PSO-Lyapunov motion/force control of robot arms with model uncertainties

Mehdi, Haifa; Boubaker, Olfa

doi:10.1017/s0263574714001775

Cited by 11 publications

(4 citation statements)

References 41 publications

(38 reference statements)

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“…Consider the 3D hyperchaotic Rabinovich systems and the error system described by (19), (21), and (23) with ℎ = 6.75, = 4, = 1, and = 1, respectively, where the initial conditions are 1 (0) = 0.1, 2 (0) = 0.1, …”

Section: Remark 11mentioning

confidence: 99%

Master‐Slave Synchronization of 4D Hyperchaotic Rabinovich Systems

Ding

Volos

et al. 2018

Complexity

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This paper is concerned with master-slave synchronization of 4D hyperchaotic Rabinovich systems. Compared with some existing papers, this paper has two contributions. The first contribution is that the nonlinear terms of error systems remained which inherit nonlinear features from master and slave 4D hyperchaotic Rabinovich systems, rather than discarding nonlinear features of original hyperchaotic Rabinovich systems and eliminating those nonlinear terms to derive linear error systems as the control methods in some existing papers. The second contribution is that the synchronization criteria of this paper are global rather than local synchronization results in some existing papers. In addition, those synchronization criteria and control methods for 4D hyperchaotic Rabinovich systems are extended to investigate the synchronization of 3D chaotic Rabinovich systems. The effectiveness of synchronization criteria is illustrated by three simulation examples.

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Section: Remark 11mentioning

confidence: 99%

Master‐Slave Synchronization of 4D Hyperchaotic Rabinovich Systems

Ding

Volos

et al. 2018

Complexity

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“…ii. Generate the polynomial trajectories φ a , φ a and φ a described by (18)(19)(20) using the Point-to-Point method according to the relation (11). iii.…”

Section: The Jerk Optimal Algorithmmentioning

confidence: 99%

“…Unfortunately, it generally suffers of lack of precision and robustness. Recently, several research papers have proposed some improvements to overcome such problems [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

An optimal jerk-stiffness controller for gait pattern generation in rough terrain

Aloulou

Boubaker

2016

Robomech J

Self Cite

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In this paper, an optimal jerk stiffness controller is proposed to produce stable gait pattern generation for bipedal robots in rough terrain. The optimal jerk controller is different from the point-to-point and via-Point conventional approaches as trajectories are planned in the Cartesian space system whereas control laws are expressed in the joint space. Its major contribution resides in the generation of stable semi elliptic Cartesian trajectories during the swing phase that do combine benefits of trigonometric and polynomial functions. The stiffness controller is designed without gravity compensation and ensures for the robotic system elastic and stable contact forces with the ground during the impact and the double support phases. Not only, the control strategy proposed needs very few sensors to be implemented but also it ensures robustness to sensory noise and safety with rough terrain. Simulation performed on a 12 DOF bipedal robot shows the performances of the control laws combined to produce a 3D stable walking cycles without shaking in uneven terrain.

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“…By observing the movement of the teacher with marked points, the movement information of the teacher can be quickly and accurately obtained, and the computer passes the obtained data through. A certain algorithm is processed to generate a reasonable robot trajectory and store it and then controls the robot to repeat the same actions as the teacher, so that the robot learns useful actions and enables it to quickly adapt to new tasks and environments [23,24].…”

Section: Introductionmentioning

confidence: 99%

Optimal Recognition of Volleyball Player’s Arm Movement Track Based on Embedded Microprocessor

Liu

Tao

2022

Wireless Communications and Mobile Computing

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An embedded microprocessor is the core part of the integrated circuit system, and it represents one of the highest levels of a digital integrated circuit design. Therefore, the design of low-power embedded microprocessors has become an important research direction in the integrated circuit design. Volleyball has always been a very important sport in our country, and it is a sport that the masses of people like to see. The basic techniques of volleyball include ready posture and movement, serving, hot ball, passing, smashing, and netting. The research content of this article is a simulation study of volleyball players’ arm trajectory optimization recognition. In response to the above problems, this paper proposes an optimized recognition method based on the volleyball player’s arm motion trajectory. The simulation results show that the method has high recognition accuracy and provides a strong scientific basis for improving the volleyball players’ spike skills. Without interference from the right arm, the controller input and position tracking error will not fluctuate in 1 ≤ T ≤ 3 , the controller input is stable, and the output error is zero. Based on the above simulation analysis, it can be seen that the control method does not require the robot kinematics and dynamics model to generate any regression matrix when designing the controller. The controller is suitable for the performance tracking of humanoid robot arms.

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PSO-Lyapunov motion/force control of robot arms with model uncertainties

Cited by 11 publications

References 41 publications

Master‐Slave Synchronization of 4D Hyperchaotic Rabinovich Systems

Master‐Slave Synchronization of 4D Hyperchaotic Rabinovich Systems

An optimal jerk-stiffness controller for gait pattern generation in rough terrain

Optimal Recognition of Volleyball Player’s Arm Movement Track Based on Embedded Microprocessor

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