Vibration Control Using Pole Placement with Proportional Gain of a Flexible Manipulator Incorporating Payload

Khairudin, Moh.

doi:10.1007/s40313-021-00752-7

Cited by 5 publications

(3 citation statements)

References 13 publications

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“…The motion of such sets can be expressed via a hybrid system of partial differential equations (PDEs), ordinary differential equations (ODEs), and boundary conditions (BCs). Such systems of equations cannot be usually solved by common analytical methods due to their nonlinearity or their complex boundary conditions, but they can be solved using the assumed mode method (AMM) approach, 1 finite element method (FEM), 2 lumped parameter method (LPM), 3 method of lines (MOL) 4 and so forth. One of the most fundamental models by which a wide range of mechanical systems such as robotic arms can be described is the beam model.…”

Section: Introductionmentioning

confidence: 99%

Feedback control of actuation‐constrained moving structure carrying Timoshenko beam

Homaeinezhad

Gavari

2022

Intl J Robust & Nonlinear

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This article deals with tracking control and active vibration suppression of a hybrid rigid‐elastic vibrational mobile system with a nonlinear elastic foundation in the presence of actuator bandwidth limitation and control input saturation. The system consists of a rigid rectilinearly mobile frame on an elastic foundation, and a flexible Timoshenko beam clamped to it with a heavy attached concentrated mass. The hybrid partial differential equation (PDE)‐ordinary differential equation (ODE) system of the plant is obtained using Hamilton's principle and then is converted to a system of ODEs using the assumed mode method (AMM). Next, the model will be discretized in the time domain using the two‐step Adams‐Bashforth technique. Considering the first‐order dynamics to cover the bandwidth limitation of the actuator, a discrete‐time sliding mode controller (DSMC) is designed based on a positive definite Lyapunov functional. Following that, an innovative optimal predictive algorithm is proposed to compensate for the effects of input saturation. The proposed algorithm is based on a positive definite cost function and using an intelligent regime of optimizations and decisions, minimizes the cost function in a predefined prediction horizon. The vibratory behavior of the system also is included in the mentioned cost function. Consequently, the overall control scheme called optimal rigid‐elastic interaction control (OREIC) will be able to follow the desired tracking trajectory, suppress the beam vibrations, and compensate for the effect of bandwidth limitation as well as the effect of input saturation. The performance of the OREIC algorithm is compared with a saturated DSMC controller and the simulation results demonstrate the efficiency of the method in vibration control of mobile rigid‐elastic systems subjected to actuator bandwidth frequency and saturation limitations.

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Section: Introductionmentioning

confidence: 99%

Feedback control of actuation‐constrained moving structure carrying Timoshenko beam

Homaeinezhad

Gavari

2022

Intl J Robust & Nonlinear

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“…A careful revision about the modeling and control of flexible manipulators is presented by Sayahkarajy et al 1 It is a fact that the reduction of inertia inevitably can increase vibrations requiring the design of adequate control strategies as indicated by Khairudin. 2 These control strategies should cope with performance requirements and actuation limitations.…”

Section: Introductionmentioning

confidence: 99%

A comparison between gain-scheduling linear quadratic regulator and model predictive control for a manipulator with flexible components

Colombo

Silva

2022

Proceedings of the Institution of Mechanical Engineers, Part I:

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Dynamic performance and energy efficiency can be improved by reducing the inertia of mechanical systems. However, the components of such a system may be flexible and, inevitably, subject to vibrations. Moreover, the relative motion between flexible components leads to time-varying boundary conditions characterizing configuration-dependent dynamics. Since robust controllers may be conservative for this problem, adaptive controllers should be considered since they can cope with performance design requirements. In this work, we present a comparison between a linear quadratic regulator gain-scheduling control and an adaptive model predictive control for a flexible industrial Cartesian manipulator with configuration-dependent dynamics. This study takes the system stability and the use of bounded actuation into account. Numerical results demonstrate that the adaptive model predictive control strategy achieved better performance than the linear quadratic regulator gain scheduled. Also, in applications with tighter actuation bounds, the difference between the performance of both approaches is even higher, reinforcing the model predictive control capability of dealing with limited actuation.

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“…In general, self-tuning control for elastic joint manipulators is designed based on input and output data of the plant. It is now more prevalent than model-based control techniques [1,2] due to the difficulty in establishing an accurate model for the complicated elastic joint manipulator [3]. In this respect, selftuning control for flexible (elastic) joint manipulators is divisible into two types: feedforward and feedback controllers.…”

Section: Introductionmentioning

confidence: 99%

PID Tuning Method Using Chaotic Safe Experimentation Dynamics Algorithm for Elastic Joint Manipulator

Fadzrizan¹,

Ahmad²,

Jui³

2021

JESA

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This paper proposed the chaotic safe experimentation dynamics algorithm (CSEDA) to regulate angular tracking and vibration of the self-tuning PID controller for elastic joint manipulators. CSEDA was a modified version of the safe experimentation dynamics algorithm (SEDA) that used a chaos function in the updated equation. The chaos function increased the exploration capability, thus improving the convergence accuracy. In this study, two self-tuning PID controllers were used to regulate the rotating angle tracking and vibration for elastic joint manipulators in this control challenge. The suggested self-tuning PID controller's performance was evaluated in angular motion trajectory tracking, vibration suppression, and the pre-determined control fitness function. A self-tuned PID controller based on CSEDA could achieve superior control accuracy than a traditional SEDA and its variants.

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Vibration Control Using Pole Placement with Proportional Gain of a Flexible Manipulator Incorporating Payload

Cited by 5 publications

References 13 publications

Feedback control of actuation‐constrained moving structure carrying Timoshenko beam

Feedback control of actuation‐constrained moving structure carrying Timoshenko beam

A comparison between gain-scheduling linear quadratic regulator and model predictive control for a manipulator with flexible components

PID Tuning Method Using Chaotic Safe Experimentation Dynamics Algorithm for Elastic Joint Manipulator

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