Adaptive Neuro-Fuzzy Control Approach for a Single Inverted Pendulum System

The inverted pendulum is an under-actuated and nonlinear system, which is also unstable. It is a single-input double-output system, where only one output is directly actuated. This paper investigates a single intelligent control system using an adaptive neuro-fuzzy inference system (ANFIS) to stabilize the inverted pendulum system while tracking the desired position. The non-linear inverted pendulum system was modelled and built using MATLAB Simulink. An adaptive neuro-fuzzy logic controller was implemented and its performance was compared with a Sugeno-fuzzy inference system in both simulation and real experiment. The ANFIS controller could reach its desired new destination in 1.5 s and could stabilize the entire system in 2.2 s in the simulation, while in the experiment it took 1.7 s to reach stability. Results from the simulation and experiment showed that ANFIS had better performance compared to the Sugeno-fuzzy controller as it provided faster and smoother response and much less steady-state error

Design and Implementation of a Furuta Pendulum Device for Benchmarking Non-Linear Control Methods

Furuta pendulum is an academic benchmark example for evaluating non-linear control algorithms. The main aim of this dissertation is to study this physical system, showing its dynamic model and several strategies for its control. An assortment of swing-up and upright control approaches is reported with its design and simulations. Besides, this document describes the project development which is being done at the FabLab of the Obuda University, whose objective is to design and manufacture a demonstration device that is capable to test and display various control strategies. Requirements and specications of the design, used tools and future work are described. The dissertation is structured in eight different chapters: (1) History of the Furuta pendulum, describing the origin of this system; (2) State-of-the-art in non-linear control, giving a background for the different control strategies; (3) Dynamic model of the Furuta pendulum; (4) Swing-up by energy control, based on the work of Astrom and Furuta; (5) Stabilizing local control, via full state feedback; (6) Hybrid control, which sums up the previous approaches; (7) Development project, which describes the work realized in the FabLab and (8) Conclusion, discussing the knowledge extracted from the development of this thesis

A two-wheeled machine with a handling mechanism in two different directions

Despite the fact that there are various configurations of self-balanced two-wheeled machines (TWMs), the workspace of such systems is restricted by their current configurations and designs. In this work, the dynamic analysis of a novel configuration of TWMs is introduced that enables handling a payload attached to the intermediate body (IB) in two mutually perpendicular directions. This configuration will enlarge the workspace of the vehicle and increase its flexibility in material handling, objects assembly and similar industrial and service robot applications. The proposed configuration gains advantages of the design of serial arms while occupying a minimum space which is unique feature of TWMs. The proposed machine has five degrees of freedoms (DOFs) that can be useful for industrial applications such as pick and place, material handling and packaging. This machine will provide an advantage over other TWMs in terms of the wider workspace and the increased flexibility in service and industrial applications. Furthermore, the proposed design will add additional challenge of controlling the system to compensate for the change of the location of the COM due to performing tasks of handling in multiple directions

Modified PSO based PID Sliding Mode Control using Improved Reaching Law for Nonlinear systems

In this paper, a new model based nonlinear control technique, called PID (Proportional-Integral-Derivative) type sliding surface based sliding mode control is designed using improved reaching law. To improve the performance of the second order nonlinear differential equations with unknown parameters modified particle swarm intelligent optimization (MPSO) is used for the optimized parameters. This paper throws light on the sliding surface design, on the proposed power rate exponential reaching law, parameters optimization using modified particle swarm optimization and highlights the important features of adding an integral term in the sliding mode such as robustness and higher convergence, through extensive mathematical modeling. Siding mode control law is derived using Lyapunov stability approach and its asymptotic stability is proved mathematically and simulations showing its validity. MPSO PID-type Sliding mode control will stabilize the highly nonlinear systems, will compensate disturbances and uncertainty and reduces tracking errors. Simulations and experimental application is done on the non-linear systems and are presented to make a quantitative comparison.Comment: arXiv admin note: substantial text overlap with arXiv:2207.1112

Non-conventional control of the flexible pole-cart balancing problem

Emerging techniques of intelligent or learning control seem attractive for applications in manufacturing and robotics. It is however important to understand the capabilities of such control systems. In the past the inverted pendulum has been used as a test case. The thesis begins with an examination of whether the inverted pendulum or polecart balancing problem is a representative problem for experimentation for learning controllers for complex nonlinear systems. Results of previous research concerning the inverted pendulum problem are presented to show that this problem is not sufficiently testing. This thesis therefore concentrates on the control of the inverted pendulum with an additional degree of freedom as a testing demonstrator problem for learning control system experimentation. A flexible pole is used in place of a rigid one. The transverse displacement of the flexible pole adds a degree of freedom to the system. The dynamics of this new system are more complex as the system needs additional parameters to be defIned due to the pole's elastic deflection. This problem also has many of the signifIcant features associated with flexible robots with lightweight links as applied in manufacturing. Novel neural network and fuzzy control systems are presented that control such a system both in simulation and real time. A fuzzy-genetic approach is also demonstrated that allows the creation of fuzzy control systems without the use of extensive knowledge

Analyzing and Designing Control System for an Inverted Pendulum on a Cart

It is a collection of MATLAB functions and scripts, and SIMULINK models, useful for analyzing Inverted Pendulum System and designing Control System for it. Automatic control is a growing field of study in the field of Mechanical Engineering. This covers the proportional, integral and derivative (PID). The principal reason for its popularity is its nonlinear and unstable control. The reports begin with an outline of research into inverted pendulum design system and along with mathematical model formation. This will present introduction and review of the system. Here one dimensional inverted pendulum is analyzed for simulating in MATLAB environment. Control of Inverted Pendulum is a Control Engineering project based on the flight simulation of rocket or missile during the initial stages of flight. The aim of this study is to stabilize the Inverted Pendulum such that the position of the carriage on the track is controlled quickly and accurately so that the pendulum is always erected in its inverted position during such movements

Stabilizing control of two-wheeled wheelchair with movable payload using optimized interval type-2 fuzzy logic

The control schemes of a wheelchair having two wheels with movable payload utilizing the concept of a double-link inverted pendulum have been investigated in this article. The proposed wheelchair has been simulated using SimWise 4D software considering the most efficient parameters. These parameters are extracted using the spiral dynamic algorithm while being controlled with interval type-2 fuzzy logic controller (IT2FLC). The robustness and stability of the implemented controller are assessed under different situations including standing upright, forward motion and application of varying directions and magnitudes of outer disturbances to movable (up and down) system payload. It is shown that the two-wheeled wheelchair adopted by the newly introduced controller has achieved a 94% drop in torque for both Link1 and Link2 and more than 98% fall in distance travelled in comparison with fuzzy logic control type-1 (FLCT1) controller employed in an earlier design. The present study has further considered the increased nonlinearity and complexity of the additional moving payload. From the outcome of this study, it is obvious that the proposed IT2FLC-spiral dynamic algorithm demonstrates better performance than FLCT1 to manage the uncertainties and nonlinearities in case of a movable payload two-wheel wheelchair system