A Wheeled Inverted Pendulum Learning Stable and Accurate Control from Demonstrations

Jin, Shaokun; Ou, Yongsheng

doi:10.3390/app9245279

Cited by 5 publications

(3 citation statements)

References 31 publications

(41 reference statements)

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“…It is a type of artificial intelligence that allows the controller to make decisions based on a set of rules. The rules are based on the robot's position and tilt angle [23]. The controller then uses these rules to calculate the amount of speed that needs to be applied to the wheels in order to keep the robot balanced.…”

Section: Fuzzy Pd Controllermentioning

confidence: 99%

Study the Performance of Two-Wheeled Balancing Mobile Robot Using Fuzzy Pd Controller

Mohd Noor,

Mohd Halid,

Mahmod @Wahab

2023

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Nowadays, the research on a two-wheeled self-balancing robot is an active area of research especially in terms of design as well as control to continue the innovation applications of robots in the future. Most of the two-wheeled self-balancing robots are designed based on an inverted pendulum system for stability and maneuverability. The aim of this paper is to propose the fuzzy PD controller to control and maintain its balance on the two wheels. A sensor of the Inertial Measurement Unit (IMU) was used as an input to evaluate and obtain the position and orientation of the robot. The control algorithms for the robot also are designed to keep the pendulum upright. Then, the fuzzy PD concept was applied to correct the error between the desired set point and the actual tilt angle position to adjust the speed of the motor accordingly. The results obtained from this controller were capable of maintaining the balancing of the robot by using an experimental method of PID tuning. The prototype of the two-wheeled self-balancing robot was implemented with Arduino Uno and a fuzzy PD controller. However, the limitation of the project is the longer size and heavier weight of the robot are less stable, then a better controller is needed to balance the robot.

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Section: Fuzzy Pd Controllermentioning

confidence: 99%

Study the Performance of Two-Wheeled Balancing Mobile Robot Using Fuzzy Pd Controller

Mohd Noor,

Mohd Halid,

Mahmod @Wahab

2023

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“…Zhou et al [30] applied sliding mode control and an extended Kalman filter to enable a TWIP robot to track a reference position or velocity trajectory on uneven ground. Jin and Ou [31] developed a learning method for a TWIP robot to guarantee path-following and balance.…”

Section: Introductionmentioning

confidence: 99%

Decoupled Multi-Loop Robust Control for a Walk-Assistance Robot Employing a Two-Wheeled Inverted Pendulum

et al. 2021

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This paper develops a decoupled multi-loop control for a two-wheeled inverted pendulum (TWIP) robot that can assist user’s with walking. The TWIP robot is equipped with two wheels driven by electrical motors. We derive the system’s transfer function and design a robust loop-shaping controller to balance the system. The simulation and experimental results show that the TWIP system can be balanced but might experience velocity drifts because its balancing point is affected by model variations and disturbances. Therefore, we propose a multi-loop control layout consisting of a velocity loop and a position loop for the TWIP robot. The velocity loop can adjust the balancing point in real-time and regulate the forward velocity, while the position loop can achieve position tracking. For walking assistance, we design a decoupled control structure that transfers the linear and rotational motions of the robot to the commands of two parallel motors. We implement the designed controllers for simulation and experiments and show that the TWIP system employing the proposed decoupled multi-loop control can provide satisfactory responses when assisting with walking.

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“…There are a number of standard control techniques that exist in the control engineering area, which have been tested on an inverted pendulum model prior to their implementation on the real systems [4,[7][8][9][10][11]. For example, the design of an active stabilizing system for a single-track vehicle system was studied [12], and an intelligent control and balancing technique for a robotics system has been formulated [13]. A fuzzy controller has been suggested to solve the trajectory tracking problem of the inverted pendulum attached to a cart system [14], while a particle swarm optimization-based neural network controller has been designed for solving a real world unstable control challenge [15].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Response of an Inverted Pendulum System in Water under Parametric Excitations for Energy Harvesting: A Conceptual Approach

et al. 2020

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In this paper, we have investigated the dynamic response, vibration control technique, and upright stability of an inverted pendulum system in an underwater environment in view point of a conceptual future wave energy harvesting system. The pendulum system is subjected to a parametrically excited input (used as a water wave) at its pivot point in the vertical direction for stabilization purposes. For the first time, a mathematical model for investigating the underwater dynamic response of an inverted pendulum system has been developed, considering the effect of hydrodynamic forces (like the drag force and the buoyancy force) acting on the system. The mathematical model of the system has been derived by applying the standard Lagrange equation. To obtain the approximate solution of the system, the averaging technique has been utilized. An open loop parametric excitation technique has been applied to stabilize the pendulum system at its upright unstable equilibrium position. Both (like the lower and the upper) stability borders have been shown for the responses of both pendulum systems in vacuum and water (viscously damped). Furthermore, stability regions for both cases are clearly drawn and analyzed. The results are illustrated through numerical simulations. Numerical simulation results concluded that: (i) The application of the parametric excitation control method in this article successfully stabilizes the newly developed system model in an underwater environment, (ii) there is a significant increase in the excitation amplitude in the stability region for the system in water versus in vacuum, and (iii) the stability region for the system in vacuum is wider than that in water.

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A Wheeled Inverted Pendulum Learning Stable and Accurate Control from Demonstrations

Cited by 5 publications

References 31 publications

Study the Performance of Two-Wheeled Balancing Mobile Robot Using Fuzzy Pd Controller

Study the Performance of Two-Wheeled Balancing Mobile Robot Using Fuzzy Pd Controller

Decoupled Multi-Loop Robust Control for a Walk-Assistance Robot Employing a Two-Wheeled Inverted Pendulum

Dynamic Response of an Inverted Pendulum System in Water under Parametric Excitations for Energy Harvesting: A Conceptual Approach

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