Approximate Dynamic Programming in Tracking Control of a Robotic Manipulator

Szuster, Marcin; Gierlak, Piotr

doi:10.5772/62129

Cited by 10 publications

(5 citation statements)

References 29 publications

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“…We compare with the adaptive sliding controller (ASC) in [12]. Consider a Scorbot-ER robot manipulator [27] shown in Figures 4 and 5, where a 1 = 0.35m, a e = 0.025m, a 2 = 0.222m, a 3 = 0.222m.…”

Section: Resultsmentioning

confidence: 99%

Adaptive synchronous sliding control for a robot manipulator based on neural networks and fuzzy logic

Nguyen Duc,

Vu Viet

2024

IJECE

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Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for robot hands is always an attractive topic in the research community. This is a challenging problem because robot manipulators are complex nonlinear systems and are often subject to fluctuations in loads and external disturbances. This article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller ensures that the positions of the joints track the desired trajectory, synchronize the errors, and significantly reduces chattering. First, the synchronous tracking errors and synchronous sliding surfaces are presented. Second, the synchronous tracking error dynamics are determined. Third, a robust adaptive control law is designed, the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy logic. The built algorithm ensures that the tracking and approximation errors are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results. Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is significantly reduced.

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Section: Resultsmentioning

confidence: 99%

Adaptive synchronous sliding control for a robot manipulator based on neural networks and fuzzy logic

Nguyen Duc,

Vu Viet

2024

IJECE

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“…The Lyapunov stability method is used to evaluate the optimization, and an artificial neural network is used to identify critical conditions. Then, the same authors in [9] presented the use of dual heuristic dynamic programming to solve the task of the optimal tracking control of an articulated robot manipulator. The duality of the control algorithm results from the two structures of the actor's and the critic's neural networks.…”

Section: State Of Knowledgementioning

confidence: 99%

Creating Autonomous Multi-Object Safe Control via Different Forms of Neural Constraints of Dynamic Programming

Lisowski

2024

Electronics

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The aim of this work, which is an extension of previous research, is a comparative analysis of the results of the dynamic optimization of safe multi-object control, with different representations of the constraints of process state variables. These constraints are generated with an artificial neural network and take movable shapes in the form of a parabola, ellipse, hexagon, and circle. The developed algorithm allows one to determine a safe and optimal trajectory of an object when passing other multi-objects. The obtained results of the simulation tests of the algorithm allow for the selection of the best representation of the motion of passing objects in the form of neural constraints. Moreover, the obtained characteristics of the sensitivity of the object’s trajectory to the inaccuracy of the input data make it possible to select the best representation of the motion of other objects in the form of an excessive approximation area as neural constraints of the control process.

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“…Consider the Scorbot-ER robotic manipulator [38], illustrated in Figs. 2, 3, where l 1 = 0.35m, l e = 0.025m, l 2 = 0.222m, l 3 = 0.222m.…”

Section: Figure 2 Actual Scorbot-ermentioning

confidence: 99%

ADP-Based H_∞ Optimal Control of Robot Manipulators With Asymmetric Input Constraints and Disturbances

Nguyen Duc,

Lai Khac,

Tan

2024

IEEE Access

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Trajectory tracking control for robot manipulators is an attractive topic in the research community. This is a challenging problem because robot manipulators are complex nonlinear systems. Furthermore, the tracking control performance for robot manipulators is greatly affected by input constraints and external disturbances. This paper proposes a novel H ∞ optimal controller for robot manipulators with asymmetric input constraints and external disturbances based on adaptive dynamic programming (ADP). Firstly, a strict feedback nonlinear system is used to represent the robot manipulator dynamics, and then a feedforward controller is designed to construct the tracking error dynamics. Secondly, a value function is introduced, and the Hamilton-Jacobi-Isaacs equation is made and approximated online by the principle of adaptive dynamic programming. Thirdly, the optimal control law and disturbance compensation law are determined. The stability and convergence of the proposed algorithm are analyzed by the Lyapunov technique. Finally, the controller performance is verified through simulation and experimental results with STM32F407 of STMicroelectronics.INDEX TERMS Robot manipulators, Asymmetric input constraints, Adaptive dynamic programming, H ∞ optimal control.

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Approximate Dynamic Programming in Tracking Control of a Robotic Manipulator

Cited by 10 publications

References 29 publications

Adaptive synchronous sliding control for a robot manipulator based on neural networks and fuzzy logic

Adaptive synchronous sliding control for a robot manipulator based on neural networks and fuzzy logic

Creating Autonomous Multi-Object Safe Control via Different Forms of Neural Constraints of Dynamic Programming

ADP-Based H_∞ Optimal Control of Robot Manipulators With Asymmetric Input Constraints and Disturbances

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Approximate Dynamic Programming in Tracking Control of a Robotic Manipulator

Cited by 10 publications

References 29 publications

Adaptive synchronous sliding control for a robot manipulator based on neural networks and fuzzy logic

Adaptive synchronous sliding control for a robot manipulator based on neural networks and fuzzy logic

Creating Autonomous Multi-Object Safe Control via Different Forms of Neural Constraints of Dynamic Programming

ADP-Based H∞ Optimal Control of Robot Manipulators With Asymmetric Input Constraints and Disturbances

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ADP-Based H_∞ Optimal Control of Robot Manipulators With Asymmetric Input Constraints and Disturbances