A novel hybrid bacteria-chemotaxis spiral-dynamic algorithm with application to modelling of flexible systems

This paper presents a novel hybrid optimisation algorithm namely HBCSD, which synergises a bacterial foraging algorithm (BFA) and spiral dynamics algorithm (SDA). The main objective of this strategy is to develop an algorithm that is capable to reach a global optimum point at the end of the final solution with a faster convergence speed compared to its predecessor algorithms. The BFA is incorporated into the algorithm to act as a global search or exploration phase. The solutions from the exploration phase then feed into SDA, which acts as a local search or exploitation phase. The proposed algorithm is used in dynamic modelling of two types of flexible systems, namely a flexible robot manipulator and a twin rotor system. The results obtained show that the proposed algorithm outperforms its predecessor algorithms in terms of fitness accuracy, convergence speed, and time-domain and frequency-domain dynamic characterisation of the two flexible systems. © 2014 Elsevier Ltd

Dynamic modelling of a single-link flexible manipulator: Parametric and non-parametric approaches

This paper presents an investigation into the development of parametric and non-parametric approaches for dynamic modelling of a flexible manipulator system. The least mean squares, recursive least squares and genetic algorithms are used to obtain linear parametric models of the system. Moreover, non-parametric models of the system are developed using a non-linear AutoRegressive process with eXogeneous input model structure with multi-layered perceptron and radial basis function neural networks. The system is in each case modelled from the input torque to hub-angle, hub-velocity and end-point acceleration outputs. The models are validated using several validation tests. Finally, a comparative assessment of the approaches used is presented and discussed in terms of accuracy, efficiency and estimation of the vibration modes of the system

Control and modeling of underwater flexible manipulator structure

The use of flexible structures in many engineering applications is expanding rapidly. Position control is delicate, such as angular position control of a flexible structure especially underwater condition. Flexible structure in an underwater condition often having the problem of the hub angle position as the hub angle is affected by the inline force of the flexible structure underwater. To develop an optimum control system for the horizontal motion of such condition, the operating system must first be identified. A system model of an experimental test rig representing the Underwater Flexible Single Link Manipulator System (UFSLMS), needs to be developed before designing a controller to control the hub angle position. The objectives of this project are to identify the model and develop the controller to control the hub angle position of a UFSLMS. Previous studies have shown that parametric modelling involving Auto Regressive with Exogenous Input model using Recursive Least Squares algorithm, and non-parametric modelling involving Evolution Algorithm are suitable to model the UFSLMS system, with acceptably low Mean Square Error. The project is done by reviewing the UFSLMS dynamic modelling and control methodology. The collection of data from the UFSLMS system will be simulated and identified as the dynamic UFSLMS. A Proportional- Integral-Derivative controller is developed based on the system identification model, using heuristic techniques within MATLAB environment and robustness test is carried out at different magnitudes to determine the robustness of the controller. The performance of the controllers thus developed is verified and validated by simulation on MATLAB SIMULINK. The objectives are achieved when the controller is proven to be stable by effectively control the hub angle position in the horizontal motion underwater

OUTPUT BASED INPUT SHAPING FOR OPTIMAL CONTROL OF SINGLE LINK FLEXIBLE MANIPULATOR

Endpoint residual vibrations and oscillations due to flexible and rigid body motions are big challenges in control of single link flexible manipulators, it makes positioning of payload difficult especially when using various payloads. This paper present output based input shaping with two different control algorithms for optimal control of single link flexible manipulators. Output based filter (OBF) is designed using the signal output of the system and then incorporated with both linear quadratic regulator (LQR) and PID separately for position and residual vibration control. The Robustness of these control algorithms are tested by changing the payloads from 0g to30g, 50g and 70g in each case. Based on MATLAB simulation results and time response analysis, LQR-OBF outperformed the PID-OBF in both tracking and vibration reduction

Modelling and control of two-link flexible manipulator

Flexible link manipulators have caught the interest of many researchers due to the limitations of their rigid counterparts. However, Flexible manipulators introduces undesired vibrations which is not easy to control due to its high-non linearity. In order to keep the advantages associated with the lightness and flexibility of the manipulators, accurate modelling of the system and efficient reliable controller have to be developed which is the focus of this study. The two-link flexible manipulator is split into 4 models, the Hub angle and endpoint vibrations of both links of the Two-Link Flexible Manipulator. Input and output data were obtained from an experimental rig. Each model was obtained through system identification techniques within MATLAB simulation environment, namely conventional Recursive Least Square and Cuckoo Search Algorithm. Comparison was made between models developed using the two algorithms and this study shows that Cuckoo Search Algorithm is superior than Recursive Least Square Algorithm based on Mean Square error (MSE). RLS developed models MSE are 5.6321×10−5,0.0018,0.0129 & 0.0078e for hub angle 1, hub angle 2, deflection 1 and deflection 2 respectively. CSA developed models MSE are 2.7164×10−5,1.1546×10−5,6.0404×10−4 & 0.0026 respectively. Correlation tests showed that the hub angle models are biased, while the deflection models are unbiased for both algorithms. Finally, controllers intelligently tuned by Cuckoo search optimization algorithm were introduced to control the hub angle position and the endpoint vibrations. The rise time and maximum overshoot are 0.5 seconds and 0 rad for hub angle 1 and 0.5 seconds and 0.2 rad for hub angle 2. The setting time and maximum overshoot are 2 seconds and 0.01 rad for deflection 1 and 2 seconds and 0.007 rad for deflection 2

Novel metaheuristic hybrid spiral-dynamic bacteria-chemotaxis algorithms for global optimisation

© 2014 Elsevier B.V. All rights reserved. This paper presents hybrid spiral-dynamic bacteria-chemotaxis algorithms for global optimisation and their application to control of a flexible manipulator system. Spiral dynamic algorithm (SDA) has faster convergence speed and good exploitation strategy. However, the incorporation of constant radius and angular displacement in its spiral model causes the exploration strategy to be less effective hence resulting in low accurate solution. Bacteria chemotaxis on the other hand, is the most prominent strategy in bacterial foraging algorithm. However, the incorporation of a constant step-size for the bacteria movement affects the algorithm performance. Defining a large step-size results in faster convergence speed but produces low accuracy while de.ning a small step-size gives high accuracy but produces slower convergence speed. The hybrid algorithms proposed in this paper synergise SDA and bacteria chemotaxis and thus introduce more effective exploration strategy leading to higher accuracy, faster convergence speed and low computation time. The proposed algorithms are tested with several benchmark functions and statistically analysed via nonparametric Friedman and Wilcoxon signed rank tests as well as parametric t-test in comparison to their predecessor algorithms. Moreover, they are used to optimise hybrid Proportional-Derivative-like fuzzy-logic controller for position tracking of a flexible manipulator system. The results show that the proposed algorithms significantly improve both convergence speed as well as fitness accuracy and result in better system response in controlling the flexible manipulator

Study of Motion Control of A Flexible Link

20th century has witnessed massive upsurge in the use of manipulators in several industries especially in space, defense, and medical industries. Among the types of manipulators used, single link manipulators are the most widely used. A single link robotic manipulator is nothing but a link controlled by an actuator to carry out a particular function such as placing a payload from point A to point B. For low power requirements single link manipulators are made up of light weight materials which require flexibility considerations.Flexibility makes the dynamics of the link heavily non-linear which induces vibrations and overshoot. In this project initially the dynamic model of rigid flexible manipulator is explained, then the state space model of the manipulator system is incorporated into MATLAB. The link flexibility is studied by a single beam FEmodel, where expressions for kinetic and potential energyare employed to derive the torqueequation.The 3 flexible link equations are coupled in terms of 3 variables, θ, Ø and v. The tip angle is finally given aslvfor flexible case whereas for the rigid manipulator the tip angle is same as the hub angle θ. Thereforeaccurate computation of v is very important. The joint flexibility is excluded from analysis.Several comparisons were made between the rigid and flexible link for torque requirement. The relation between the trajectory and hub angle is also plotted in a graph.Finally a PD controller taking the errors and its derivative is designed based on the rigid link dynamics

Intelligent PID Controller of Flexible Link Manipulator with Payload

This paper presents the experimental study of intelligent PID controller with the present of payload. The controllers were constructed to optimally track the desired hub angle and vibration suppression of DLFRM. The hub angle and end-point vibration models were identified based on NNARX structure. The results of all developed controllers were analyzed in terms of trajectory tracking and vibration suppression of DLFRM subjected to disturbance. The simulation studies showed that the intelligent PID controllers have provided good performance. Further investigation via experimental studies was carried out. The results revealed that the intelligent PID control structure able to show similar performance up to 20 g of payload hold by the system. Once the payload increased more than 20 g, the performance of the controller degrades. Thus, it can be concluded that, the controllers can be applied in real application, provided the tuning process were carried out with the existence of the maximum payload which will be subjected in the system. The 20 g payload value can act as uncertainty for the controller performance