Iterative learning control: algorithm development and experimental benchmarking

This thesis concerns the general area of experimental benchmarking of Iterative Learning Control (ILC) algorithms using two experimental facilities. ILC is an approach which is suitable for applications where the same task is executed repeatedly over the necessarily finite time duration, known as the trial length. The process is reset prior to the commencement of each execution. The basic idea of ILC is to use information from previously executed trials to update the control input to be applied during the next one. The first experimental facility is a non-minimum phase electro-mechanical system and the other is a gantry robot whose basic task is to pick and place objects on a moving conveyor under synchronization and in a fixed finite time duration that replicates many tasks encountered in the process industries. Novel contributions are made in both the development of new algorithms and, especially, in the analysis of experimental results both of a single algorithm alone and also in the comparison of the relative performance of different algorithms. In the case of non-minimum phase systems, a new algorithm, named Reference Shift ILC (RSILC) is developed that is of a two loop structure. One learning loop addresses the system lag and another tackles the possibility of a large initial plant input commonly encountered when using basic iterative learning control algorithms. After basic algorithm development and simulation studies, experimental results are given to conclude that performance improvement over previously reported algorithms is reasonable. The gantry robot has been previously used to experimentally benchmark a range of simple structure ILC algorithms, such as those based on the ILC versions of the classical proportional plus derivative error actuated controllers, and some state-space based optimal ILC algorithms. Here these results are extended by the first ever detailed experimental study of the performance of stochastic ILC algorithms together with some modifications necessary to their configuration in order to increase performance. The majority of the currently reported ILC algorithms mainly focus on reducing the trial-to-trial error but it is known that this may come at the cost of poor or unacceptable performance along the trial dynamics. Control theory for discrete linear repetitive processes is used to design ILC control laws that enable the control of both trial-to-trial error convergence and along the trial dynamics. These algorithms can be computed using Linear Matrix Inequalities (LMIs) and again the results of experimental implementation on the gantry robot are given. These results are the first ever in this key area and represent a benchmark against which alternatives can be compared. In the concluding chapter, a critical overview of the results presented is given together with areas for both short and medium term further researc

DC motorun otomatik ayarlamalı PID ile hız kontrolünün gerçekleştirilmesi

Although advanced controllers are used in control applications, proportional-integral-derivative (PID) controllers are preferred in industry due to their simple structure and ease of application. However, it can difficult to set these controller parameters for the controlled platform. These parameters tuning with trial-error method leads to time and job loss, and the parameters determined in this way cannot provide a sufficiently efficient operating characteristic. In order to overcome this problem related to PID parameter tuning many automatic tuning methods have been developed. In this paper, the automatic tuning method proposed by Aström and Hagglund was applied to a DC motor speed control system. The DC motor speed control system was implemented in an interface designed on Laboratory Virtual Instrument Electronic Workbench (LabVIEW) environment and CompactRIO unit. The PID parameters obtained with trial-error and two types auto-tuning methods were tested in the DC motor control system and achieved results were compered. The results showed that performance of the PID controller tuned with LAbVIEW auto-tuning method is better than others.Kontrol uygulamalarında gelişmiş kontrolörler kullanılsa da PID (Proportional-Integral-Derivative) kontrolörler basit yapısından ve kolay uygulanabildiğinden dolayı endüstride tercih edilmektedir. Ancak kontrol edilecek platforma uygun PID parametrelerinin ayarlanması oldukça güç olabilmektedir. Bu parametrelerin deneme yanılma yöntemiyle ayarlanması zaman ve iş kaybına sebep olmakla birlikte bu yolla tespit edilen parametrelerle ayarlanan kontrolörler yeterince verimli bir çalışma karakteristiği sunmayabilmektedir. PID parametrelerinin ayarıyla ilgili bu sorunların üstesinden gelebilmek için çok sayıda otomatik ayar yöntemi geliştirilmiştir. Bu makalede Åström ve Hägglund tarafından önerilen otomatik ayar yöntemi bir DC motoru hız kontrol sistemine uygulanmıştır. Bu DC motor hız kontrol sistemi LabVIEW (Laboratory Virtual Instrument Electronic Workbench) ortamında geliştirilen ara yüz ve CompactRIO ünitesi üzerinde gerçekleştirilmiştir. Deneme yanılma ve iki farklı otomatik ayarlama yöntemiyle elde edilen PID parametreleri DC motor kontrol sistemi üzerinde denenmiş ve elde edilen sonuçlar karşılaştırılmıştır. Sonuçlar, LabVIEW otomatik ayarlama yöntemiyle elde edilen parametrelerle işletilen PID kontrolörün daha iyi performans gösterdiğini göstermişti

On the robustness of the slotine-Li and the FPT/SVD-based adaptive controllers

A comparative study concerning the robustness of a novel, Fixed Point Transformations/Singular Value Decomposition (FPT/SVD)-based adaptive controller and the Slotine-Li (S&L) approach is given by numerical simulations using a three degree of freedom paradigm of typical Classical Mechanical systems, the cart + double pendulum. The effects of the imprecision of the available dynamical model, presence of dynamic friction at the axles of the drives, and the existence of external disturbance forces unknown and not modeled by the controller are considered. While the Slotine-Li approach tries to identify the parameters of the formally precise, available analytical model of the controlled system with the implicit assumption that the generalized forces are precisely known, the novel one makes do with a very rough, affine form and a formally more precise approximate model of that system, and uses temporal observations of its desired vs. realized responses. Furthermore, it does not assume the lack of unknown perturbations caused either by internal friction and/or external disturbances. Its another advantage is that it needs the execution of the SVD as a relatively time-consuming operation on a grid of a rough system-model only one time, before the commencement of the control cycle within which it works only with simple computations. The simulation examples exemplify the superiority of the FPT/SVD-based control that otherwise has the deficiency that it can get out of the region of its convergence. Therefore its design and use needs preliminary simulation investigations. However, the simulations also exemplify that its convergence can be guaranteed for various practical purposes

Novel Design of a Model Reference Adaptive Controller for Soft Tissue Operations

Model Reference Adaptive Controllers (MRAC) have dual functionality: besides guaranteeing precise trajectory track- ing of the controlled system, they have to provide an “external control loop” with the illusion that it controls a physical system of prescribed dynamic properties, i.e., the “reference system”. The MRACs are designed traditionally by Lyapunov’s 2 nd method that is mathematically complicated, requiring strong skills from the designer. Adaptive controllers alternatively designed by the use of Robust Fixed Point Transformations (RFPT) operate according to Banach’s Fixed Point Theorem , and are normally simple iterative constructions that also have a standard variant for MRAC design. This controller assumes a single actuator that is driven adaptively. Master–Slave Systems form a distinct class of practical applications, in which two arms—the master and the slave—operate simultaneously. The movement of the master must be tracked precisely by the slave in spite of the quite different forces exerted by them. In the present paper, a soft tissue-cutting operation by a master–slave structure is simulated. The master arm has a simple torque–reference friction model, and is driven by the surgeon. The obtained master arm trajectory has to be precisely tracked by the electric DC motor driven slave system, which is in dynamic interaction with the actual tissue under operation. It is shown via simulations that the RFPT-based design can efficiently solve such tasks without considerable mathematical complexity

Evolutionary optimisation and real-time self-tuning active vibration control of a flexible beam system

Active vibration control has long been recognised as a solution for flexible beam structure to achieve sufficient vibration suppression. The flexible beam dynamic model is derived according to the Euler Bernoulli beam theory. The resonance frequencies of the beam are investigated analytically and the validity was experimentally verified. This thesis focuses on two main parts: proportional-integralderivative (PID) controller tuning methods based on evolutionary algorithms (EA) and real-time self-tuning control using iterative learning algorithm and poleplacement methods. Optimisation methods for determining the optimal values of proportional-integral-derivative (PID) controller parameters for active vibration control of a flexible beam system are presented. The main objective of tuning the PID controller is to obtain a fast and stable system using EA such as genetic algorithm (GA) and differential evolution (DE) algorithms. The PID controller is tuned offline based on the identified model obtained using experimental input-output data. Experimental results have shown that PID parameters tuned by EA outperformed conventional tuning method in term of better transient response. However, in term of vibration attenuation, the performance between DE, GA and Ziegler-Nichols (ZN) method produced about the same value. For real-time selftuning control, successful design and implementation has been accomplished. Two techniques, self-tuning using iterative learning algorithm and self-tuning poleplacement control were implemented to adapt the controller parameters to meet the desired performances. In self-tuning using iterative learning algorithm, its learning mechanism will automatically find new control parameters. Whereas the self tuning pole-placement control uses system identification in real time and then the control parameters are calculated online. It is observed that self-tuning using iterative learning algorithm does not require accurate model of the plant and control the vibration based on the reference error, but it is unable to maintain its transient performance due to the change of physical parameters. Meanwhile, self-tuning poleplacement controller has shown its ability to maintain its transient performance as it was designed based on the desired closed loop poles where the control system can track changes in the plant and disturbance characteristics at every sampling time. Overall results revealed the effectiveness of both control schemes in suppressing the unwanted vibration over conventional fixed gain controllers

Implementation of Iterative Learning Control on a Pneumatic Actuator.

Masters Degree. University of KwaZulu-Natal, Durban.Pneumatic systems play a pivotal role in many industrial applications, such as in petrochemical industries, steel manufacturing, car manufacturing and food industries. Besides industrial applications, pneumatic systems have also been used in many robotic systems. Nevertheless, a pneumatic system contains different nonlinear and uncertain behaviour due to gas compression, gas leakage, attenuation of the air in pipes and frictional forces in mechanical parts, which increase the system’s dynamic orders. Therefore, modelling a pneumatic system tends to be complicated and challenges the design of the controller for such a system. As a result, employing an effective control mechanism to precisely control a pneumatic system for achieving the required performance is essential. A desirable controller for a pneumatic system should be capable of learning the dynamics of the system and adjusting the control signal accordingly. In this study, a learning control scheme to overcome the highlighted nonlinearity problems is suggested. Many industrial processes are repetitive, and it is reasonable to make use of previously acquired data to improve a controller’s convergence and robustness. An Iterative Learning Control (ILC) algorithm uses information from previous repetitions to learn about the system’s dynamics. The ILC algorithm characteristics are beneficial in real-time control given its short time requirements for responding to input changes. Cylinder-piston actuators are the most common pneumatic systems, which translate the air pressure force into a linear mechanical motion. In industrial automation and robotics, linear pneumatic actuators have a wide range of applications, from load positioning to pneumatic muscles in robots. Therefore, the aim of this research is to study the performance of ILC techniques in position control of the rod in a pneumatic position-cylinder system. Based on theoretical analysis, the design of an ILC is discussed, showing that the controller can satisfactorily overcome nonlinearities and uncertainties in the system without needing any prior knowledge of the system’s model. The controller has been designed in such a way to even work on non-iterative processes. The performance of the ILC-controlled system is compared with a well-tuned PID controller, showing a faster and more accurate response

Flight desk control demonstrator

The aim of a control system is to obtain a desired output response according to an input command. This can be achieved by knowing a model of the system with an open-loop control. However, an accurate model can be difficult to obtain. With a closed-loop control system, the controller determines the input signal of the process by using the measurement of the output. The most used method in the industry world involves PID correction. The concept of feedback control and the choice of the three gains (Proportional, Integrator, Derivative) for a simple PID controller can be quite hard for students to conceptualize and understand their effectiveness. The aim of this project is to develop a simple feedback system for aerospace students to understand the nature of feedback control, the choice and the influence of the PID terms. The system consists of a demonstrator for the control of the pitch angle of a simple aerofoil by means of a regulated flap. This document focuses on the process to design a fully working demonstrator including the design of the demonstrator, its building and the programming of the GUI (Graphical User Interface). The first step is to create an aerodynamic model of the system. Once a reliable model is obtained, a structural layout is suggested, based on existing wind tunnel design. The wind tunnel design is critical because the geometry has a direct impact on the loads acting on the aerofoil and it must satisfy aerodynamic requirements. The wind tunnel must create favourable aerodynamic conditions to make an easier control of the aerofoil by its flap. Then, the demonstrator is built using laser cutting and 3D printing. The PID controller is implemented into an Arduino board programmed in C++ connected via Bluetooth to the GUI on a computer programmed in JAVA. It is possible to plot and save the output of the demonstrator as well as send new settings to the controller. The demonstrator will be assessed, and several PID settings are suggested

Saturable absorption measurement of platinum as saturable absorber by using twin detector method based on mode-locked fiber laser

This paper illustrates the absorption measurement of Pt as saturable absorber (SA) by using mode-locked fiber laser system. The SA is fabricated by depositing 10 nm of Pt on the fiber ferrules using sputtering method. The absorption measurement of Pt is characterised by employing a balanced twin detector method based on mode-locked fiber laser with central wavelength of 1532.25 nm, repetition rate of 2.833 MHz and pulse duration of 34.3 ns. The Pt-SA produce modulation depth of 21.9% and saturation intensity of 21.6 MW cm-2