Vibration suppression of the horizontal flexible plate using proportional– integral–derivative controller tuned by particle swarm optimization

This paper presents the development of an active vibration control for vibration suppression of the horizontal flexible plate structure using proportional–integral–derivative controller tuned by a conventional method via Ziegler–Nichols and an intelligent method known as particle swarm optimization algorithm. Initially, the experimental rig was designed and fabricated with all edges clamped at the horizontal position of the flexible plate. Data acquisition and instrumentation systems were designed and integrated into the experimental rig to collect input–output vibration data of the flexible plate. The vibration data obtained through experimental study was used to model the system using system identification technique based on auto-regressive with exogenous input structure. The plate system was modeled using particle swarm optimization algorithm and validated using mean squared error, one-step ahead prediction, and correlation tests. The stability of the model was assessed using pole zero diagram stability. The fitness function of particle swarm optimization algorithm is defined as the mean squared error between the measured and estimated output of the horizontal flexible plate system. Next, the developed model was used in the development of an active vibration control for vibration suppression on the horizontal flexible plate system using a proportional–integral–derivative controller. The proportional–integral–derivative gains are optimally determined using two different ways, the conventional method tuned by Ziegler–Nichols tuning rules and the intelligent method tuned by particle swarm optimization algorithm. The performances of developed controllers were assessed and validated. Proportional–integral–derivative-particle swarm optimization controller achieved the highest attenuation value for first mode of vibration by achieving 47.28 dB attenuation as compared to proportional–integral–derivative-Ziegler–Nichols controller which only achieved 34.21 dB attenuation

Modelling and control of horizontal flexible plate using particle swarm optimization

This paper presents the modeling and active vibration control using an evolutionary swarm algorithm known as particle swarm optimization. Initially, a flexible plate experimental rig was designed and fabricated with all clamped edges as boundary conditions constrained at horizontal position. The purpose of the experimental rig development is to collect the input-output vibration data. Next, the data acquisition and instrumentation system were designed and integrated with the experimental rig. Several procedures were conducted to acquire the input-output vibration data. The collected vibration data were then utilized to develop the system model. The parametric modeling using particle swarm optimization was devised using an auto regressive model with exogenous model structure. The developed model was validated using mean square error, one step ahead prediction, correlation tests and pole-zero diagram stability. Then, the developed model was used for the development of controller using an active vibration control technique. It was found that particle swarm optimization based on the active vibration control using Ziegler-Nichols method has successfully suppressed the unwanted vibration of the horizontal flexible plate system. The developed controller achieved the highest attenuation value at the first mode of vibration which is the dominant mode in the system with 34.37 dB attenuation

Evolutionary algorithms for active vibration control of flexible manipulator

Flexible manipulator systems offer numerous advantages over their rigid counterparts including light weight, faster system response, among others. However, unwanted vibration will occur when flexible manipulator is subjected to disturbances. If the advantages of flexible manipulator are not to be sacrificed, an accurate model and efficient control system must be developed. This thesis presents the development of a Proportional-Integral-Derivative (PID) controller tuning method using evolutionary algorithms (EA) for a single-link flexible manipulator system. Initially, a single link flexible manipulator rig, constrained to move in horizontal direction, was designed and fabricated. The input and output experimental data of the hub angle and endpoint acceleration of the flexible manipulator were acquired. The dynamics of the system was later modeled using a system identification (SI) method utilizing EA with linear auto regressive with exogenous (ARX) model structure. Two novel EAs, Genetic Algorithm with Parameter Exchanger (GAPE) and Particle Swarm Optimization with Explorer (PSOE) have been developed in this study by modifying the original Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithms. These novel algorithms were introduced for the identification of the flexible manipulator system. Their effectiveness was then evaluated in comparison to the original GA and PSO. Results indicated that the identification of the flexible manipulator system using PSOE is better compared to other methods. Next, PID controllers were tuned using EA for the input tracking and the endpoint vibration suppression of the flexible manipulator structure. For rigid motion control of hub angle, an auto-tuned PID controller was implemented. While for vibration suppression of the endpoint, several PID controllers were tuned using GA, GAPE, PSO and PSOE. The results have shown that the conventional auto-tuned PID was effective enough for the input tracking of the rigid motion. However, for end-point vibration suppression, the result showed the superiority of PID-PSOE in comparison to PID-GA, PID-GAPE and PID-PSO. The performance of the best simulated controller was validated experimentally later. Through experimental validation, it was found that the PID-PSOE was capable to suppress the vibration of the single-link flexible manipulator with highest attenuation of 31.3 dB at the first mode of the vibration. The outcomes of this research revealed the effectiveness of the PID controller tuned using PSOE for the endpoint vibration suppression of the flexible manipulator amongst other evolutionary methods

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