An Approach to the Dynamics and Control of Uncertain Robot Manipulators

Yang, Xiaohui; Zhang, Xiaolong; Xu, Shaoping; Ding, Yihui; Zhu, Ka-Di; Liu, Peter

doi:10.3390/a12030066

Cited by 5 publications

(4 citation statements)

References 30 publications

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“…e dynamic parameters which describe the dynamic model are important for the control algorithms, effective simulation results, and accurate trajectory tracking algorithms. Dynamic equation of the robotic manipulator withn-DOF has been characterized in many literature studies [1][2][3][4][5][6][7][8][9][10][11] as follows:…”

Section: Description Of Link Parameters Of Robotic Manipulatormentioning

confidence: 99%

“…e first stage of trajectory tracking is to establish the precise mathematical model of the robotic manipulator. However, the nonlinear part of the dynamic model of the robotic manipulator is ignored in many literatures [1][2][3][4][5] or parameter identification by many approaches [6][7][8]; even the torque in the joint space and the moment of inertia were ignored in [9]. By calculating kinetic energy, potential energy, and generalized force, the Lagrange equation was utilized to build the dynamic equation for robotic manipulator [10,11].…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Backstepping Sliding Mode Control of Trajectory Tracking for Robotic Manipulators

Zhu

Puchen

et al. 2020

Complexity

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To achieve precise trajectory tracking of robotic manipulators in complex environment, the precise dynamic model, parameters identification, nonlinear characteristics, and disturbances are the factors that should be solved. Although parameters identification and adaptive estimate method were proposed for robotic control in many literature studies, the essential factors, such as coupling and friction, are rarely mentioned as it is difficult to build the precise dynamic model of the robotic manipulator. An adaptive backstepping sliding mode control is proposed to solve the precise trajectory tracking under external disturbances with complex environment, and the dynamic response characteristics of a two-link robotic manipulator are described in this paper. First, the Lagrange kinetic method is used to derive the precise dynamic model which includes the nonlinear factor with friction and coupling. Moreover, the dynamic model of two-link robotic manipulator is built. Second, the estimate function for the nonlinear part is selected, and backstepping algorithm is used for analyzing the stabilities of the sliding mode controller by using Lyapunov theory. Furthermore, the convergence of the proposed controller is verified subject to the external disturbance. At last, numerical simulation results are reported to demonstrate the effectiveness of the proposed method.

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Section: Description Of Link Parameters Of Robotic Manipulatormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive Backstepping Sliding Mode Control of Trajectory Tracking for Robotic Manipulators

Zhu

Puchen

et al. 2020

Complexity

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“…Dynamic methods can be mainly divided into two types: explicit and recursive. These procedures include the recursive Lagrange method, the generalized D'Alembert principle, the Kane method, the recursive Newton-Euler algorithm (RNEA), and the Lagrange-Euler formulation (L-E) [25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Automated Symbolic Processes for Dynamic Modeling of Redundant Manipulator Robots

Urrea,

Saa,

Kern

2024

Processes

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In this study, groundbreaking software has been developed to automate the generation of equations of motion for manipulator robots with varying configurations and degrees of freedom (DoF). The implementation of three algorithms rooted in the Lagrange–Euler (L-E) formulation is achieved through the utilization of .m files in MATLAB R2020a software.This results in the derivation of a symbolic dynamic model for industrial manipulator robots. To comprehend the unique features and advantages of the developed software, dynamic simulations are conducted for two 6- and 9-DoF redundant manipulator robots as well as for a 3-DoF non-redundant manipulator robot equipped with prismatic and rotational joints, which is used to simplify the dynamic equations of the redundant prototypes. Notably, for the 6-DoF manipulator robot, model predictive control (MPC) is employed using insights gained from the dynamic model. This enables optimal control by predicting the future evolution of state variables: specifically, the values of the robot’s joint variables. The software is executed to model the dynamics of different types of robots, and the CPU time for a MacBook Pro with a 3 GHz Dual-Core Intel Core i7 processor is less than a minute. Ultimately, the theoretical findings are validated through response graphs and performance indicators of the MPC, affirming the accurate functionality of the developed software. The significance of this work lies in the automation of motion equation generation for manipulator robots, paving the way for enhanced control strategies and facilitating advancements in the field of robotics.

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“…The same method is used in a manifold of applications to minimise a cost function with constraints, such as [34][35][36]. Among the applications that are based on this method, one can enumerate the following: trajectory planning for unmanned ground vehicles [37], optimal control of a diesel engine [38], minimisation of fuel consumption in a hybrid electric vehicle [39], control of dynamics of a robot manipulator [40] and thermal applications [41,42]. The main advantages of our proposed solution with respect to similar works are:…”

Section: Introductionmentioning

confidence: 99%

Multivariable Optimisation for Waiting-Time Minimisation at Roundabout Intersections in a Cyber-Physical Framework

Pauca

Maxim

Caruntu

2021

Sensors

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The evolution of communication networks offers new possibilities for development in the automotive industry. Smart vehicles will benefit from the possibility of connecting with the infrastructure and from an extensive exchange of data between them. Furthermore, new control strategies can be developed that benefit the advantages of these communication networks. In this endeavour, the main purposes considered by the automotive industry and researchers from academia are defined by: (i) ensuring people’s safety; (ii) reducing the overall costs, and (iii) improving the traffic by maximising the fluidity. In this paper, a cyber-physical framework (CPF) to control the access of vehicles in roundabout intersections composed of two levels is proposed. Both levels correspond to the cyber part of the CPF, while the physical part is composed of the vehicles crossing the roundabout. The first level, i.e., the edge-computing layer, is based on an analytical solution that uses multivariable optimisation to minimise the waiting times of the vehicles entering a roundabout intersection and to ensure a safe crossing. The second level, i.e., the cloud-computing layer, stores information about the waiting times and trajectories of all the vehicles that cross the roundabout and uses them for long-term analysis and prediction. The simulated results show the efficacy of the proposed method, which can be easily implemented on an embedded device for real-time operation.

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An Approach to the Dynamics and Control of Uncertain Robot Manipulators

Cited by 5 publications

References 30 publications

Adaptive Backstepping Sliding Mode Control of Trajectory Tracking for Robotic Manipulators

Adaptive Backstepping Sliding Mode Control of Trajectory Tracking for Robotic Manipulators

Automated Symbolic Processes for Dynamic Modeling of Redundant Manipulator Robots

Multivariable Optimisation for Waiting-Time Minimisation at Roundabout Intersections in a Cyber-Physical Framework

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