Wheeled Inverted Pendulum Vehicle Research Articles

Optimal Trajectory Planning Method for the Navigation of WIP Vehicles in Unknown Environments: Theory and Experiment.

Navigation of underactuated wheeled inverted pendulum (WIP) vehicles in unknown environments is still facing great difficulties, especially when the optimal motion is required. This article proposes an optimal trajectory planning method for the navigation of WIP vehicles in unknown environments, where various performance demands, such as security, smoothness, efficiency, etc., are all considered. First, a map-building algorithm based on the improved Rao-Blackwellized particle filter is applied for the WIP vehicle to construct the environmental map. Then, a multiobjective optimization using the genetic algorithm is performed to find an optimized path between the given start and target point with path length, path curvature, and safe distance being taken into consideration simultaneously. Moreover, on the basis of kinematical and dynamical analysis, velocity, and acceleration constraints are parameterized with a path parameter, and the minimum-time trajectory along the optimized path is further planned with a sequence of maximum acceleration and deceleration trajectories. Finally, a WIP vehicle platform based on the robot operating system is designed, and related experiments in a real obstacle environment are conducted to validate the feasibility of the proposed method.

Time-Optimal Point Stabilization Control for WIP Vehicles Using Quasi-Convex Optimization and B-Spline Adaptive Interpolation Techniques

This paper addresses a time-optimal point stabilization control for inherent unstable wheeled inverted pendulum (WIP) vehicles using quasi-convex optimization and B-spline adaptive interpolation techniques. First, to handle the difficulty caused by the inherent unstable characteristic, a state feedback control law is introduced to the state-space model deduced with the kinematic coupling relationship between the longitudinal motion and tilt angle of vehicle body. Then, by system discretization, a standard quasi-convex optimization problem is formulated to plan a time-optimal trajectory with various constraints being taken into account, and the optimization problem can be solved by a bisection method combined with solving a series of convex feasibility problems. Next, to obtain the analytic expression of the discrete optimal trajectory, a B-spline interpolation algorithm with adaptive curve refinement is presented based on feature points recognition. Furthermore, as the time-optimal trajectories with analytic expressions, including displacement, velocity, and acceleration trajectories, have been obtained, a proportional-integral-derivative (PID) tracking controller is applied to control the vehicle to track the optimal trajectories and, thus, the time-optimal point stabilization control for the WIP vehicle can be realized. Finally, simulation results of a numerical example is presented to validate the feasibility and effectiveness of the proposed method.

Point Stabilization Control Method for WIP Vehicles Based on Motion Planning

Point stabilization control of wheeled inverted pendulum (WIP) vehicles remains a challenge because of the existing nonholonomic and underactuated characteristics. This paper proposes a point stabilization control method for the WIP vehicle based on motion planning, where a point-to-point motion is achieved by performing pivot steering and longitudinal motion successively to avoid the nonholonomic constraint. Specifically, to handle the underactuated problem, a kinematic coupling-based longitudinal trajectory planning approach is presented, by which both precise longitudinal movement and stability of vehicle body can be guaranteed. Moreover, a mathematical model of parameters optimization problem is deduced with strict analysis, and then the particle swarm optimization algorithm is used to obtain the appropriate trajectory parameters, which ensures the good performance of the trajectory planning method. On this basis, the point stabilization of the WIP vehicle can be effectively realized through a commonly used proportional-integral-derivative control approach. Numerical simulation and experimental study are both conducted to demonstrate the feasibility and effectiveness of the proposed method.

Composite following control for wheeled inverted pendulum vehicles based on human-robot interaction

Composite following control for wheeled inverted pendulum vehicles based on human-robot interaction

A trajectory planning and tracking control approach for obstacle avoidance of wheeled inverted pendulum vehicles

ABSTRACT This paper investigates a trajectory planning and tracking control scheme to implement the autonomous obstacle avoidance for wheeled inverted pendulum (WIP) vehicles, which enable the mobile platform to avoid obstacles rapidly and stabilise the vehicle body simultaneously. In the first place, an obstacle avoidance trajectory planning method suitable for the WIP vehicle is proposed, which, in particular, is capable of planning an obstacle avoidance trajectory with the merits of continuous curvature and approximately zero longitudinal acceleration in vehicle body-fixed frame system. Then, aiming the feature of the each subsystem, a nonsingular terminal sliding mode control and a nested saturation approach are employed to construct the trajectory tracking algorithm for fully actuated steering subsystem and underactuated longitudinal subsystem of the WIP vehicle, respectively. Besides, the closed-loop system's stability and asymptotical convergence of tracking error are proven in the sense of Lyapunov stability theory. In the end, numerical simulations are performed to demonstrate the feasibility and effectiveness of the proposed scheme for obstacle avoidance of WIP vehicles.

Constrained Adaptive Robust Trajectory Tracking for WIP Vehicles Using Model Predictive Control and Extended State Observer

This paper is concerned with a model predictive control (MPC) technique together with an adaptive robust scheme for the trajectory tracking of a wheeled inverted pendulum vehicle in the absence of platform velocity information, in addition to taking dynamic uncertainty and external disturbance into consideration. Specifically, to deal with velocity information loss and dynamic uncertainty, an extended state observer is introduced to evaluate the velocity vectors and model dynamics, where the uniformly ultimately bounded property of observer system can be guaranteed by using the Lyapunov stability theorem. With these observations, MPC is employed for the underactuated longitudinal subsystem to achieve longitudinal velocity tracking, as well as holding the pendulum-like vehicle body stability, and in particular taking the state and input saturation into account; at the same time, an adaptive robust controller is constructed for the rotational subsystem to realize the rotational velocity tracking, in which the adaptive laws can enhance the vehicle adaptability in diverse environment. In addition, a saturated trajectory generator with closed-loop characteristic is introduced so as to properly handle the velocity limitation and nonholonomic constraint simultaneously. The simulation results validate that the control system is robust against the external disturbance and model uncertainty, thereby demonstrating the effectiveness and robustness of the proposed control strategy.

An Efficient Model Predictive Control for Trajectory Tracking of Wheeled Inverted Pendulum Vehicles with Various Physical Constraints

This study presents a robust model predictive control (MPC) strategy to handle the trajectory tracking problem for a underactuated two-wheeled inverted pendulum (WIP) vehicle, in addition to taking various physical constraints into account. To begin with, a saturated trajectory generator is proposed to produce the desired velocities by which all posture tracking errors converge to the compact sets as well as the saturation of velocities being guaranteed. In addition, a MPC approach is put up forward after the approximate feedback linearization is performed to decrease the burden of computation and increase the realtime performance of the control system. Particularly, various physical constraints can be readily assured by the presented MPC method although the equilibrium of WIP vehicle is unstable. Meanwhile, to validate the robustness and availability of the proposed approach, initial errors, pulse disturbance and random noise are introduced to test the control performance of the closed-loop system in the simulation environment. The results from both theoretical analysis and simulation show that the proposed control strategy are effective and feasible for practical implementation.

Zero dynamics stabilisation and adaptive trajectory tracking for WIP vehicles through feedback linearisation and LQR technique

ABSTRACTThis paper presents a composite control strategy integrating adaptive sliding-mode control and the linear quadratic regulator (LQR) technology for a wheeled inverted pendulum (WIP) vehicle system. The system can be partitioned into an actuated rotational subsystem and an underactuated longitudinal subsystem based on the different control input in the mathematical model. In particular, the instability analysis of zero dynamic for the underactuated longitudinal subsystem is investigated in detail using the feedback linearisation technology. Then, an adaptive sliding-mode control is designed for the trajectory tracking, where an adaptive algorithm is developed to handle with the parameter uncertainties. In addition, the LQR technique is employed to guarantee zero dynamics stability so as to achieve simultaneously the vehicle body stabilisation at the upright position. Simulation results show the good performance and strong robustness of the proposed control schemes.

Development and Implementation of a Wheeled Inverted Pendulum Vehicle Using Adaptive Neural Control with Extreme Learning Machines

A novel neural control on basis of extreme learning machines (ELMs) is proposed to control wheeled inverted pendulum vehicle, which is a human transportation platform mounted on two coaxial wheels. A dynamic self-balancing control scheme for such vehicle is constructed which depends on the single-hidden layer feedforward network approximation capability of combing ELMs to capture vehicle dynamics. It is superior to conventional intelligent control by using extreme learning machines since the proposed neural control adjusts the output weight parameters online on basis of the Lyapunov synthesis approach. Experimental results are provided to demonstrate that the vehicle can maintain upright posture stably with the external disturbances based on the proposed control scheme.

Indirect adaptive fuzzy control for a nonholonomic/underactuated wheeled inverted pendulum vehicle based on a data-driven trajectory planner

In this study, we investigate an error data-based trajectory planner and indirect adaptive fuzzy control for a class of wheeled inverted pendulum vehicle systems. Based on the error dynamics, the closed-loop trajectory planner can generate the desired velocity values. Using the virtual acceleration input for the tilt angle subsystem, composite control for the rotational and longitudinal subsystems can be constructed via indirect adaptive fuzzy and sliding mode control approaches to achieve simultaneous velocity tracking and tilt angle stabilization. We rigorously prove the system stability and convergence of the tracking error signals using the Lyapunov theory and LaSalle's invariance theorem. The results of our numerical simulations demonstrated the efficiency of the proposed control strategies and the implementations of the algorithms.

Zero-dynamics-based adaptive sliding mode control for a wheeled inverted pendulum with parametric friction and uncertain dynamics compensation

In this paper, we propose a novel control methodology based on zero-dynamics theory for a class of wheeled inverted pendulum (WIP) vehicles, which is efficient even in the presence of uncertain system frictions and dynamics parameters. The control schemes are elegantly constructed so that the WIP vehicle can successfully implement stabilizing of the posture (longitudinal and rotational movements), as well as hold the upright position of the vehicle body (tilt angle stability), only by the two control inputs with the aid of the design approach of zero-dynamics. In particular, the dynamics uncertainties, especially the friction effects, would deteriorate the control performance severely in practice. Therefore, we employ adaptive laws for the design parameters of zero-dynamics subsystem and uncertain coefficients of parametric frictions and dynamics. Consequently, the estimated frictions and dynamics are compensated through feedforward to obtain better control performance. To enhance the robustness of the system against parameter variations and external disturbances, sliding mode control techniques are applied to derive the specific algorithms, and then the closed-loop systems are proven to be globally asymptotically stable by Lyapunov techniques and LaSalle’s invariance theorem. In addition, simulation studies have been performed to demonstrate the feasibility and effectiveness of the proposed strategies, which illuminate the promising practical application potentiality of the designed WIP vehicle control system.

Dynamic balance and motion control for wheeled inverted pendulum vehicle via hierarchical sliding mode approach

Dynamic balance and motion control for a class of underactuated wheeled inverted pendulum vehicles that are inherent unstable are investigated in this study. The control objective is to stable the posture of the vehicle platform (longitudinal and rotational position/velocity) as well as hold upright position of the pendulum (tilt angle stability), only with two control inputs generated by the left and right motors. The overall dynamic system is separated into two decoupled subsystems: one is a one-dimensional fully actuated subsystem while the other is a two-dimensional underactuated subsystem. A new hierarchical sliding mode control methodology is first developed to resolve the underactuated problem of this kind of unstable vehicles. The first layer sliding mode surfaces are established upon tilt angle and longitudinal displacement of the vehicle body, respectively; while the second layer sliding mode surface is constructed by the first layer sliding mode surfaces. Consequently, the total control law is deduced, and then the asymptotic stabilities for the overall closed-loop control system are addressed via Lyapunov stability theorem and Barbalat’s Lemma. Numerical simulations illustrate the effectiveness of the proposed control approaches and methodologies.

2P1-F02 坂道での乗り降りを考慮した搭乗型倒立振子の制御方法の開発

2P1-F02 坂道での乗り降りを考慮した搭乗型倒立振子の制御方法の開発