Robust Feed-Forward/Feedback Design for Tape Transport

Tenne, D.; Singh, Tarunraj

doi:10.2514/6.2004-5119

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…Assuming there is no force loss across the head, the tape tension T � T 1 � T 2 [42]. Although the physical model of the process contains nonlinearities, in (22), a simplified state-space model is presented in continuous time [42][43][44]:…”

Section: Example 1: Tape Transport Systemmentioning

confidence: 99%

Model Predictive Control with a Relaxed Cost Function for Constrained Linear Systems

Sotelo

Favela‐Contreras

Kalashnikov

et al. 2020

Mathematical Problems in Engineering

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The Model Predictive Control technique is widely used for optimizing the performance of constrained multi-input multi-output processes. However, due to its mathematical complexity and heavy computation effort, it is mainly suitable in processes with slow dynamics. Based on the Exact Penalization Theorem, this paper presents a discrete-time state-space Model Predictive Control strategy with a relaxed performance index, where the constraints are implicitly defined in the weighting matrices, computed at each sampling time. The performance validation for the Model Predictive Control strategy with the proposed relaxed cost function uses the simulation of a tape transport system and a jet transport aircraft during cruise flight. Without affecting the tracking performance, numerical results show that the execution time is notably decreased compared with two well-known discrete-time state-space Model Predictive Control strategies. This makes the proposed Model Predictive Control mainly suitable for constrained multivariable processes with fast dynamics.

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Section: Example 1: Tape Transport Systemmentioning

confidence: 99%

Model Predictive Control with a Relaxed Cost Function for Constrained Linear Systems

Sotelo

Favela‐Contreras

Kalashnikov

et al. 2020

Mathematical Problems in Engineering

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“…The input shapers and the time-delay filters assume that the system being studied is stable. The effect of the feedback controller on the prefilter has recently been studied by Kenison and Singhose [3], Muenchhof and Singh [13], Tenne and Singh [12] etc. Kenison and Singhose [3] study the problem of simultaneous design of a PD controller and an Input shaper for a double integrator.…”

Section: Introductionmentioning

confidence: 99%

“…They illustrated their controller on the benchmark floating oscillator problem. The minimax design problem is computationally expensive and to address this issue, Tenne and Singh [12], proposed to exploit the Unscented Transformation to represent the distribution of the cost function as a function of the distribution of the uncertain model parameters. They solved the minimax problem where the cost is a combination of the residual energy, maneuver time and the integral of a quadratic cost of the states and control.…”

Section: Introductionmentioning

confidence: 99%

Concurrent Feedback/Feedforward Design for Second Order Systems

Gopalakrishnan

Reddy

Singh

2005

AIAA Guidance, Navigation, and Control Conference and Exhibit

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This paper studies the problem of concurrent design of a feedback controller and a pre-filter to minimize a weighted cost comprising the maneuver time and the input power. The pre-filter is parameterized as a time-delay filter motivated by the Posicast controller. The proposed technique is illustrated on a double integrator assuming that the feedback controller is of the proportional derivative form. A closed form expression relating the weighting parameter and the number of delays, to the feedback gains is derived. The proposed technique is also illustrated on spring-mass and springmass-dashpot systems.

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A New Software-Based Optimization Technique for Embedded Latency Improvement of a Constrained MIMO MPC

et al. 2022

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Embedded controllers for multivariable processes have become a powerful tool in industrial implementations. Here, the Model Predictive Control offers higher performances than standard control methods. However, they face low computational resources, which reduces their processing capabilities. Based on pipelining concept, this paper presents a new embedded software-based implementation for a constrained Multi-Input-Multi-Output predictive control algorithm. The main goal of this work focuses on improving the timing performance and the resource usage of the control algorithm. Therefore, a profiling study of the baseline algorithm is developed, and the performance bottlenecks are identified. The functionality and effectiveness of the proposed implementation are validated in the NI myRIO 1900 platform using the simulation of a jet transport aircraft during cruise flight and a tape transport system. Numerical results for the study cases show that the latency and the processor usage are substantially reduced compared with the baseline algorithm, 4.6× and 3.17× respectively. Thus, efficient program execution is obtained which makes the proposed software-based implementation mainly suitable for embedded control systems.

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Robust Feed-Forward/Feedback Design for Tape Transport

Cited by 3 publications

References 8 publications

Model Predictive Control with a Relaxed Cost Function for Constrained Linear Systems

Model Predictive Control with a Relaxed Cost Function for Constrained Linear Systems

Concurrent Feedback/Feedforward Design for Second Order Systems

A New Software-Based Optimization Technique for Embedded Latency Improvement of a Constrained MIMO MPC

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