Robust Control with Dynamic Compensation for Human-Wheelchair System

Andaluz, Víctor H.; Canseco, Paúl; Varela, José; Ortiz, Jessica S.; Pérez, María Jesús Verdú; Robertí, Flavio; Carelli, Ricardo

doi:10.1007/978-3-319-13966-1_37

Cited by 14 publications

(3 citation statements)

References 18 publications

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“…Therefore, it is useful to express the dynamic model of the mobile robot unicycle type conveniently considering the linear and angular speed as input signals, all in order to use this model in controller design. Then, the model of the mobile robot can be expressed as [15,16]…”

Section: Dynamic Modelmentioning

confidence: 99%

“…On the other hand, if perfect speed tracking is not considered in the design of the kinematic controller, i.e.,v(t) = v c (t), the speed error is defined asṽ(t) = v c (t) − v(t). Considering this speed error arises the need to design a dynamic compensation control, whose objective is to reduce the speed tracking error; therefore, it is proposed the following control law based on the dynamic model ( 4), [15,17] After introducing the control laws (4) and ( 10) in (11), the time derivative can be expressed as:V…”

Section: Dynamic Compensation Of the I-th Robotmentioning

confidence: 99%

See 1 more Smart Citation

Unicycle Mobile Robot Formation Control in Hardware in the Loop Environments

Quispe

Molina

Ortiz

et al. 2021

Communications in Computer and Information Science

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This work presents the development of a formation control algorithm for three unicycle-type robots, to solve the problem in the implementation of controllers oriented to collaborative functions and also subject to an excessive economic cost. This leads to the approximation of the simulation technique in environments Hardware in the loop (HIL), which allow clearly visualize with a real idea and a high percentage of approximation of the behavior of mobile robots unicycle type integrating different types of advanced controllers that will allow the execution of tasks of mobile robots unicycle type the same that are determined by the trajectories that control the position and thus raises the strategy of nonlinear control with a centralized and decentralized formation in the work area, acting as a command and control management system that will in turn be able to receive input signals, process the information and deliver control signals, which will later be displayed and analyzed to help verify the control theory.

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Section: Dynamic Modelmentioning

confidence: 99%

Section: Dynamic Compensation Of the I-th Robotmentioning

confidence: 99%

Unicycle Mobile Robot Formation Control in Hardware in the Loop Environments

Quispe

Molina

Ortiz

et al. 2021

Communications in Computer and Information Science

Self Cite

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“…For several years differential-drive mobile robots (DDMR) have been widely used in many applications because of their simple configuration and good mobility. Some applications of DDMR are surveillance [2], floor cleaning [3], industrial load transportation [4], autonomous wheelchairs [5], and others.…”

Section: Introductionmentioning

confidence: 99%

Motion Control and Velocity-Based Dynamic Compensation for Mobile Robots

Martins

Brandão²

2019

Applications of Mobile Robots

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The design of motion controllers for wheeled mobile robots is often based only on the robot's kinematics. However, to reduce tracking error it is important to also consider the robot dynamics, especially when high-speed movements and/or heavy load transportation are required. Commercial mobile robots usually have internal controllers that accept velocity commands, but the control signals generated by most dynamic controllers in the literature are torques or voltages. In this chapter, we present a velocity-based dynamic model for differential-drive mobile robots that also includes the dynamics of the robot actuators. Such model can be used to design controllers that generate velocity commands, while compensating for the robot dynamics. We present an explanation on how to obtain the parameters of the dynamic model and show that motion controllers designed for the robot's kinematics can be easily integrated with the velocity-based dynamic compensation controller. We conclude the chapter with experimental results of a trajectory tracking controller that show a reduction of up to 50% in tracking error index IAE due to the application of the dynamic compensation controller.

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