A nonlinear optimal control approach for autonomous motorcycles

Rigatos, Gerasimos; Siano, Pierluigi; Wira, Patrice; Abbaszadeh, Masoud

doi:10.23919/acc.2018.8431431

Cited by 4 publications

(14 citation statements)

References 17 publications

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“…The global stability properties of the control scheme are proven through Lyapunov analysis. First, it is demonstrated that the control loop of the rotary double inverted pendulum satisfies the H‐infinity tracking performance criterion 1‐4,32 . This signifies elevated robustness against model uncertainty and exogenous perturbations.…”

Section: Introductionmentioning

confidence: 95%

“…Nonlinear control for underactuated robotic systems is an elaborated task which has become the subject of much research work during the last years 1‐4 . In this domain, the double rotary pendulum (double Furuta pendulum) is a benchmark nonlinear dynamical system and the solution of the associated nonlinear optimal control problem is challenging 5‐9 .…”

Section: Introductionmentioning

confidence: 99%

“…For the approximately linearized model of the rotary double inverted pendulum a stabilizing H‐infinity feedback controller is designed. This controller achieves the solution of the optimal control problem for the nonlinear dynamics of the rotary double inverted pendulum under model uncertainty and external disturbances 2‐4 …”

Section: Introductionmentioning

confidence: 99%

“…Actually, the H‐infinity controller represents a min‐max differential game which takes place between: (i) the system's control inputs that try to minimize a cost function which contains a quadratic term of the state vector's tracking error, (ii) the system's disturbances and model uncertainty terms which try to maximize this cost function. To select the feedback gains of the H‐infinity controller an algebraic Riccati equation has to be repetitively solved at each time‐step of the control algorithm 1‐4 . The global stability properties of the control scheme are proven through Lyapunov analysis.…”

Section: Introductionmentioning

confidence: 99%

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Nonlinear optimal control for the rotary double inverted pendulum

et al. 2023

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The control problem of the rotary double inverted pendulum (double Furuta pendulum) is nontrivial because of underactuation and strong nonlinearities in the associated state‐space model. The system has three degrees of freedom (one actuated and two unactuated joints) while receiving only one control input. In this article, a novel nonlinear optimal (H‐infinity) control approach is developed for the dynamic model of the rotary double inverted pendulum. First, the dynamic model of the double pendulum undergoes approximate linearization with the use of first‐order Taylor series expansion and through the computation of the associated Jacobian matrices. The linearization process takes place at each sampling instance around a temporary operating point which is defined by the present value of the system's state vector and by the last sampled value of the control inputs vector. At a next stage a stabilizing H‐infinity feedback controller is designed. To compute the controller's feedback gains an algebraic Riccati equation has to be solved at each time‐step of the control algorithm. The global stability properties of the control scheme are proven through Lyapunov analysis. To implement state estimation‐based control without the need to measure the entire state vector of the rotary double‐pendulum the H‐infinity Kalman filter is used as a robust state observer. The nonlinear optimal control method achieves fast and accurate tracking of setpoints by all state variables of the rotary double inverted pendulum under moderate variations of the control input.

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Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Nonlinear optimal control for the rotary double inverted pendulum

et al. 2023

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“…Apart from that, there has been design of ‘flatness‐based controllers’ implemented in ‘successive loops’ and indicative results about this approach can be found in [42]. The problem of non‐linear control and stabilisation for the power generation unit that comprises a steam turbine and a synchronous generator can be also treated with the use of a novel non‐linear optimal control method [44]. The flatness‐based control approach which is proposed in the present article is based on the global linearisation of the dynamics of the steam‐turbine and synchronous generator power unit, whereas in the non‐linear optimal control approach an approximate linearisation concept has been followed.…”

Section: Simulation Testsmentioning

confidence: 99%

Flatness‐based control for steam‐turbine power generation units using a disturbance observer

Rigatos

Zervos

Siano

et al. 2021

IET Electric Power Appl

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Steam-turbine power plants still supply a significant part of the electric power consumed worldwide. The viability of steam turbine power units depends on their efficiency to a great extent and the control method applied to the them is of major importance for achieving their improved functioning. The authors propose flatness-based control and non-linear Kalman Filtering for power generation units comprising synchronous generators connected to steam turbines. It is shown that the dynamic model of this power system is a differentially flat one. This property signifies that all its state variables and its control inputs can be expressed as its differential functions of selected state variables, the latter standing for the flat outputs of the system. This allows for its transformation into a linear canonical form in which the design of a feedback controller and the solution of the state estimation problem becomes possible. Moreover, by introducing a Kalman Filterbased disturbance observer it becomes possible to identify in real time the perturbation terms that affect the power system's model. Through the proposed flatness-based controller, fast and accurate tracking of all reference setpoints is achieved by the state vector elements of the power unit. Moreover, through the proposed Kalman Filter-based disturbances estimator, the control loop is given additional robustness against modelling errors and external perturbations.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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