Complete dynamic model of the Twin Rotor MIMO System (TRMS) with experimental validation

Tastemirov, Azamat; Lecchini‐Visintini, Andrea; Morales-Viviescas, Rafael M.

doi:10.1016/j.conengprac.2017.06.009

Cited by 35 publications

(28 citation statements)

References 16 publications

(26 reference statements)

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“…

and

define the moment of inertia of the rotors; the terms

and

express the main and tail electromechanical torques generated by the DC motors;

and

illustrate the aerodynamic torques; and

and

denote the friction torques. Following a similar argument as [ 13 ], the dynamics of the current of the motors defined in Expressions ( 1 ) and ( 3 ) is ignored due to the higher value of the DC motor mechanical time constants against the electrical ones. In fact, the DC motor mechanical constants (

and

) are in the order of

-times higher than the DC motor electrical constants (

and

), as you may observe in Table 1 , which shows the parameters of both rotors.…”

Section: Dynamic Modelmentioning

confidence: 99%

“…A linear parameter varying (LPV) method of identification, by taking a local approach, is considered in order to derive an LPV model for TRMS by means of interpolation and approximation in the work of Tanaka et al [ 12 ]. The Euler–Lagrange method is employed in the research of Tastermirov [ 13 ] to obtain a complete dynamic model of the TRMS, which is tuned and validated experimentally. More recently, a model based on first-principle modeling and later improved by gray box modeling, has been presented in [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Robust Decentralized Nonlinear Control for a Twin Rotor MIMO System

Belmonte

Morales

Fernández-Caballero

et al. 2016

Sensors

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This article presents the design of a novel decentralized nonlinear multivariate control scheme for an underactuated, nonlinear and multivariate laboratory helicopter denominated the twin rotor MIMO system (TRMS). The TRMS is characterized by a coupling effect between rotor dynamics and the body of the model, which is due to the action-reaction principle originated in the acceleration and deceleration of the motor-propeller groups. The proposed controller is composed of two nested loops that are utilized to achieve stabilization and precise trajectory tracking tasks for the controlled position of the generalized coordinates of the TRMS. The nonlinear internal loop is used to control the electrical dynamics of the platform, and the nonlinear external loop allows the platform to be perfectly stabilized and positioned in space. Finally, we illustrate the theoretical control developments with a set of experiments in order to verify the effectiveness of the proposed nonlinear decentralized feedback controller, in which a comparative study with other controllers is performed, illustrating the excellent performance of the proposed robust decentralized control scheme in both stabilization and trajectory tracking tasks.

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“…

and

define the moment of inertia of the rotors; the terms

and

express the main and tail electromechanical torques generated by the DC motors;

and

illustrate the aerodynamic torques; and

and

) are in the order of

-times higher than the DC motor electrical constants (

and

), as you may observe in Table 1 , which shows the parameters of both rotors.…”

Section: Dynamic Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust Decentralized Nonlinear Control for a Twin Rotor MIMO System

Belmonte

Morales

Fernández-Caballero

et al. 2016

Sensors

View full text Add to dashboard Cite

show abstract

“…These works can roughly be categorized as dedicated to i) physics-based modeling approaches including energy-based methods such as Newtonian, Euler-Lagrange, etc. (i.e., white box system identification) [3]- [5], ii) modeling methods utilizing artificial intelligence-like approaches such as neural networks, genetic algorithms, etc. (i.e., black box system identification) [6]- [9], and iii) some hybrid methods that make use of both of the above-mentioned methods (i.e., grey box modeling approaches) [10]- [13].…”

Section: Introductionmentioning

confidence: 99%

Experimental Verification of Lead-Lag Compensators on a Twin Rotor System

Deniz

Tatlıcıoğlu

Bayrak

2018

Electrical, Control and Communication Engineering

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Twin rotor system is a laboratory setup resembling a simplified helicopter model that moves along both horizontal and vertical axes. The literature on control of twin rotor systems reflects a good amount of research on designing PID controllers and their extensions considering several aspects, as well as onsome nonlinear controllers. However, there is almost no previous work on design of lag-lead type compensators for twin rotor systems. In this study, by considering this open research problem, lag and lead type compensators are designed and then experimentally verified on the twin rotor system. Specifically, first, lag and lag-lag compensators are designed to obtain a reduced steady state error as compared with proportional controllers. Secondly, lead compensation is discussed to obtain a reduced overshoot. Finally, lag-lead compensators are designed to make use of their favorable properties. All compensators are applied to the twin rotor system in our laboratory. From experimental studies, it was observed that steady state error was reduced when a lag compensator was used in conjunction with a lead compensator.

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“…Since the Twin Rotor is fundamentally a mechanical system, its equations of motion can be obtained directly through an energetic formulation based on the Euler-Lagrange equations [12,13,16]. For that, it is necessary to calculate the kinetic energy (x,ẋ ) and the potential energy (x) of its moving parts.…”

Section: The Twin Rotormentioning

confidence: 99%

“…This laboratory setup, which is similar to a model of a helicopter, has attracted a great attention during the last decades due to its highly nonlinear and cross-coupled dynamics. Being seen as a challenging engineering problem, the Twin Rotor has been widely used as an experimentation platform in research projects [11][12][13][14][15][16] as well as in MS and PhD theses [17] to validate different types of control algorithms.…”

Section: Introductionmentioning

confidence: 99%

Iterative Learning Control Experimental Results in Twin‐Rotor Device

Palliser¹,

Costa‐Castelló²,

Ramos³

2017

Mathematical Problems in Engineering

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This paper presents the results of applying the Iterative Learning Control algorithms to a Twin-Rotor Multiple-Input MultipleOutput System (TRMS) in order to achieve high performance in repetitive tracking of trajectories. The plant, which is similar to a prototype of helicopter, is characterized by its highly nonlinear and cross-coupled dynamics. In the first phase, the system is modelled using the Lagrangian approach and combining theoretical and experimental results. Thereafter, a hierarchical control architecture which combines a baseline feedback controller with an Iterative Learning Control algorithm is developed. Finally, the responses of the real device and a complete analysis of the learning behaviour are exposed.

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Complete dynamic model of the Twin Rotor MIMO System (TRMS) with experimental validation

Cited by 35 publications

References 16 publications

Robust Decentralized Nonlinear Control for a Twin Rotor MIMO System

Robust Decentralized Nonlinear Control for a Twin Rotor MIMO System

Experimental Verification of Lead-Lag Compensators on a Twin Rotor System

Iterative Learning Control Experimental Results in Twin‐Rotor Device

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