This study aims to develop a complex hybrid 3D robot with parallel links driven by the nonlinear pneumatic servo system for path tracking control. The mechanical system and the control system are the primary parts for developing a complex hybrid 3D robot. In the mechanical system, a complex hybrid 3D robot contains serial manipulators, parallel links, base plates, a movable platform and a pneum...

this paper presents designing an optimal adaptive controller for tracking control of robot manipulators based on particle swarm optimization (pso) algorithm. pso algorithm has been employed to optimize parameters of the controller and hence to minimize the integral square of errors (ise) as a performance criteria. in this paper, an improved pso using logic is proposed to increase the convergenc...

The problems of control of robot manipulators with actuation degradation and detection of actuation faults are addressed in this paper. An adaptive fault tolerant control method is proposed for robot manipulators to maintain the required performance in the presence of actuation degradation, and the same adaptive algorithm is utilized to detect actuation failures. The proposed method can compens...

This paper presents a discrete-time decentralized control scheme for trajectory tracking of a two degrees of freedom (DOF) robot manipulator. A modified recurrent high order neural network (RHONN) structure is used to identify the plant model and based on this model, a discrete-time control law is derived, which combines block control and sliding mode techniques. The neural network learning is ...

This paper presents an on-line tracking optimization scheme for sensor guided robotic manipulators by associating sensor information, manipulator dynamics and a path generator model. Feedback linearizationdecoupling permits the use of linear SISO prediction models for the dynamics of each robot joint. Scene interpretation of CCD-camera images generates spline fitted segments of future trajector...

This paper presents a general recurrent neural network (RNN) model for online control of time-varying robot manipulators. The robot manipulators with different setting parameters work cooperatively on an unknown curve tracing. Each joint of the manipulator is respectively provided a learning method to optimize trajectory by the training RNN model. In this paper, the proposed RNN model shortens ...

Reduction of contour error is a very important issue for high precise contour tracking applications, and many control systems were proposed to deal with contour tracking problems for two/three axial translational motion systems. However, there is no research on cross-coupled contour tracking control for serial multi-DOF robot manipulators. In this paper, the contouring control of multi-DOF seri...

A neural network (NN)-based adaptive controller with an observer is proposed for the trajectory tracking of robotic manipulators with unknown dynamics nonlinearities. It is assumed that the robotic manipulator has only joint angle position measurements. A linear observer is used to estimate the robot joint angle velocity, while NNs are employed to further improve the control performance of the ...

We present some feedback control techniques recently developed for the exact solution of t rajectory tracking problems for manipulators with flexible elements. Two classes are considered: i) robots with rigid links but with elastic transmissions, in which flexibility is concentrated at the joints, and ii) robots with lightweight and/or long arms, where flexibility is distributed along the links...

The KUKA Control Toolbox (KCT) is a collection of MATLAB functions developed at the University of Siena, for motion control of KUKA robot manipulators. The toolbox, which is compatible with all 6 DOF small and low-payload KUKA robots that use the Eth.RSIXML, runs on a remote computer connected with the KUKA controller via TCP/IP. KCT includes more than 40 functions, spanning operations such as ...