Dynamic Model Of Robot Manipulator Research Articles

Optimal Fully Actuated System Approach-Based Trajectory Tracking Control for Robot Manipulators.

In this article, a trajectory tracking control strategy is proposed for robot manipulators via a fully actuated system (FAS) approach, which has shown its simplicity and flexibility for most of the nonlinear controller design. However, the motion control for robot manipulators is more complicated since unknown dynamical model, external disturbances, friction forces, and various physical constraints are required to be considered. Therefore, the FAS approach cannot be straightforwardly applied. To address these challenges, the dynamic model of robot manipulators is established via model identification methods. Furthermore, based on the identified model, an FAS composite control strategy with simple structure is designed, which is achieved by integrating a high-order disturbance observer (HODO) in the inner loop, with an FAS trajectory tracking controller in the outer loop. Specifically, the HODO is utilized for handling the uncertain dynamics and external disturbances. Moreover, the controller gains are optimized using a gradient-based optimal parameter tuning method (OPTM). By imposing joint angle constraints, joint angular velocity constraints, and input torque limits into the formulation, the OPTM also ensures the satisfaction of these physical constraints. Numerical simulations and experiments are provided to validate the performance of the proposed controller.

Interval Type 2 Fuzzy PD+G Control for Position Regulation of Manipulator Robots

This paper presents an alternative to enhance the classical PD+G Control for position regulation of robot manipulators, using interval type-2 fuzzy logic to compensate variations in the gravitational forces vector of the dynamic model of the robot. The proposed control strategy detects the variation in the gravity vector and performs a Takagi-Sugeno type fuzzy mapping using the mentioned variation as the input and a compensation gain as the output using interval type-2 fuzzy sets. Furthermore, the passivity property of the dynamic model of robot manipulators is used for the controller design by means of the direct Lyapunov's method in order to guarantee asymptotic stability. The experiments were performed using numerical simulations with a model of a 2 DOF robot manipulator, showing successful results for the position regulation of the robot joints.

ANFIS-based an adaptive continuous sliding-mode controller for robot manipulators in operational space

This paper addresses the task-space robust trajectory tracking control problem for robot manipulators in the presence of uncertainties and external disturbances. First, a discontinuous sliding-mode controller-based inverse dynamics control strategy (IDSMC) with discontinuous robust control action is synthesized. Second, an adaptive inverse dynamics controller based on continuous sliding-mode control (AIDCSMC) is designed, in which the adaptation laws are addressed to compensate for the unknown parameters of the dynamical model of robot manipulators. The global stability of the closed-loop control system is proven using the Lyapunov theorem and the proposed AIDCSMC controller is further proven to guarantee convergence to zero of both trajectory tracking error and error rate. Finally, a hybrid intelligent neuro-fuzzy adaptive fuzzy inference system (ANFIS)-based adaptive inverse dynamics controller with continuous sliding-mode control (ANFIS-AIDCSMC) is adopted. Numerical simulations using the dynamic model of rigid robot manipulators with uncertainties show the effectiveness of the presented approach in simple and complex trajectory tracking problems. The simulation results indicate that the control performance of the robot system is satisfactory, and the proposed approach can achieve favorable tracking performance and it is robust with regard to uncertainties.

Simplied Methodology for Obtaining the Dynamic Model of Robot Manipulators

The main goal of this manuscript is to present a simplification of the Euler-Lagrange methodology, which allows us to simplify the obtaining of dynamic model of a robot using the intrinsic properties of dynamic model, which allows to reduce the computation time when the model is programmed. Using the [Formula: see text] norm, the proposed methodology is compared with the Euler-Lagrange methodology for obtaining a performance index to determine the proposed simplification efficiency. The main contribution of this manuscript is to present a methodology to obtain the completely symmetric dynamic model.

Dynamic model of robot manipulator in explicit form formulation with dual vectors and the notion of augmented body

AbstractThis article deals with the dynamic model formulation and computation in explicit form of the inverse dynamic model of a robot manipulator constituted with a simple kinematic chain. We go on with the studies of Pennock and Giordano using the dual vectors, and we introduce the notion of augmented body. Our aim is to obtain the computation of the inverse dynamic model in explicit form with an almost minimal number of arithmetical operations to allow the dynamic control synthesis in real time. The method proposed here requires two steps of computation: first, an intrinsic theoretical computation; second, an extrinsic practical computation using dual matrices. This method is then applied to the robot manipulator COMAU‐POLAR 6000 and compared with the method of Renaud, considered until now the most performant method. This comparison leads to the same number of arithmetical operations with both methods.