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

Yue, Ming; An, Cong; Du, Yu; Sun, Jinwei

doi:10.1016/j.fss.2015.08.013

Cited by 51 publications

(31 citation statements)

References 41 publications

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“…The key of state feedback is to calculate the gain vector . In this section, the desired closed-loop poles are set to ] , (26) where is calculated by solving the Lyapunov equation + = − . The experiment results are shown in Figure 3 under the control law, which realizes not only stability control but also swing-up control.…”

Section: System Parameter Settings the Values Of The Parameters Inmentioning

confidence: 99%

“…On the other hand, the inverted system can be underactuated and nonholonomic systems. Yue et al used indirect adaptive fuzzy and sliding mode control approaches to achieve simultaneous velocity tracking and tilt angle 2 Journal of Control Science and Engineering stabilization for a nonholonomic and underactuated wheeled inverted pendulum vehicle [26]. Different from [26], some researchers focus on the study of the general classes of underactuated and nonholonomic systems.…”

Section: Introductionmentioning

confidence: 99%

“…Yue et al used indirect adaptive fuzzy and sliding mode control approaches to achieve simultaneous velocity tracking and tilt angle 2 Journal of Control Science and Engineering stabilization for a nonholonomic and underactuated wheeled inverted pendulum vehicle [26]. Different from [26], some researchers focus on the study of the general classes of underactuated and nonholonomic systems. For example, Mobayen proposed a new recursive terminal sliding mode strategy for tracking control of disturbed chained-form nonholonomic systems whose reference targets are allowed to converge to zero in finite time with an exponential rate [27].…”

Section: Introductionmentioning

confidence: 99%

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Stabilizing a Rotary Inverted Pendulum Based on Logarithmic Lyapunov Function

Wen

Shi

2017

Journal of Control Science and Engineering

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The stabilization of a Rotary Inverted Pendulum based on Lyapunov stability theorem is investigated in this paper. The key of designing control laws by Lyapunov control method is the construction of Lyapunov function. A logarithmic function is constructed as the Lyapunov function and is compared with the usual quadratic function theoretically. The comparative results show that the constructed logarithmic function has higher numerical accuracy and faster convergence speed than the usual quadratic function. On this basis, the control law of stabilizing Rotary Inverted Pendulum is designed based on the constructed logarithmic function by Lyapunov control method. The effectiveness of the designed control law is verified by experiments and is compared with LQR controller and the control law designed based on the quadratic function. Moreover, the system robustness is analyzed when the system parameters contain uncertainties under the designed control law.

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Section: System Parameter Settings the Values Of The Parameters Inmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Stabilizing a Rotary Inverted Pendulum Based on Logarithmic Lyapunov Function

Wen

Shi

2017

Journal of Control Science and Engineering

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“…The indirect adaptive control approach uses an identifier mechanism to distinguish the unknown plant parameters in real time from which the control gains are obtained. () However, these kinds of adaptive controllers require accurate information about the plant dynamics model . On the other hand, updating the process of controller gains can be made directly and without any information about plant parameters or mathematical models of the controlled system in direct adaptive control approach.…”

Section: Introductionmentioning

confidence: 99%

Online self‐tuning mechanism for direct adaptive control of tall building

Hosseini

Taghikhany

2017

Adaptive Control & Signal

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to the control system has completely different characteristics than the initial designed seismic excitation. KEYWORDS adaptive control, ANFIS, fuzzy inference system, MR damper, SAC, semiactive control 424 TABLE 6 Evaluation criteria comparison of different designed fuzzy inference systems Kobe J 1 J 2 J 3 J ave 3-Layer 0.7836 0.5857 0.7897 0.7196 5-Layer 0.7749 0.5784 0.8027 0.7187 7-Layer 0.7676 0.5713 0.8154 0.7181 El Centro J 1 J 2 J 3 J ave 3-Layer 0.7841 0.7502 0.9396 0.8246 5-Layer 0.7504 0.733 0.9268 0.8034 7-Layer 0.7088 0.7147 0.936 0.7865

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“…A novel control scheme is developed based on a single-hidden layer feedforward network approximation capability of combing ELMs to capture vehicle dynamics. Yue et al [34] investigated error data-based trajectory planner and indirect adaptive fuzzy control with the application on two-wheeled IP using indirect adaptive fuzzy and sliding mode control approaches, Lyapunov theory and LaSalle’s invariance theorem. Yue et al [35] designed a composite control approach for balancing and trajectory tracking of two-wheeled IP vehicle using adaptive sliding mode, fuzzy-based control and adaptive mechanism.…”

Section: Introductionmentioning

confidence: 99%

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

Goher

2016

Robot. Biomim.

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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.

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

Cited by 51 publications

References 41 publications

Stabilizing a Rotary Inverted Pendulum Based on Logarithmic Lyapunov Function

Stabilizing a Rotary Inverted Pendulum Based on Logarithmic Lyapunov Function

Online self‐tuning mechanism for direct adaptive control of tall building

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

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