Turning Motion Control Design of a Two-Wheeled Inverted Pendulum Using Curvature Tracking and Optimal Control Theory

Zhou, Yusheng; Wang, Zaihua; Chung, Kwok Wai

doi:10.1007/s10957-019-01472-4

Cited by 18 publications

(13 citation statements)

References 29 publications

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“…Method in [34] Method in [35]  -shape Fish-shape S-shape We also used the swept error area standard (SEA) [29] to evaluate the proposed method and the traditional methods [34,35] quantitatively. The SEA standard measures the difference between the generated and the reference trajectories by their included area (Figure 9).…”

Section: Proposed Methodsmentioning

confidence: 99%

“…A • is the area of the tetragon enclosed by the four adjacent points along the trajectories. The SEA results by the proposed method and the approaches in [34,35] can be seen in Table 1. From the results, we can see that the proposed method can better achieve the capacity of path following; i.e., the error between the generated trajectory by the learned controller and the reference trajectory is smaller.…”

Section: Proposed Methodsmentioning

confidence: 99%

“…The results by the proposed method and two traditional control methods [34,35] are shown in Figure 8. It can be seen that the proposed learning method can smoothly follow the reference trajectory and finally converge to the target position.…”

Section: Demonstrationsmentioning

confidence: 99%

“…Figure 8. The results by the proposed method and the methods in[34,35]. The upper row shows the general trajectory shape of the path following.…”

mentioning

confidence: 99%

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A Wheeled Inverted Pendulum Learning Stable and Accurate Control from Demonstrations

Jin

2019

Applied Sciences

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In order to enable robots to be more intelligent and flexible, one way is to let robots learn human control strategy from demonstrations. It is a useful methodology, in contrast to traditional preprograming methods, in which robots are required to show generalizing capacity in similar scenarios. In this study, we apply learning from demonstrations on a wheeled, inverted pendulum, which realizes the balance controlling and trajectory following simultaneously. The learning model is able to map the robot position and pose to the wheel speeds, such that the robot regulated by the learned model can move in a desired trajectory and finally stop at a target position. Experiments were undertaken to validate the proposed method by testing its capacity of path following and balance guaranteeing.

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Section: Proposed Methodsmentioning

confidence: 99%

Section: Proposed Methodsmentioning

confidence: 99%

Section: Demonstrationsmentioning

confidence: 99%

“…Figure 8. The results by the proposed method and the methods in[34,35]. The upper row shows the general trajectory shape of the path following.…”

mentioning

confidence: 99%

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A Wheeled Inverted Pendulum Learning Stable and Accurate Control from Demonstrations

Jin

2019

Applied Sciences

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“…Most conventional robotic wheelchairs contain two active driving wheels and two passive casters [4]. Though casters enhance the stability of the wheelchair, they have a negative effect on its mobility [5][6][7]. To solve this problem, caster-free two-wheeled robotic wheelchair equipped with an active stability controller was proposed [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

An Approach on Velocity and Stability Control of a Two-Wheeled Robotic Wheelchair

2020

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Conventional robotic wheelchairs (three or four-wheeled) which are statically stable are poor in mobility. Though a two-wheeled robotic wheelchair has better mobility, it is not statically stable and needs an active stability controller. In addition to mobility and stability, velocity control is also important for the operation of a wheelchair. Conventional stability and velocity controllers rely on the motion of the wheels and require high driving torque and power. In this paper, this problem is tackled by adding a compact pendulum-like movable mechanism whose main function is for stability control. Its motion and those of the wheels are controlled through a quasi-sliding mode control approach to achieve a simultaneous velocity and stability control with much less driving torque and power. Simulation results are presented to show the effectiveness of the proposed controller.

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Adaptive Neural Delay Feedback Control of a Typical Robot on a Slope

Ji,

Sun,

Pan

et al. 2024

Optim Control Appl Methods

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In this article, an adaptive neural delay feedback control strategy is proposed for the motion control of a two‐wheel self‐balancing robot (TWSBR) on a slope with an input delay. Based on the Lagrange equation, the dynamic model of the robot is derived. Given a target trajectory vector, the corresponding error system is obtained. An input delay and uncertainties are considered. First, the system with an input delay is transformed into a delay‐free one. Second, a quadratic performance optimization criterion is defined, and a linear quadratic regulator (LQR) controller is designed to minimize the error between the system's state vector and the target vector. Thirdly, an integral sliding mode controller is added to the LQR controller to enhance the system's robustness. To reduce the “chattering” phenomenon, an adaptive neural delay feedback control scheme is developed based on the adaptive learning of the uncertainties' upper bound by a radial basis function neural network (RBFNN). It is demonstrated that a relaxation process exists at the beginning of the upslope motion. As the input delay increases, the swing range of the center of gravity of the pendulum expands. The angle can converge to the steady state more quickly, but the relaxation time is still 0.031 s which has nothing to do with the input delay. An example of the back‐and‐forth motion of a TWSBR on a slope can verify an excellent agreement between theoretical analysis and numerical results.

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Turning Motion Control Design of a Two-Wheeled Inverted Pendulum Using Curvature Tracking and Optimal Control Theory

Cited by 18 publications

References 29 publications

A Wheeled Inverted Pendulum Learning Stable and Accurate Control from Demonstrations

A Wheeled Inverted Pendulum Learning Stable and Accurate Control from Demonstrations

An Approach on Velocity and Stability Control of a Two-Wheeled Robotic Wheelchair

Adaptive Neural Delay Feedback Control of a Typical Robot on a Slope

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