Active vibration control of flexible structures by optimally placed sensors and actuators

PhD ThesisThe active vibration reduction of plane and stiffened plates was investigated using a genetic algorithm based on finite element modelling to optimise the location of sensors and actuators. The main aspects of this work were: Development of a finite element model for a plate stiffened by beams with discrete sensors and actuators bonded to its surface. Development of a finite element program for steel plates with various symmetrical and asymmetrical stiffening and edge conditions. Development of a genetic algorithm program based on the finite element modelling for the optimisation of the location and number of sensor/actuator pairs and feedback gain. Determination of optimum locations and feedback gain for collocated piezoelectric sensors and actuators on steel plates with various symmetrical and asymmetrical stiffening and edge conditions. Development of fitness and objective functions to locate sensors and actuators. Development of fitness and objective functions to determine the optimal number of sensors and actuators. Development of a reduced search space technique for symmetrical problems. Optimisation of vibration reduction control scheme parameters using the genetic algorithm. Optimisation of the number and location of sensor/actuator pairs and feedback gain to reduce material costs and structural weight and to achieve effective vibration reduction. The modelling was validated by comparison with conventional finite element analysis using ANSYS, and by experiment. The modelling was developed using a quadrilateral isoparametric finite element, based on first order shear deformation theory and Hamilton’s principle, which may be arbitrarily stiffened by beams on its edges. The model can be applied to flat plates with or without stiffening, with discrete piezoelectric sensors and actuators bonded to its surfaces. The finite element modelling was tested for flat and stiffened plates with different boundary conditions and geometries, and the results of the first six natural frequencies were validated with the ANSYS package and experimentally. A genetic algorithm placement strategy is proposed to find the global optimal distribution of two, four, six and ten sensor/actuator pairs and feedback gain based on the minimisation of optimal linear quadratic index as an objective function, and applied to a cantilever plate to attenuate the first six modes of vibration. The configuration of this global optimum was found to be symmetrically distributed about the dynamic axes of symmetry and gave higher vibration attenuation than previously published results with an asymmetrical distribution which was claimed to be optimal. Another genetic algorithm placement strategy is proposed to optimise sensor/actuator locations using new fitness and objective functions based on . This is applied to the same cantilever plate, and was also found to give a symmetrical optimal sensor/actuator configuration. As before, it was found that the optimal transducer locations are distributed with the same axes of symmetry and in agreement with the ANSYS results. A program to simulate the active vibration reduction of stiffened plates with piezoelectric sensors and actuators was written in the ANSYS Parametric Design Language (APDL). This makes use of the finite element capability of ANSYS and incorporates an estimator based on optimal linear quadratic and proportional differential control schemes to investigate the open and closed loop time responses. The complexity of the genetic algorithm problem is represented by the number of finite elements, sensor/actuator pairs and modes required to be suppressed giving a very large search space. In this study, this problem was reduced by the development of a new half and quarter chromosomes technique exploiting the symmetries of the structure. This greatly reduces the number of generations, and hence the computing time, required for the genetic algorithm to converge on the global optimal solution. This could be significant when the technique is applied to large and complex structures. Finally, new fitness and objective functions were proposed to optimise the number of sensor/actuator pairs required for effective active vibration reduction in order to reduce the added cost and weight. The number, location and feedback gain were optimised for the same cantilever plate and it was found that two sensor/actuator pairs in optimal locations could be made to give almost as much vibration reduction as ten pairs.Ministry of Higher Education and Scientific Research of Iraq

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

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

Structual-acoustic properties of automotive panels with shell elements

The automotive industry has witnessed a trend in the recent years of reducing the bulk weight of the vehicle in order to achieve improved ride dynamics and economical fuel consumption. Unfortunately, reducing the bulk weight often compromises the noise, vibra- tion, and harshness (NVH) characteristics of the vehicle. In general, the automotive body panels are made out of thin sheet metals (steel and aluminium) that have a very low bend- ing stiffness. Hence, it becomes important to find countermeasures that will increase the structural stiffness of these thin body panels without affecting their bulk weight. One such countermeasure is to introduce the geometrical indentations on various body panels. The geometrical indentation explained in this thesis is in the shape of elliptical dome, which supports the increase of the structural stiffness whilst keeping the bulk weight constant. The primary reason to choose elliptical domes as the applied geometrical indentation is due to a significant amount of interest shown by Jaguar Land Rover. Moreover, the elliptical domes, because of the nature of its design, can cover a larger surface area with minimal depth, thereby, eliminating the possibility of sharp and pointy indentations. This thesis presents a comprehensive study of the structural-acoustic behaviour of the automotive-type panels with dome-shaped indentations. The ultimate aim of this research is to establish a set of design guidelines in order to produce automotive-type panels with optimised dome-shaped indentations. In order to do so, a new design optimisation strategy is proposed that results in the optimal placement of the required dome-shaped indenta- tions. The optimisation problem addressed in this thesis is unlike a general mathematical problem, and requires specific methodologies for its solution. Therefore, the use of genetic algorithm is observed as the most suitable method in order to tackle this type of design optimisation problem. During the development of the optimisation procedure, the preliminary results show a consistency in the design patterns. This led to the motivation to investigate a few intuitively designed panels, which are inspired by the initial, trial, optimisation results. Therefore, four intuitively designed panels are investigated for their structural-acoustic characteristics. The study of the intuitively designed panels provided essential physical insight into the design optimisation problem, which ultimately defined the guidelines in order to develop the proposed optimisation procedure. This type of optimisation procedure is completely new in the domain of structural-acoustic optimisation. The efficiency of the underlying work lies in the separate investigation of both the structural and the acoustic properties of the panels with various dome-shaped indentations, and then utilising the insights gained in order to develop a specific optimisation algorithm to stream-line the dome-shaped panel design procedure

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

INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM

The gradient flexible plate structure has been widely used in engineering industries. However, the gradient flexible plate is susceptible to vibrational disturbances and affecting its durability and performance over time. Hence, the unwanted vibration needs to be controlled and can be accomplished by developing an accurate model. Despite that, the accurate model is hard to be obtained especially in estimating the model parameters. Thus, the research presents the development of dynamic modelling for gradient flexible plate structure (GFPS). A slanted GFPS with orientation angle of 30° and all edges clamped was developed and fabricated to represent the actual dynamics of the system. Then, data acquisition and instrumentation system were integrated to the rig to collect the input-output vibration data. The research utilised parametric system identification based on autoregressive with exogenous input (ARX) model structure. First, evolutionary algorithms, namely particle swarm optimisation (PSO) and grey wolf optimisation (GWO) were used in developing GFPS dynamic model and their performances were compared. It was discovered that GWO model outperformed PSO model. However, the computational time of GWO is slower compared to PSO. Thus, a hybrid of grey wolf and particle swarm optimisation (GWO-PSO) were proposed to further improve the system modelling. It was found out that the hybrid GWO-PSO model outperformed PSO and GWO models by achieving the lowest mean squared error, correlation up to 95 % confidence level, and good stability. The obtained GWO-PSO models which is model order 2 and model order 4 were verified by using proportional-integral-derivative (PID) based controller. Their performances were measured in terms of model robustness based on vibration suppression. The final result confirmed that model order 2 of GWO-PSO is the optimum model to represent GFPS system modelling with 71.08% vibration attenuation

Optimum design of a partially-treated MR-fluid sandwich plate

The present study concerns with dynamic characterization and optimal design of a partially treated magneto-rheological (MR) sandwich plate. An aluminum sandwich plate, partially treated with MR fluid (MRF 132DG) was fabricated for dynamic characterization in the laboratory. The MR-filled cavity in the plate was subjected to a uniform magnetic flux using two permanent magnets located at top and bottom of the structure. The dynamic response characteristics of the sandwich plate were experimentally obtained under harmonic force excitations. A finite element model of the partially-treated MR sandwich plate was developed using classical plate theory considering the effect of slippage between the top and bottom layers. The validity of the finite element model was demonstrated by comparing the theoretical results with those of the experiment. An optimization problem was subsequently formulated and solved using genetic algorithm (GA) to identify optimal locations for the MR fluid treatments for realizing maximum variations in stiffness and damping properties of the structure corresponding to the lower three modes of flexural vibration, individually and simultaneously, in response to the applied magnetic field. The effect of shear deformation on the vibration properties of the partially treated sandwich plate was particularly highlighted. The results suggest that the MR fluid treatments can significantly alter the stiffness and damping properties of the sandwich structure under noticeable shear strain, while a partial treatment could yield the changes in stiffness and damping comparable to those of a fully-treated plate

Smart FRP Composite Sandwich Bridge Decks in Cold Regions

INE/AUTC 12.0

New methodology for optimal placement of piezoelectric sensor/actuator pairs for active vibration control of flexible structures

This paper describes a computationally efficient method to determine optimal locations of sensor/actuator (s/a) pairs for active vibration reduction of a flexible structure. Previous studies have tackled this problem using heuristic optimization techniques achieved with numerous combinations of s/a locations and converging on a suboptimal or optimal solution after multithousands of generations. This is computationally expensive and directly proportional to the number of sensors, actuators, possible locations on structures, and the number of modes required to be suppressed (control variables). The current work takes a simplified approach of modeling a structure with sensors at all locations, subjecting it to external excitation force or structure base excitation in various modes of interest and noting the locations of n sensors giving the largest average percentage sensor effectiveness. The percentage sensor effectiveness is measured by dividing all sensor output voltage over the maximum for each mode using time and frequency domain analysis. The methodology was implemented for dynamically symmetric and asymmetric structures under external force and structure base excitations to find the optimal distribution based on time and frequency responses analysis. It was found that the optimized sensor locations agreed well with the published results for a cantilever plate, while with very much reduced computational effort and higher effectiveness. Furthermore, it was found that collocated s/a pairs placed in these locations offered very effective active vibration reduction for the structure considered