On the application of a new method for fast and robust position control of industrial robots

Kuntze, H.-B.; Jacubasch, A.; Hirsch, U.; Richalet, J.; Arber, C.

doi:10.1109/robot.1988.12290

Cited by 14 publications

(3 citation statements)

References 8 publications

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“…A polynomial expression of the controller can be obtained by splitting Q 1 and Q 2 in numerators and denominators. According to (9)(10)(11), an appropriate choice of Q 1 and Q 2 can modify GPC0 to reach the desired objectives. Q 2 affects the input/output behavior, while Q 1 influences closed-loop properties such as robustness and disturbance rejection.…”

Section: B Robustification Of Gpc Control Lawsmentioning

confidence: 99%

“…In the rigid robot case, linear predictive methods are applied to linear decoupled design models, obtained either as an approximation around a fixed configuration [4], or after feedback linearization [5], [6], while analytical expressions corresponding to the nonlinear predictive control problem are obtained using Taylor approximations of the nonlinear model [7], [8]. In the case of flexible-joint robots, similar approaches are used (approximate linear model [9], Taylor approximation [10]), except for the feedback linearization which is more computationally involved in presence of joint flexibilities.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of two robust predictive control strategies for trajectory tracking of flexible-joint robots

Makarov¹,

Grossard²,

Rodríguez-Ayerbe³

et al. 2014

2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics

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Section: B Robustification Of Gpc Control Lawsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparison of two robust predictive control strategies for trajectory tracking of flexible-joint robots

Makarov¹,

Grossard²,

Rodríguez-Ayerbe³

et al. 2014

2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics

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“…Based on the robot model in the second part of the paper different joint position control concepts will be presented and discussed with respect to the dynamic response and robustness. One of it is the model-based PFC-concept (Predictive Functional Control) which has been developed and successfully applied for industrial robots by the IITB [2]. It will be shown that PFC can also be applied to hydraulic large range robots like EMIR.…”

Section: Motivationmentioning

confidence: 99%

Modelling and Control of a Hydraulic Large Range Robot

Hirsch¹,

Jacubasch²,

Kuntze³

et al. 1991

Proceedings of the 8th International Symposium on Automation and Robotics in Construction (ISARC)

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Large range robots are of increasing importance for various difficult applications at building sites or in hazardous areas. In collaboration with industrial partners the KfK has developed such extended multi joint robot (EMIR) which is driven by hydraulic actuators. The position control of EMIR is a tough problem due to the extreme nonlinearities of the kinematics and hydraulic actuators as well as the remarkable elasticities of the mechanics and hydraulics. In the first part of this paper a realistic physically transparent model of the robot will be presented. In the second part different suitable control concepts based on the model will be discussed.Keywords: Hydraulic large range robot, automatic control, modelling of nonlinearities and elasticity, model-based control concepts MOTIVATIONThere are various important out-door applications in the fields of civil engineering, environmental technoloy or catastrophy management which require necessarily the introduction of a large range robot. Complying with the existing and expected demands of these important future-oriented markets in collaboration with different industrial partners KfK has developed the EMIR robot (Extended Multi Joint Robot) [1]. It is a six-joint machine powered by hydraulic servo drives. The mechanics of the EMIR is characterized by one vertical and five kinematically redundant horizontal joints which provide the robot with an amazing dexterity for complex manipulation tasks. At the TCP (Tool Center Point) the EMIR can carry payloads of up to 1500 kg within a working range of up to 22,5 m. The hydraulic servo drives are cylinders for the five horizontal joints and one rotary actuator for the vertical base joint. The hydraulic oil flow of each actuator will be controlled by means of electro-magnetic (solenoid) servo valves. A safety logic valve between each hydraulic drive and servo valve checks permanetly the fluid pressure within the cylinder in order to prevent uncontrolled hazardous robot motions in the case of any hydraulic malfunctions (cf. Fig. 1). The control hardware is implemented on a conventional AT-386 computer including a signal processor board extension.The static and dynamic system behaviour of the uncontrolled robot is characterized by several difficulties. Mainly due to the kinematics of the joints and the behaviour of the hydraulic actuators the response of the servo system is extremely nonlinear. The nonlinearity depends both on the actual joint position and the velocity. Especially the integrated safety logic block of the actuators seriously disturbs the system dynamics mainly in the case of lowering the TCP. An additional source of trouble for the control design is the spatially distributed elasticity of the slim and huge robot mechanics which is unfortunately superimposed by the elasticity of the hydraulic fluid within the actuators. Because of the highly nonlinear and elastic system behaviour of hydraulic actuators and robot mechanics for the closed-loop position control of the robot joints sophisticated model-bas...

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A predictive functional control algorithm for multivariable systems with time delay

Zhou

Fei

Huang

et al. 2013

J. Control Theory Appl.

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On the application of a new method for fast and robust position control of industrial robots

Cited by 14 publications

References 8 publications

Comparison of two robust predictive control strategies for trajectory tracking of flexible-joint robots

Comparison of two robust predictive control strategies for trajectory tracking of flexible-joint robots

Modelling and Control of a Hydraulic Large Range Robot

A predictive functional control algorithm for multivariable systems with time delay

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