Robust IDA-PBC for under-actuated systems with inertia matrix dependent of the unactuated coordinates: application to a UAV carrying a load

Guerrero-Sánchez, María-Eusebia; Hernández-González, Omar; Valencia‐Palomo, Guillermo; Mercado-Ravell, Diego Alberto; López‐Estrada, Francisco‐Ronay; Hoyo-Montaño, José A.

doi:10.1007/s11071-021-06776-7

Cited by 20 publications

(14 citation statements)

References 20 publications

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“…Second, in view of the

H_{\infty }

performance is also significant in terms of system disturbance rejection performance analysis, the memristor‐based locally fixed‐time

H_{\infty }

controller is also designed. Compared with the existing results, the present paper has the following new highlights: (i)Compared with the existing disturbance rejection schemes [10–17], the memritor‐based method does not sacrifice its nominal control performance. The disturbance rejection is supplied by a state‐dependent memristor, which is almost as straightforward as the inclusion of resistive elements to the original PH system.…”

Section: Introductionmentioning

confidence: 82%

“…Therefore, studies on the disturbance rejection for PH systems have attracted considerable attention. In recent years, several elegant methods have been proposed, such as adaptive control (AC) [10], integral control (IC) [11,12], sliding mode control (SMC) [13], disturbance observer-based control (DOBC) [14][15][16], and active disturbance rejection control (ADRC) [17], etc. However, these control methods have their own shortcomings or limitations.…”

Section: Introductionmentioning

confidence: 99%

“…(i) Compared with the existing disturbance rejection schemes [10][11][12][13][14][15][16][17], the memritor-based method does not sacrifice its nominal control performance. The disturbance rejection is supplied by a state-dependent memristor, which is almost as straightforward as the inclusion of resistive elements to the original PH system.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Memristor‐based disturbance rejection control for port‐Hamiltonian systems with locally fixed‐time convergence

Liu

Zhao

2022

IET Control Theory & Appl

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The memristor is added to the port‐Hamiltonian systems to improve the disturbance suppression performance in this paper. The concepts of locally fixed‐time stability and locally fixed‐time H∞$H_{\infty }$ control of port‐Hamiltonian systems are presented. From this starting point, two novel memristor‐based locally fixed‐time controllers are designed to suppress the external disturbance of port‐Hamiltonian systems via the interconnection and damping assignment passivity‐based control technique. Comparing with the classical interconnection and damping assignment passivity‐based control methodology without memristor, there are some advantages. First, the settling‐time related to the memristor‐based controllers in stabilizing the same port‐Hamiltonian systems are shorter. Second, the memristor‐based controllers can make the oscillation in the case of the strong periodic disturbance be better suppressed. Theoretical analysis shows that the memristor‐based controller possesses good disturbance rejection performance owing to it can make the system states in a neighbourhood accelerate convergence to the desired equilibrium point. Two illustrative examples show that the theoretical results and the controllers designed in this paper work very well.

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“…Second, in view of the

H_{\infty }

performance is also significant in terms of system disturbance rejection performance analysis, the memristor‐based locally fixed‐time

H_{\infty }

Section: Introductionmentioning

confidence: 82%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Memristor‐based disturbance rejection control for port‐Hamiltonian systems with locally fixed‐time convergence

Liu

Zhao

2022

IET Control Theory & Appl

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“…Proposition 3. The system (1) with Assumptions 1 and 3 in closed-loop with the control law (3), the auxiliary control (21) and the time derivatives of the integral actions (22a,b) yields (18) with the parameters (19).…”

Section: Controller Design For Position-dependent and Constant Distur...mentioning

confidence: 99%

Integral passivity‐based control of underactuated mechanical systems with state‐dependent matched disturbances

Franco,

Arpenti,

Donaire

2023

Intl J Robust & Nonlinear

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This work investigates the energy shaping control of a class of underactuated mechanical systems subject to state‐dependent linearly parameterized matched disturbances. To this end, a new integral interconnection and damping‐assignment passivity‐based design is proposed. The controller design is developed for systems subject to either momenta‐dependent disturbances or position‐dependent disturbances or to both simultaneously. The effectiveness of the proposed approach is demonstrated with numerical simulations on three examples: an Acrobot system with nonlinear friction; a ball‐on‐beam system with constant and position‐dependent disturbances; a disk‐on‐disk system with a complete set of state‐dependent disturbances. In all examples, the proposed controller shows better performance compared to previous implementations.

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“…Wenbo Gao employed deep learning control in the aeroengine control system and significantly improved the performance of this engine [6]. Guerrero-Sánchez presented a passivity-based control scheme and enhanced the performance of UAVs in load transportation [7,8]. Among all theories, the MRAC controller, offering high control accuracy, robustness, and adaptability [9][10][11][12][13], is one of the most mature and widely used adaptive controllers.…”

Section: Introductionmentioning

confidence: 99%

A Nonlinear Adaptive Autopilot for Unmanned Aerial Vehicles Based on the Extension of Regression Matrix

Feng

et al. 2023

Drones

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In applications of the L1 adaptive flight control system, we found two limitations to be extended: (1) the system cannot meet the demands of engineering in terms of nonlinearity and adaptation in most flight scenarios; (2) the adaptive control law generates a transient response in the tracking error, hindering the system from reaching the steady-state error, and ultimately decreasing control accuracy. In response to these problems, an extended flight control system for L1 adaptive theory is proposed and rigorously proved. This system involves considering the nonlinear function matrix of state variables, which serves as an extension of the regression matrix in the original L1 adaptive control system, thus enhancing its nonlinear characteristics. The problem of calculating the adaptive laws, caused by the extended regression matrix, is solved by using the pseudo-inverse matrix. To eliminate the transient response, the state vector and its estimate are recorded and employed just like an integrator. Finally, the proposed system is verified on a high-subsonic flight subject to nonlinear uncertainties, with simulation results showing improved control accuracy and enhanced robustness. The proposed system resolves the limitations of the L1 adaptive control system in nonlinearity, providing the possibility for further theoretical development to improve the performance of adaptive control systems.

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Robust IDA-PBC for under-actuated systems with inertia matrix dependent of the unactuated coordinates: application to a UAV carrying a load

Cited by 20 publications

References 20 publications

Memristor‐based disturbance rejection control for port‐Hamiltonian systems with locally fixed‐time convergence

Memristor‐based disturbance rejection control for port‐Hamiltonian systems with locally fixed‐time convergence

Integral passivity‐based control of underactuated mechanical systems with state‐dependent matched disturbances

A Nonlinear Adaptive Autopilot for Unmanned Aerial Vehicles Based on the Extension of Regression Matrix

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