Robust control of nonlinear dynamic systems

Pshikhopov, Viacheslav; Medvedev, Mikhail

doi:10.1109/andescon.2010.5633481

Cited by 32 publications

(12 citation statements)

References 4 publications

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“…We consider the nominal model of the vehicle of the form [3,4] We synthesize for the nominal model (1) controls for stabilization at a given point. In accordance with the method of position-trajectory control [3] we introduce an error in the form…”

Section: Synthesis Of Control Loop Of Nomi-nal Reference Model Bumentioning

confidence: 99%

See 1 more Smart Citation

Adaptive Control of Vehicleposition with Non-linearizable Feedback

Pshikhopov¹,

Medvedev²,

Krukhmalev³

2015

Advances in Intelligent Systems Research

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The problem of vehicle control is considered in the paper. The model of vehicle is represented by the equations of kinematics and dynamics of a rigid body. The features of control that could appear for complicated maneuvers are investigated. In such motion the determinant of the matrix of kinematics may be equal to zero. This fact does not allow to set the desired dynamics of the closed-loop system in the form of linear equations. In other words the system cannot be linearized by feedback. The problem is solved by applying adaptive control systems with a reference model. A procedure for the synthesis of the basic position-trajectory control is proposed. Asymptotic stability analysis on base of the method of Lyapunov functions is considered. Adaptation of control is carried out by proportional and integral algorithms. The block-diagram of the closed-loop system is presented. The stability of the adaptive control system is proved. It is shown that in the linear approximation, the characteristic equation of the closed-loop system is a product of the characteristic equation of the reference models, the vehicle, and the adaptation subsystem. Modeling results are presented.

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Section: Synthesis Of Control Loop Of Nomi-nal Reference Model Bumentioning

confidence: 99%

“…We consider a model of the vehicle on the basis of the equations of kinematics and dynamics of a rigid body [3,4] ( ) ( )…”

Section: The Vehiclementioning

confidence: 99%

Adaptive Control of Vehicleposition with Non-linearizable Feedback

Pshikhopov¹,

Medvedev²,

Krukhmalev³

2015

Advances in Intelligent Systems Research

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“…They take into account the delay in the control signal path and relatively small disturbances. Of particular interest are the papers [15] and [16], the first of which presents experimental results of the implementation of the algorithm described in [17] (which proposes a robust controller using the inverse dynamics method). The disadvantage of the algorithm is, however, the fact that it requires the knowledge of both external disturbances and those resulting from the dynamics of the object.…”

Section: Introductionmentioning

confidence: 99%

Robust 3D tracking control of an underactuated autonomous airship

Adamski,

Pazderski,

Herman

2020

Preprint

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The paper presents a new, robust control algorithm for position trajectory tracking in a 3D space, dedicated to underactuated airships. In order to take into account real characteristics of such vehicles, and to reflect practically motivated constraints, the algorithm assumes a highly uncertain system dynamics model. The tracking problem is solved in a uniform way, without dividing it into subtasks considered in 2D spaces, thanks to the introduction of an auxiliary tracking error.The proposed controller is based on the sliding mode approach. Its stability is investigated using Lyapunov theorem. Numerical simulations are conducted in order to verify properties of a closed-loop system for a generic model of the airship.Performance of the control system is examined via experiments in various scenarios using a prototype airship. The obtained results indicate that the control objectives are satisfied in practice with a reasonable accuracy. Moreover, it is shown that the controller is robust to some bounded additive measurement perturbations and delays in the control loop.

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“…Control algorithm is described in [3,7,8]. Main advantage of control algorithm is consideration of propulsion drives on the level of control forces and moments.…”

Section: Control Algorithm and Distribution Of Control Forces And Mommentioning

confidence: 99%