Model‐based robust control design and experimental validation of collaborative industrial robot system with uncertainty

Zhen, Shengchao; Zhang, Meng; Liu, Xiaoli; Chen, Ye‐Hwa

doi:10.1002/asjc.2864

Cited by 6 publications

(6 citation statements)

References 26 publications

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“…Consider that the dynamic system with inequality constraints ( 5) is subject to the Assumptions 1-3. The system is stable by applying the control term (20).…”

Section: R Yu Et Almentioning

confidence: 99%

“…Besides, as control theory continues to advance, a series of control methods have been proposed, such as PID control [20,21], sliding model control [22,23] and adaptive robust control [24][25][26]. Some instances are as follow, in [27], a control method for nonlinear system was proposed based on the robust control and PID control, and it has been applied to solve the position tracking control of motor.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Constraint-following control for dynamic systems with comprehensive constraints: the generalized Udwadia–Kalaba approach

Yu,

Lu,

Zhu

et al. 2024

Meas. Sci. Technol.

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A novel Generalized Udwadia-Kalaba (GUK) control method is proposed in this paper to effectively deal with the constraint-following problem with comprehensive constraints, be it equality constraints or inequality constraints. Fully considering the complex application scenario in practice which encompassed both clear and feasible trajectory, the equality constraints and inequality constraints are simultaneously applied to design rational and reliable controller. Specifically, a state transformation function is introduced to describe the inequality constraints. Further, the dynamic model with comprehensive constraints is established based on the GUK theory. Then, a corresponding constraint-following control is presented to render the system performance, uniform boundedness and uniform ultimate boundedness. The effectiveness of the GUK control is verfied by the stability analysis based on Lyapunov minimax approach and experimental verification of unmanned underwater vehicle (UUV). The desired control performances of UUV, constraint-following and collision avoidance, can be achieved. As an illustrative application, the UUV is designed to navigate through narrow sea trenches. Meanwhile, through comparative analysis with the linear quadratic regulator (LQR) method and Udwadia-Kalaba (UK) method, the superiority of this approach is demonstrated.

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“…Consider that the dynamic system with inequality constraints ( 5) is subject to the Assumptions 1-3. The system is stable by applying the control term (20).…”

Section: R Yu Et Almentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Constraint-following control for dynamic systems with comprehensive constraints: the generalized Udwadia–Kalaba approach

Yu,

Lu,

Zhu

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…On this basis, the introduction of neural networks and fuzzy logic can better estimate and compensate for uncertainties [25]. Nevertheless, the combined algorithm also involves complex high-order calculations, which increase the convergence time and reduce the response speed [26]. Marco A. Arteaga-Pérez et al presented the incorporation of an adaptive term into robust control to improve the control performance, where the adaptive term is considered as a bounded disturbance and does not affect the stability of the system [27].…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Robust Adaptive Control of Universal Manipulators Based on Desired Trajectory

Chen,

Ding,

Chen

et al. 2024

Applied Sciences

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The introduction of a dynamic model in robot trajectory tracking control design can significantly improve its trajectory tracking accuracy, but there are many uncertainties in the robot dynamic model which can be dealt with through robust control and adaptive control. The prevailing robust control as well as adaptive control methods require real-time computation of robot dynamics, but the extreme complexity of the robot dynamics equations makes it difficult to apply these methods in real industrial systems. To this end, this article proposes a robust adaptive control method based on the desired trajectory, which uses the desired trajectory to compute most of the control terms offline, including the robot’s nominal dynamics and regression matrices, and substantially reduces the need for real-time computation of the feedback signals. The robust term modifies the perturbation of the inertial parameters of the links, the adaptive term learns the friction coefficients of the joints online, and an additional compensation term is designed to satisfy the Lyapunov stability condition of the system. Finally, taking a universal manipulator as the experimental platform, the control performances of different control methods are compared to show the feasibility of the controller and the effective reduction in real-time computational complexity.

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“…At present, intelligent control technology and robust control methods for robots have received extensive research [1][2][3][4]. Utilizing visual sensors as the feedback unit for robots is known as visual servoing, which is now widely applied in mobile robots control [5], underwater robot attitude control [6], unmanned aerial vehicle (UAV) attitude control [7,8], and plant harvesting [9].…”

Section: Introductionmentioning

confidence: 99%

Adaptive visual servoing for the robot manipulator with extreme learning machine and reinforcement learning

Li,

Peng,

et al. 2023

Asian Journal of Control

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In this study, a novel image‐based visual servo (IBVS) controller for robot manipulators is investigated using an optimized extreme learning machine (ELM) algorithm and an offline reinforcement learning (RL) algorithm. First of all, the classical IBVS method and its difficulties in accurately estimating the image interaction matrix and avoiding the singularity of pseudo‐inverse are introduced. Subsequently, an IBVS method based on ELM and RL is proposed to solve the problem of the singularity of the pseudo‐inverse solution and tune adaptive servo gain, improving the servo efficiency and stability. Specifically, the ELM algorithm optimized by particle swarm optimization (PSO) was used to approximate the pseudo‐inverse of the image interaction matrix to reduce the influence of camera calibration errors. Then, the RL algorithm was adopted to tune the adaptive visual servo gain in continuous space and improve the convergence speed. Finally, comparative simulation experiments on a 6‐DOF robot manipulator were conducted to verify the effectiveness of the proposed IBVS controller.

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Model‐based robust control design and experimental validation of collaborative industrial robot system with uncertainty

Cited by 6 publications

References 26 publications

Constraint-following control for dynamic systems with comprehensive constraints: the generalized Udwadia–Kalaba approach

Constraint-following control for dynamic systems with comprehensive constraints: the generalized Udwadia–Kalaba approach

Nonlinear Robust Adaptive Control of Universal Manipulators Based on Desired Trajectory

Adaptive visual servoing for the robot manipulator with extreme learning machine and reinforcement learning

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