Luo Hong Yu

Bio: Luo Hong Yu is an academic researcher. The author has contributed to research in topics: Open-loop controller & Inverted pendulum. The author has an hindex of 1, co-authored 1 publications receiving 14 citations.

An Inverted Pendulum Fuzzy Controller Design and Simulation

Abstract: Inverted pendulum poor stability, such as large overshoot problem, a fuzzy controller that can adjust the controller output in real time based on the error and error rate of change, experiment and simulation results show that the controller has good control characteristics and robustness, in addition, the controller is simple structure, high reliability, adaptability, better realization of an inverted pendulum stabilization function.

Control System in Open-Source FPGA for a Self-Balancing Robot

Abstract: Computing in technological applications is typically performed with software running on general-purpose microprocessors, such as the Computer Processing Unit (CPU), or specific ones, like the Graphical Processing Unit (GPU). Application-Specific Integrated Circuits (ASICs) are an interesting option when speed and reliability are required, but development costs are usually high. Field-Programmable Gate Arrays (FPGA) combine the flexibility of software with the high-speed operation of hardware, and can keep costs low. The dominant FPGA infrastructure is proprietary, but open tools have greatly improved and are a growing trend, from which robotics can benefit. This paper presents a robotics application that was fully developed using open FPGA tools. An inverted pendulum robot was designed, built, and programmed using open FPGA tools, such as IceStudio and the IceZum Alhambra board, which integrates the iCE40HX4K-TQ144 from Lattice. The perception from an inertial sensor is used in a PD control algorithm that commands two DC motors. All the modules were synthesized in an FPGA as a proof of concept. Its experimental validation shows good behavior and performance.

A Study on the Interpretability of a Fuzzy System to Control an Inverted Pendulum

Abstract: Fuzzy systems mimic human reasoning and provide solutions to problems under uncertainty via ‘computing with words’. This particular strength of fuzzy systems is often discarded in some real world applications where the fuzzy sets are designed for control problems or created through training using historical data. This study explores the interpretability of fuzzy systems by generating ‘meaningful’ fuzzy sets using a dictionary constructed by humans and fuzzy transfer learning. The inverted pendulum control problem is used as a case study. The empirical results show that intepretability of a fuzzy system is achievable even for this problem at the expense of a ‘slightly’ reduced performance.

Linear quadratic regulator and pole placement for stabilizing a cart inverted pendulum system

Abstract: The system of a cart inverted pendulum has many problems such as nonlinearity, complexity, unstable, and underactuated system. It makes this system be a benchmark for testing many control algorithm. This paper presents a comparison between 2 conventional control methods consist of a linear quadratic regulator (LQR) and pole placement. The comparison indicated by the most optimal steps and results in the system performance that obtained from each method for stabilizing a cart inverted pendulum system. A mathematical model of DC motor and mechanical transmission are included in a mathematical model to minimize the realtime implementation problem. From the simulation, the obtained system performance shows that each method has its advantages, and the desired pendulum angle and cart position reached.

Dynamic modeling and simulation for virtual evaluation of inverted wheeled robot controllers

Abstract: This paper develops a mathematical model of an inverted wheeled robot and uses it to simulate and animate the robot dynamics The robot is modeled as a three-body system consisting of a pendulum and two wheels where the Newtonian mechanics is employed to derive the dynamical equations The proposed model, in its current configuration, is designed to simulate and animate the controlled robot for forming a virtual controller-testing setup The open-loop system is simulated by solving the nonlinear dynamic equations recursively within an animation loop by using the Runge-Kutta 4 (RK4) method The nonlinear model is linearized for designing a PID controller to stabilize the closed-loop system of the robot The animation process is conducted by creating two graphical objects that resemble the wheel and pendulum in a graphical user interface window The keyboard arrows are used to interactively input the horizontal motion of the robot cart to the animation process where there is also an option to switch the controller off Simulation results are provided for both the open-loop and closed-loop cases to illustrate the effectiveness of the results

A Comparative Study of Controllers for QUANSER QUBE Servo 2 Rotary Inverted Pendulum System

Abstract: Inverted pendulum is an inherently unstable system which is extensively used for experimental analysis and studies. It is a nonlinear system with its centre of gravity above the pivot point; owing to this, the system is difficult to control; and controller design for balancing the pendulum is quite challenging. The work deals with modelling and designing of various controllers for QUANSER QUBE Servo 2 Rotary Pendulum system developed by National Instruments and comparison of their performances in balancing it in the upright position. The designed controllers include the conventional PID controller, linear quadratic regulator (LQR), full-state feedback controller and cascade PID controller. From the simulation results, it is found that the cascaded PID and LQR controllers provide better response of the system by balancing the pendulum with least settling time.