters for MR Damper Modelling using Firefly Algorithm

Magnetorheological (MR) damper system is commonly used to replace the conventional damper in the suspension system due to its low power consumption, fast time response and simple structure. Since inner loop controller is very important in defining the amount of current supplied to the MR damper system, many existing controllers are found not well-structured in terms of calculating the optimum value of the controller parameter. Poor control design using the conventional method will cause the output current obtained for the MR damper to be unpredictable. To overcome this problem, an intelligent optimization method known as firefly algorithm (FA) was used by this study to optimize the force tracking controller (FTC) parameters as to achieve the exact damping force of MR damper system. The MR damper was first developed using Spencer model and the required voltage input was then provided by the FTC. The controller parameters were tuned using intelligent FA method in order to find the optimum values which would identify the accuracy of the force tracking that followed the MR damping force. The simulation shows that the FTC with FA technique is able to track the desired force better than the heuristic method up to 1.71 % error considering a given desired input force

Intelligent PID Controller Tuned by Bacterial Foraging Optimization Algorithm for Vibration Suppression of Horizontal Flexible Structure

Flexible structure offers various advantages such as being lightweight, efficient, quick system response and low energy consumption. However, this structure produces too much vibration which leads to system failure. To overcome this drawback, this project developed an intelligent vibration controller based on Bacterial Foraging Optimization (BFO) and incorporated into a Proportional-Integral-Derivative (PID) controller. BFO is a metaheuristic approach categorized as an evolutionary algorithm recently developed, and a nature-inspired optimization algorithm. BFO has been successfully applied to solve some engineering problems due to its simplicity and ease of implementation. Therefore, by introducing BFO to the PID controller, the desired parameters to control vibration experienced by a horizontal flexible plate can be easily found. The performance of the intelligent PID controller was compared to the conventional tuning method known as Ziegler-Nichols (ZN). It was noticed that the PID controller tuned by BFO successfully outperformed the PID controller tuned by ZN by achieving a high attenuation at the first mode of vibration of 44.65 dB as compared to the latter which was only attenuated at the first mode of vibration at 12.8 dB. The developed PID controller was also able to maintain a good performance level even when this system was introduced to multiple sinusoidal disturbance

Modelling of flexible beam based on ant colony optimization and cuckoo search algorithms

Flexible beam structure is usually applied in various fields of engineering and industrial. There are few points of interest using flexible structure and one of the advantages is that its lighter compared to a rigid structure. Besides that, flexible beam also can save cost, reduce energy consumption, and improve operation safety. However, flexible beam structures are too sensitive and susceptible to with unwanted vibration that would cause damage or degradation to the structure system. Hence, to overcome the problem, appropriate modelling and controller for such systems should be developed. Currently, there are plenty of methods that have been developed by researchers to suppress undesired vibration. Based on previous studies, most researchers nowadays use system identification (SI) as a modelling technique to develop a dynamic model of flexible structure via swarm intelligence algorithm (SIA). Therefore, two type of algorithms was used in this work for modelling development of flexible beam structure, which are ant colony optimization (ACO) and cuckoo search algorithm (CSA). Based on the comparative results, CSA achieved the lowest mean square error (MSE) value of 6.1547×10-9 meanwhile ACO recorded a MSE of 1.0728×10-8. Moreover, CSA was deduced to be the best model for flexible beam structure because it achieved 95 % confidence level in correlation test and has excellent stability in pole-zero diagram system. Thus, CSA is a suitable algorithm to represent the real behavior of flexible beam structure in a system