Adaptive backstepping control of wheeled inverted pendulum with velocity estimator

Maruki, Yuji; Kawano, K.; Suemitsu, Haruo; Matsuo, Takami

doi:10.1007/s12555-013-0402-4

Cited by 29 publications

(12 citation statements)

References 12 publications

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“…With uniaxial vehicles backstepping is often combined with other control methods: In [10], [12], [11] adaptive backstepping for pitch control is combined with PD control for translational motion of a uniaxial vehicle, in [15] an indirect MRA controller is used.…”

Section: Approaches For Parameter Adaptive Stabilisation Of Uniaxmentioning

confidence: 99%

“…For application system description in strict feedback form is precondition, which is not possible with both (11) and (12) combined. This is why previous approaches neglect control of the systems translational motion (11) or apply additional methods.…”

Section: ) Adaptive Pitch Angle Controlmentioning

confidence: 99%

“…With also setting these parameters to zero, shortly pushing the vehicle puts it into motion without coming to a halt by itself. While the adaptive approach described above already provides pitch angle stability with variable payload, pedestrian controlled manoeuvre behaviour is still highly depending on the load's weight, since (11) is not considered yet. Fig.…”

Section: ) Adaptive Pitch Angle Controlmentioning

confidence: 99%

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Adaptive backstepping controller with Kalman state estimator for stabilisation and manoeuvre of pedestrian controlled uniaxial transport vehicles

Brüning

Thiele

Schönewolf

et al. 2015

2015 IEEE International Conference on Mechatronics (ICM)

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Pedestrian controlled uniaxial vehicles for goods transport such as hand trucks offer intuitive manoeuvrability with little space requirements. The disadvantage of this class of statically underdetermined vehicles is the need for the user to apply force for both stabilisation and propulsion. Removing this disadvantage is the key to enable their use for convenient transportation of heavy goods over long distances. For this our solution approach is to equip the vehicle with controlled drives providing force for both balancing and propulsion. Different to uniaxial vehicles without payload or for passenger transportation controller's adaptation to kinematic and dynamic parameters is required here after every reload. The frame's pitch angle must be adapted with every change of load whereby the COG's position is not measurable with acceptable effort. Dynamic parameters vary in a wide range. We applied an adaptive controller based on backstepping combined with Kalman state estimation for stable balancing with adaptation to changed payload without need for external support from the user. The manoeuvre concept based on low interaction forces applied from the user to the vehicle frame is taking advantage of the underconstrained dynamics of the vehicle, and offers similar driving behaviour to the user with different load situations. Operating control levers for setting speed is not required. To allow for cheap production a design goal was not requiring sensor information of both load's absolute weight and user interaction forces. The adaptive control and state estimation concept was simulated based on the kinematic and dynamic model of our new uniaxial vehicle system designed for urban parcel distribution on foot. Simulation results show the correct operation of the approach

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Section: Approaches For Parameter Adaptive Stabilisation Of Uniaxmentioning

confidence: 99%

Section: ) Adaptive Pitch Angle Controlmentioning

confidence: 99%

Section: ) Adaptive Pitch Angle Controlmentioning

confidence: 99%

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Adaptive backstepping controller with Kalman state estimator for stabilisation and manoeuvre of pedestrian controlled uniaxial transport vehicles

Brüning

Thiele

Schönewolf

et al. 2015

2015 IEEE International Conference on Mechatronics (ICM)

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“…[1][2][3][4][5][6][7][8][9][10][11][12][13][14] In spite of highly rich literature, it is surprising to notice that a Lyapunov function is required to obtain the virtual control law and the parameter updated law at each step of the design. In general, backstepping algorithm is taken as a core for control design of nonlinear systems in strict feedback form and is combined with other techniques like adaptive control, fuzzy or neural network control, and sliding mode control to yield some new control methods for both academic and industrial communities.…”

Section: Introductionmentioning

confidence: 99%

Mapping filtered forwarding‐based robust adaptive control for uncertain nonlinear systems with input constraint

Zhang

Huang

et al. 2017

Adaptive Control & Signal

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This work develops a robust adaptive control algorithm for uncertain nonlinear systems with parametric uncertainties and external disturbances satisfying an extended matching condition. This control method is implemented in the framework of a mapping filtered forwarding-based technique. As an attractive alternative of the adaptive backstepping method, this bottom-up strategy forms a virtual controller and a parameter updated law at each step of the design, where Lyapunov functions and the prior knowledge of system parameters are not required. The boundedness of all signals is guaranteed by using Barbalat's lemma. According to immersion relationship, a compliant behavior of systems behaves accordingly to the lower-order target dynamics. Furthermore, input constraints are handled by estimating a saturated scaling. A spring, mass, and damper system is used to demonstrate the controller performances via simulation results. KEYWORDS adaptive control, filters, input saturation, mapping filtered forwarding control, uncertain nonlinear systems 248 ;32:248-264. ZHANG ET AL. 249error as z =θ − θ + β(x), where β(x) is a continuous term, and utilizing the uncertainty equivalence principle to design parameter update laws for lower triangular systems. Although researchers used this method to design parameter update laws in some practical systems, the achievements strictly depend on an assumption satisfying the partial differential inequality to obtain β(x). 20,21 In essence, the solvability of this inequality strongly relies on the structure of the regressor, and as system order increases, the implementation will be limited. Therefore, it could not be feasible to achieve I&I adaptive stabilization for high-order nonlinear systems with extended matching uncertainties. 22,23 Furthermore, control input saturation severely limits system performance in many physical systems, giving rise to undesirable properties or leading instability. 24,25 The hyperbolic tangent function is used to approximate the saturated nonlinearity, 12 where the approximated error is considered as an augmented external disturbance. Although this algorithm is easy to be carried out, the problem of the definition domain of artanh(·) is encountered while tuning controller gains. It can be shown that the bound of the nonlinear function we derive must be restricted to (−1, 1). 26 The problem of the controller design for the nonlinear systems with input saturation and parametric uncertainties has not been addressed adequately under a mapping filtered forwarding-based framework.In this paper, we will study the robust adaptive control design for nonlinear systems subject to input saturation and uncertainties under the mapping filtered forwarding-based framework. A new bottom-up control scheme from a manifold's perspective, namely, mapping filtered adaptive forwarding, which consists of virtual control laws and parameter updated laws, will be presented. With the proposed controller architecture, manifolds are guaranteed to be insensitive to uncertainties, and the iss...

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“…Wheeled inverted pendulum is a multi-variable and uncertain nonlinear system and has attracted a lot of attention recently [6,7,8,12], and it is a ideal model to verify different control theories. The stabilization of an unstable nonlinear wheeled inverted pendulum in the upright position has been applied by Backstepping technique.…”

Section: Introductionmentioning

confidence: 99%

PD backstepping controller for stabilization of wheeled inverted pendulum

Liu

Cao

2015

2015 34th Chinese Control Conference (CCC)

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In this paper, the PD Backstepping control problem is investigated for two-wheeled inverted pendulum. A nonlinear model with two states is given which is proposed to keep stability at upright position and track the specified position. Backstepping controller is used to generate the law with measured states and ensures the convergence towards zero of the angle tracking error. Furthermore, PD controller is used to control the movement of system towards the set position. The co-simulation results demonstrate the effectiveness and correction of the proposed control method in this paper.

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Adaptive backstepping control of wheeled inverted pendulum with velocity estimator

Cited by 29 publications

References 12 publications

Adaptive backstepping controller with Kalman state estimator for stabilisation and manoeuvre of pedestrian controlled uniaxial transport vehicles

Adaptive backstepping controller with Kalman state estimator for stabilisation and manoeuvre of pedestrian controlled uniaxial transport vehicles

Mapping filtered forwarding‐based robust adaptive control for uncertain nonlinear systems with input constraint

PD backstepping controller for stabilization of wheeled inverted pendulum

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