Analytical Synthesis of Aggregated Regulators for Unmanned Aerial Vehicles

Podvalny, S. L.; Vasiljev, Eugeny

doi:10.1007/s10958-019-04295-w

Cited by 16 publications

(2 citation statements)

References 7 publications

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“…To solve the synthesis problem and obtain an equilibrium point, methods of modal control [29] can be applied for linear systems, as well as other analytical methods such as backstepping [30], analytical design of aggregated controllers [31,32], or synthesis based on the application of the Lyapunov function [21,33]. Note that all known analytical synthesis methods for nonlinear systems, when implemented, are associated with a specific type of model, therefore they cannot be considered universal.…”

Section: The Problem Of Control System Synthesismentioning

confidence: 99%

Fundamentals of Synthesized Optimal Control

et al. 2020

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This paper presents a new formulation of the optimal control problem with uncertainty, in which an additive bounded function is considered as uncertainty. The purpose of the control is to ensure the achievement of terminal conditions with the optimal value of the quality functional, while the uncertainty has a limited impact on the change in the value of the functional. The article introduces the concept of feasibility of the mathematical model of the object, which is associated with the contraction property of mappings if we consider the model of the object as a one-parameter mapping. It is shown that this property is sufficient for the development of stable practical systems. To find a solution to the stated problem, which would ensure the feasibility of the system, the synthesized optimal control method is proposed. This article formulates the theoretical foundations of the synthesized optimal control. The method consists in making the control object stable relative to some point in the state space and to control the object by changing the position of the equilibrium points. The article provides evidence that this approach is insensitive to the uncertainties of the mathematical model of the object. An example of the application of the method for optimal control of a group of robots is given. A comparison of the synthesized optimal control method with the direct method on the model without disturbances and with them is presented.

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Section: The Problem Of Control System Synthesismentioning

confidence: 99%

Fundamentals of Synthesized Optimal Control

et al. 2020

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“…With the structural-parametric approach, not only are the parameters optimized, but the optimal structure of the feedback control function is also sought. Among the analytical methods for solving the problem of stabilization system synthesis, the most popular are methods based on solving the Riccati equation [7], but, for linear systems only, as well as more modern analytical approaches of backstepping [8] and analytical design of aggregated controllers [9,10], they also depend on the types of right-hand sides of nonlinear differential equations that describe the control object model. This challenging task for nonlinear systems can be addressed by a dynamic programming (DP) algorithm assisted by the Hamilton-Jacobi-Bellman (HJB) equation.…”

Section: Introductionmentioning

confidence: 99%