Experimentally supported control design for a direct drive robot

IEEE Transactions on Robotics, 2010

Robust controllers for robot manipulators ensure stability of the closed-loop system, even if only partial knowledge of the dynamic model of the manipulator is available. Existing derivations of robust-control laws, while guaranteeing the stability result, present an undesired dependence of the robust-control term on the gains of the controller for the nominal system. This dependence forces larger robust-control terms when the nominal control gains are large. Based on a structured representation of the model uncertainty, this paper proposes a derivation of the robust-control law, where these limitations are removed. Experimental results on the COMAU SMART 3S industrial robot in a 3-degree-of-freedom (DOF) configuration confirm the advantages of the proposed controller.

IEEE Transactions on Energy Conversion, 1991

IEEJ Transactions on Industry Applications, 1996

We consider the problem of applying H`° optimization techniques to design a TDOF controller for robust servo systems. We introduce a two-step H°° optimization procedure: a feedback controller is designed to satisfy feedback properties and a prefilter is used to improve reference tracking performance. We describe a mixed sensitivity optimization scheme that is used for the feedback controller design, and propose a frequency shaping philosophy that highlights key issues for the prefilter design. We discuss the uncertainties in DC motor model and explain how to treat the parametric and non-parametric uncertainties in H"° optimization framework. We also show a design example for a DC motor with parametric uncertainties and analyze the tracking property in terms of design strategy and parameters change.

Journal of Telecommunication, Electronic and Computer Engineering, 2016

Direct drive system is the driving part that is directly connected to the driven part without using a gearbox. The advantages of direct drive system are frictionless, high efficiency, noise reduction and high torque, produced at low speed. However, the direct drive motor system has its limitation, which is sensitive to the disturbance and parameter variation. In this paper, a proportional derivative controller with disturbance observer (PDDO) is designed to achieve high positioning performance of the direct-drive system in the presence of mass and disturbance force variations. The direct-drive system in this paper is driven using voice coil motor. The disturbance observer controller is relatively easier to design than the other advanced controllers and often shows higher robust to the disturbance force and model parameter change, as compared to the conventional controller. The positioning performance of PDDO controller is evaluated and compared with a PID controller, which is design...

IEEE/ASME Transactions on Mechatronics, 2000

This paper presents a new methodology for the design of a robust controller to compensate for friction-induced dynamical characteristics inherently present in servodrives systems. A friction model is developed using a local modeling approach of the physical properties of friction along the operating range of the underlying system. Generally, developing a faithful model for physical nonlinearities is still a challenging task that is strongly related to the identification effort required by the structure of the model and the complexity of the control algorithm. The proposed model has the advantage of being simple and able to describe friction locally. The accuracy of the estimator based on the model structure can be improved by a gain-scheduled input signal obtained for different velocities and used as a precompensator of nonlinear friction. This leads to an effective linearzing strategy of the controlled system that subsequently simplifies the controller implementation stage. A stabilizing-state feedback controller is designed, assuming an inexact compensation of friction, which guarantees robustness against uncertainties arising from modeling errors and achieves high tracking performance of the overall controlled system. Experimental tests performed on a robot joint laboratory prototype demonstrate the effectiveness of the proposed friction compensation scheme to improve the performance of the overall system.

IEEE Transactions on Control Systems Technology, 2005

A combination of model-based and iterative learning control (ILC) is proposed as a method to achieve high-quality motion control of direct-drive robots in repetitive motion tasks. We include both model-based and learning components in the total control law, as their individual properties influence the performance of motion control. The model-based part of the controller compensates much of the nonlinear and coupled robot dynamics. A new procedure for estimating the parameters of the rigid body model, implemented in this part of the controller, is used. This procedure is based on a batch-adaptive control algorithm that estimates the model parameters online. Information about the dynamics not covered by the rigid body model, due to flexibilities, is acquired experimentally, by identification. The models of the flexibilities are used in the design of the iterative learning controllers for the individual joints. Use of the models facilitates quantitative prediction of performance improvement via ILC. The effectiveness of the combination of the model-based and the iterative learning controllers is demonstrated in experiments on a spatial serial direct-drive robot with revolute joints.

Vietnam Journal of Science and Technology

Precise control is critical for robots, but it is difficult to obtain an accurate dynamic model of the robot due to the presence of modeling errors and uncertainties in the complex working environment, resulting in decreased control performances. The article proposes a method for designing a digital controller for output tracking of disturbed repetitive robot manipulators that does not require a mathematical model of the controlled robots, with the goal of improving tracking accuracy. This controller consists of two separate intelligent parts. The first part aims to stabilize the original robot manipulators via a model-free state feedback linearization technique. The suggested model-free state feedback linearization technique does not make use of the original Euler-Lagrange model of the robot. The second part will then employ the concept of iterative learning control to asymptotically drive the obtained stable linear system to desired references. Both of these parts use only the rob...

IFAC Proceedings Volumes, 2014

Control of a flexible joint of an industrial manipulator using H ∞ design methods is presented. The considered design methods are i) mixed-H ∞ design, and ii) H ∞ loop shaping design. Two different controller configurations are examined: one uses only the actuator position, while the other uses the actuator position and the acceleration of the end-effector. The four resulting controllers are compared to a standard pid controller where only the actuator position is measured. The choices of the weighting functions are discussed in details. For the loop shaping design method, the acceleration measurement is required to improve the performance compared to the pid controller. For the mixed-H ∞ method it is enough to have only the actuator position to get an improved performance. Model order reduction of the controllers is briefly discussed, which is important for implementation of the controllers in the robot control system.

IEEE Access, 2022

This paper proposes a new design and practical implementation of a robust H ∞ control applied to some mechanical systems considering in the controller design full access to the state variables and in the equivalent controller implementation only the feedback of all positions or of all velocities of the plant. An important characteristic, though, is that limitations are considered for the state feedback. Two methods are presented, one that uses feedback only from state variables related to positions of the system and another that uses feedback only from state variables related to velocities. The control strategy is based on Linear Matrix Inequalities (LMIs), using the theory of D-stability, which allows the designer to allocate the closed loop system eigenvalues in a negative complex semi-plane region, which, in addition to ensuring stability, also allows to attend certain performance requirements of the feedback system. The paper motivation is to provide satisfactory control results with limited states access, without any kind of estimation of the state variables that are not available. Therefore, the proposed control systems are interesting options as alternatives for the design of full-order state feedback for plants with uncertain parameters using only output feedback, considering that it is not required to build an observer to estimate any plant state variable. Furthermore, their implementations are relatively cheaper because it is not necessary to measure all state variables of the plant.

Journal of Dynamic Systems, Measurement, and Control, 1983

A direct-drive arm is a mechanical arm in which the shafts of articulated joints are directly coupled to the rotors of motors with high torque. Since the arm does not contain transmission mechanisms between the motors and their loads, the drive system has no backlash, small friction, and high mechanical stiffness, all of which are desirable for fast, accurate, and versatile robots. First, the prototype robot is described, and basic feedback controllers for single-link drive systems are designed. Second, feedforward compensation is discussed. This compensation significantly reduces the effect of interactions among multiple joints and nonlinear forces. The experiments showed the excellent performance of the direct-drive arm in terms of speed and accuracy.