A linear programming approach to design robust input shaping

Broeck, Lynn Van den; Pipeleers, Goele; Caigny, Jan De; Demeulenaere, Bram; Swevers, Jan; Schutter, Joris De

doi:10.1109/amc.2008.4516045

Cited by 9 publications

(9 citation statements)

References 10 publications

(30 reference statements)

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“…Hence, the optimization will restart the factorization of the KKT-matrix. However, this problem is hotstarted by starting the solution from a static controller, which has properties similar to the desired controller [14].…”

Section: Transition Over Timementioning

confidence: 99%

Time optimal MPC for mechatronic applications

Broeck

Diehl

Swevers

2009

Proceedings of the 48h IEEE Conference on Decision and Control (CDC) Held Jointly With 2009 28th Chinese Control Conference

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Model predictive control (MPC) is an on-line control technique originally developed for slow processes which makes an assessment between input effort and output error while respecting constraints on inputs and outputs. Due to improved computing power and algorithms, MPC is nowadays also applied to mechatronic systems. For these systems, achieving minimal settling time is the main concern, while the input cost is usually of less importance. Hence, this paper presents a new type of MPC; time optimal MPC (TOMPC) which minimizes the settling time of the system. Theoretical considerations show that TOMPC is stabilizing. Simulations show the merits of this technique and indicate that it is applicable in real-time.

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Section: Transition Over Timementioning

confidence: 99%

Time optimal MPC for mechatronic applications

Broeck

Diehl

Swevers

2009

Proceedings of the 48h IEEE Conference on Decision and Control (CDC) Held Jointly With 2009 28th Chinese Control Conference

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“…to make it more robust [2], to make it faster by allowing negative impulses [5], or including a priori information about the desired trajectory [3]. It has been shown that the input shaping problem can be reformulated in a more general linear programming framework [8], [9]. This generalization considers the system and prefilter as one system of which the total impulse response has to be shaped; i.e., the input shaping prefilter design considers:…”

Section: A Input Shapingmentioning

confidence: 99%

“…a reference step of 1cm. The considered prefilter is designed following the procedure of [8]. In this procedure, negative impulses are allowed as in the predictive prefilter, and such that no saturation takes place for a reference step of 1cm.…”

Section: B Single Step Benchmarkmentioning

confidence: 99%

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Performant design of an input shaping prefilter via embedded optimization

Broeck

Diehl

Swevers

2009

2009 American Control Conference

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Traditional input shaping filters are linear mappings between the reference input and the system input. These filters are often unnecessarily conservative with respect to input and output bounds if multiple references with different amplitudes are applied. This conservatism is due to the off-line computation of the prefilter. This paper presents an on-line input prefilter design approach to overcome this conservatism. The resulting prefilters are called predictive prefilters because the on-line design is based on the model predictive control (MPC) framework. By theoretical considerations, simulation results and experimental results, it is shown that this new prefilter is at least as good as traditional prefilters, and can result in substantial gains in settling time. Tests show that a 30 % decrease in settling time is possible in a classical application.

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“…The profile design is not strictly a feedforward control; in terms of predicting the characteristics of the plant system, however, the profile design is considered to be a kind of the off-line feedforward control. Recent research has produced the filtering methods that propose suppressing the frequency component around the resonant frequency (5)- (7) . Hence, profile design methods that use the final state control have also been proposed (8)-(11) .…”

Section: Introductionmentioning

confidence: 99%

Vibration Suppression Control based on Final State Control Considering Convergence Time and Inertia Variation for Industrial Robot

et al. 2014

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Industrial robots require high-speed and high-precision motion for improvements in productivity and product quality. However, high-speed motion excites residual vibration because the joint axis of the industrial robot has axial torsion. In addition, the inertia moment of the industrial robot is changed by the end-effector tool. Therefore, robust vibration suppression control is required. However, achieving both robust vibration suppression control and high-speed motion control is difficult. This paper proposes a new final state control method that considers the convergence time and inertia variation for an industrial robot. The proposed method applies final state control to the entire motion control system of each joint. To achieve the desired convergence time for the end-effector, the final state control profile is redesigned by using a proposed flowchart. The effectiveness of the proposed method is confirmed by a numerical simulation and an experiment using a 3-degree-of-freedom robot manipulator.

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A linear programming approach to design robust input shaping

Cited by 9 publications

References 10 publications

Time optimal MPC for mechatronic applications

Time optimal MPC for mechatronic applications

Performant design of an input shaping prefilter via embedded optimization

Vibration Suppression Control based on Final State Control Considering Convergence Time and Inertia Variation for Industrial Robot

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