A trajectory tracking controller with dynamic gains for mobile robots

Resende, Cassius Zanetti; Espinosa, Felipe; Bravo, Ignácio; Sarcinelli-Filho, Mário; Bastos-Filho, Teodiano Freire

doi:10.1109/iros.2011.6094540

Cited by 3 publications

(5 citation statements)

References 16 publications

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“…The uncertainty vector is ignored in this case. The suggested control law for parametric uncertainty is as in (7):…”

Section: Dynamic Controllermentioning

confidence: 99%

“…In this section, C-BO is used to optimize parameters 𝑘 𝑥 , 𝑘 𝑦 , 𝑘 𝑢 and 𝑘 𝜔 of the tracking controller described in (4) and (7). Figure 3 depicts the ISE fitness function convergence of the C-BO, where shows a lower change after 300 iterative.…”

Section: Tuning and Simulation Process-based C-bo Algorithmmentioning

confidence: 99%

“…The actuator dynamics were included in the dynamic model, and the generated commands were the voltages. In [6], [7], various forms of trajectory-tracking controllers primarily depend on robot dynamics were developed. Signals of control by some of the dynamic controllers shown in literature, as in a significant number of the aforementioned studies, are voltages or torques for robot motors, although business robots usually receive velocity commands.…”

Section: Introductionmentioning

confidence: 99%

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Path tracking control of differential drive mobile robot based on chaotic-billiards optimization algorithm

Mohammed

Dessouki²,

Elnaghi³

2023

IJECE

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<span lang="EN-US">Mobile robots are typically depending only on robot kinematics control. However, when high-speed motions and highly loaded transfer are considered, it is necessary to analyze dynamics of the robot to limit tracking error. The goal of this paper is to present a new algorithm, chaotic-billiards optimizer (C-BO) to optimize internal controller parameters of a differential-drive mobile robot (DDMR)-based dynamic model. The C-BO algorithm is notable for its ease of implementation, minimal number of design parameters, high convergence speed, and low computing burden. In addition, a comparison between the performance of C-BO and ant colony optimization (ACO) to determine the optimum controller coefficient that provides superior performance and convergence of the path tracking. The ISE criterion is selected as a fitness function in a simulation-based optimization strategy. For the point of accuracy, the velocity-based dynamic compensation controller was successfully integrated with the motion controller proposed in this study for the robot's kinematics. Control structure of the model was tested using MATLAB/Simulink. The results demonstrate that the suggested C-BO, with steady state error performance of 0.6 percent compared to ACO's 0.8 percent, is the optimum alternative for parameter optimizing the controller for precise path tracking. Also, it offers advantages of quick response, high tracking precision, and outstanding anti-interference capability.</span>

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“…The uncertainty vector is ignored in this case. The suggested control law for parametric uncertainty is as in (7):…”

Section: Dynamic Controllermentioning

confidence: 99%

Section: Tuning and Simulation Process-based C-bo Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Path tracking control of differential drive mobile robot based on chaotic-billiards optimization algorithm

Mohammed

Dessouki²,

Elnaghi³

2023

IJECE

View full text Add to dashboard Cite

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“…Based on the Lyapunov function, backstepping control [6], [7], [8] designs the trajectory tracking control law with the thought of integral. The intelligent control [9], [10], [11] is successfully applied to the trajectory tracking of mobile robot without the determinate mathematical model. Each of the control approaches above has advantages and drawbacks in different situations yet, none of them can achieve perfect performance in the trajectory tracking.…”

Section: Introductionmentioning

confidence: 99%

A new method for trajectory tracking of nonholonomic mobile robot based on frequency spectrum

Liu

Dong

Jin

et al. 2015

2015 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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It is one of the fundamental issues for the mobile robot motion to track a known trajectory in most cases, such as the AGV in the factory, the mobile car in the physical distribution. This paper presents a new method for controlling a nonholonomic mobile robot to track a desired trajectory considering the sampling period of the sensors equipped on the robot. In natural coordinate system, the Fourier transform is utilized to attain the frequency characteristics of the trajectory. Then it can be confirmed that whether the trajectory can be tracked accurately and how to achieve an effective strategy for trajectory tracking according to the Nyquist's Theory. The simulation results verify the validity of the method proposed in this paper.

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“…The controller here proposed uses the control structure reported in Resende, Espinosa, Bravo, Sarcinelli-Filho, and Bastos-Filho (2011), combining the heuristic knowledge of the problem, the sector nonlinearity approach (Tanaka & Wang, 2001) and the inverse kinematic of the mobile platform. The use of the sector nonlinearity allows designing a fuzzy controller with a quite reduced number of rules and a quite low complexity, making it suitable for implementation in the low-profile processors generally available onboard mobile platforms.…”

Section: Introductionmentioning

confidence: 99%

A nonlinear trajectory tracking controller for mobile robots with velocity limitation via fuzzy gains

Resende

Carelli

Sarcinelli-Filho

2013

Control Engineering Practice

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A trajectory tracking controller with dynamic gains for mobile robots

Cited by 3 publications

References 16 publications

Path tracking control of differential drive mobile robot based on chaotic-billiards optimization algorithm

Path tracking control of differential drive mobile robot based on chaotic-billiards optimization algorithm

A new method for trajectory tracking of nonholonomic mobile robot based on frequency spectrum

A nonlinear trajectory tracking controller for mobile robots with velocity limitation via fuzzy gains

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