Swing-up Dan Stabilisasi Pada Sistem Pendulum Kereta Menggunakan Metode Fuzzy Dan Linear Quadratic Regulator

Sistem Pendulum Kereta merupakan sistem nonlinear dan tidak stabil yang sering digunakan untuk menguji metode-metode kontrol. Makalah ini membahas desain sistem kontrol swing-up menggunakan Fuzzy Swing-up Controller (FSC) model Mamdani dimana variabel yang dikontrol adalah sudut batang pendulum dan kecepatan sudut batang pendulum. Selain itu, juga memperhitungkan batasan panjang rel dan sinyal kontrol. Untuk stabilisasi batang pendulum pada posisi 0 radian diselesaikan menggunakan Linear Quadratic Regulator (LQR), disusun dari model nonlinear Sistem Pendulum Kereta yang direpresentasikan dalam model fuzzy Takagi-Sugeno (T-S) untuk beberapa titik kerja. Skema kontrol keseluruhan disusun dengan konsep Parallel Distributed Compensation (PDC) yang merupakan kontroler state-feedback yang dinamis. Hasil simulasi dan implementasi menunjukkan bahwa Sistem Pendulum Kereta dapat melakukan swing-up dan mempertahankan batang pendulum pada posisi terbalik

Swing-up dan Stabilisasi pada Sistem Pendulum Kereta menggunakan Metode Fuzzy dan Linear Quadratic Regulator

Sistem Pendulum Kereta merupakan sistem nonlinear dan tidak stabil yang sering digunakan untuk menguji metode-metode kontrol. Makalah ini membahas desain sistem kontrol swing-up menggunakan Fuzzy Swing-up Controller (FSC) model Mamdani dimana variabel yang dikontrol adalah sudut batang pendulum dan kecepatan sudut batang pendulum. Selain itu, juga memperhitungkan batasan panjang rel dan sinyal kontrol. Untuk stabilisasi batang pendulum pada posisi 0 radian diselesaikan menggunakan Linear Quadratic Regulator (LQR), disusun dari model nonlinear Sistem Pendulum Kereta yang direpresentasikan dalam model fuzzy Takagi-Sugeno (T-S) untuk beberapa titik kerja. Skema kontrol keseluruhan disusun dengan konsep Parallel Distributed Compensation (PDC) yang merupakan kontroler state-feedback yang dinamis. Hasil simulasi dan implementasi menunjukkan bahwa Sistem Pendulum Kereta dapat melakukan swing-up dan mempertahankan batang pendulum pada posisi terbalik

Desarrollo de un módulo didáctico para control angular de un péndulo suspendido

Este trabajo presenta el desarrollo de un módulo didáctico con la implementación de un controlador proporcional – integrativo (PI) en un péndulo suspendido, donde se regula la velocidad de la hélice de forma se obtenga el ángulo deseado y se mantenga estable ante la presencia de perturbaciones adicionadas al péndulo. Además el módulo didáctico, le fue desarrollado un sistema de adquisición de datos con un microcontrolador atmega atmel 328 en comunicación serial con la plataforma matlab® simulink®, la cual permite un monitoreamiento en línea en tiempo real del comportamiento del péndulo para sus posteriores análisis y prácticas a los estudiantes en el área de teoría control e ingeniería. El comportamiento del sistema fue satisfactorio, se alcanzaron respuestas transitorias no mayores a cuatro segundos por parte del controlador PI para estabilizar el sistema ante la presencia de perturbaciones o cambios tipo escalonado en su setpoint.Palabras clave: péndulo, controlador PI.

IMPACT ANALYSIS OF MICRO-JET COOLING FOR STRESS CONCENTRATION IN A CRANE BUMPER DURING A COLLISION

In the structure of crane bumpers, there is a need to join various types of steel. Usually, low-alloy steel structures are used for this purpose, which can be represented by S355J2 steel. The tensile strength of S355J2 low-alloy steel is slightly below 600 MPa, and the tensile strength of S355J2 steel is at the high level of 200 J at ambient temperature. The impact strength of this steel in negative temperatures is also good at over 47 J at -60 °C, so it meets the 6th class of impact toughness. Welding structures, after classic gas metal arc welding (GMAW) processes, meet only the second impact toughness class. An improved GMAW process was used by micro-jet cooling application to raise the mechanical properties of the joints. The microstructure and main properties of the joints were carefully analyzed. The influence of using the new suggested welding process on the various properties of the welds is presented (UTS – ultimate tensile strength, YS – yield strength, Poisson ratio, elongation, Young’s modulus). Then, the effects of tests for use in crane bumper construction were checked by using a hybrid finite element method (FEM) analysis

Robust nonlinear controller based on set propagation

Bibliography: leaves 74-[76.]A novel control method, based on interval analysis, that optimises the control surface (or u-surface) for sampled systems with output disturbances is demonstrated on a driven pendulum with actuator constraints. The fitness function to be maximized is the probability of each state of the system being controlled to the setpoint without being perturbed to regions that are more iterations away from the setpoint. The u-surface is designed by finding all the states that could go to the setpoint in an interval and optimising these states. This process is repeated (backwards in time) by optimising states that go to the previously optimised states until no more states that have not been optimised are found. The proposed control method has been applied to the problem of swinging up a driven pendulum from rest to the inverted position with constraints on the torque of the motor. This method is computationally intensive and time constraints limit its current application to systems of low order

Implementation and Control of an Inverted Pendulum on a Cart

An Inverted Pendulum on a Cart is a common system often used as a benchmark problem for control systems. The system consists of a cart that can move in one direction on the horizontal plane and a pendulum attached to the cart through a hinge point. The pendulum can rotate 360° on the plane made up of the vertical direction and the direction the cart can move. The system is controlled by applying a force to the cart, to make it move. This thesis consists of two goals. The first goal is to build a lab model of the Inverted Pendulum on a Cart system. The second goal is to create a controller that can swing the pendulum from a pendulum down position to a pendulum up position, and balance it in this position. The lab model is built using a track that the cart can move along, a stepper motor for applying force to the cart and a microcontroller for controlling the system. The pendulum angle and the cart position are measured using incremental encoders. A Mathematical model of the system have been derived. This forms the basis for the design of the controller and is also used for simulating and testing the system and controller in MATLAB/Simulink before it is implemented on the real system. The controller consists of three parts. An extended Kalman filter is implemented to estimate the non-measurable state. An energy-based controller is used to swing the pendulum from the down position to the up position. This controller regulates the energy in the pendulum to be close to the energy the pendulum should have when it is balanced in the upright position. When the pendulum is close to the upright position the controller will switch to a linear quadratic regulator to balance the pendulum. This controller is based on a linearized version of the mathematical system model. The lab model and the controllers have been successfully built and implemented

Stability analysis of non-holonomic inverted pendulum system

The inverted pendulum is doubtlessly one of the most famous control problems found in most control text books and laboratories worldwide. This popularity comes from the fact that the inverted pendulum exhibits nonlinear, unstable and non-minimum phase dynamics. The basic control objective of the study is to design a controller in order to maintain the upright position of the pendulum while also controlling the position of the cart. In our study we explored the relationship that the tuning parameters (weight on the position of the car and the angle that the pendulum makes with the vertical) of a classical inverted pendulum on a cart has on the pole placement and hence on the stability of the system. We then present a family of curves showing the local root-locus and develop relationships between the weight changes and the system performance. We describe how these locus trends provide insight that is useful to the control designer during the effort to optimize the system performance. Finally, we use our general results to design an effective feedback controller for a new system with a longer pendulum, and present experiment results that demonstrate the effectiveness of our analysis. We then designed a simulation-based study to determine the stability characteristics of a holonomic inverted pendulum system. Here we decoupled the system using geometry as two independent one dimensional inverted pendulum and observed that the system can be stabilized using this method successfully with and without noise added to the system. Next, we designed a linear system for the highly complex inverted pendulum on a non-holonomic cart system. Overall, the findings will provide valuable input to the controller designers for a wide range of applications including tuning of the controller parameters to design of a linear controller for nonlinear systems

Visual Feedback Stabilisation of a Cart Inverted Pendulum A

Vision-based object stabilisation is an exciting and challenging area of research, and is one that promises great technical advancements in the field of computer vision. As humans, we are capable of a tremendous array of skilful interactions, particularly when balancing unstable objects that have complex, non-linear dynamics. These complex dynamics impose a difficult control problem, since the object must be stabilised through collaboration between applied forces and vision-based feedback. To coordinate our actions and facilitate delivery of precise amounts of muscle torque, we primarily use our eyes to provide feedback in a closed-loop control scheme. This ability to control an inherently unstable object by vision-only feedback demonstrates an exceptionally high degree of voluntary motor skill. Despite the pervasiveness of vision-based stabilisation in humans and animals, relatively little is known about the neural strategies used to achieve this task. In the last few decades, with advancements in technology, we have tried to impart the skill of vision-based object stabilisation to machines, with varying degrees of success. Within the context of this research, we continue this pursuit by employing the classic Cart Inverted Pendulum; an inherently unstable, non-linear system to investigate dynamic object balancing by vision-only feedback. The Inverted Pendulum is considered to be one of the most fundamental benchmark systems in control theory; as a platform, it provides us with a strong, well established test bed for this research. We seek to discover what strategies are used to stabilise the Cart Inverted Pendulum, and to determine if these strategies can be deployed in Real-Time, using cost-effective solutions. The thesis confronts, and overcomes the problems imposed by low-bandwidth USB cameras; such as poor colour-balance, image noise and low frame rates etc., to successfully achieve vision-based stabilisation. The thesis presents a comprehensive vision-based control system that is capable of balancing an inverted pendulum with a resting oscillation of approximately ±1º. We employ a novel, segment-based location and tracking algorithm, which was found to have excellent noise immunity and enhanced robustness. We successfully demonstrate the resilience of the tracking and pose estimation algorithm against visual disturbances in Real-Time, and with minimal recovery delay. The algorithm was evaluated against peer reviewed research; in terms of processing time, amplitude of oscillation, measurement accuracy and resting oscillation. For each key performance indicator, our system was found to be superior in many cases to that found in the literature. The thesis also delivers a complete test software environment, where vision-based algorithms can be evaluated. This environment includes a flexible tracking model generator to allow customisation of visual markers used by the system. We conclude by successfully performing off-line optimization of our method by means of Artificial Neural Networks, to achieve a significant improvement in angle measurement accuracy.Goodrich Engine Control Systems and Balfour Beatty Rail Technologie