Designing a controller with image-based pipelined sensing and additive uncertainties

Medina, R.; Valencia, J.; Stuijk, S.; Goswami, D.; Basten, T.

doi:10.1145/3326067

Designing a controller with image-based pipelined sensing and additive uncertainties

Title

Designing a controller with image-based pipelined sensing and additive uncertainties

Author

Medina, R.
Valencia, J.
Stuijk, S.
Goswami, D.
Basten, T.

Publication year

2019

Abstract

Pipelined image-based control uses parallel instances of its image-processing algorithm in a pipelined fashion to improve the quality of control. A performance-oriented control design improves the controller settling time with each additional processing resource, which creates a resources-performance trade-off. In real-life applications, it is common to have a continuous-time model with additive uncertainties in one or more parameters that may affect the controller performance and the aforementioned trade-off.We present a robustness analysis framework for performance-oriented pipelined controllers with additive model uncertainties.We present a technique to obtain discrete-time uncertainties based on the continuous-time uncertainties for given uncertainty bounds. To benchmark such uncertainty bounds for a real system, we consider uncertainties in one element of the system, potentially caused by multiple uncertain parameters in the model. Robustness and its impact in the trade-off analysis are studied. We also provide a robustness-oriented pipelined controller design that takes into account the benchmarked uncertainties. Our results show that in performance-oriented designs, the tolerable uncertainties for a pipelined controller decrease when increasing the number of pipes. In robustness-oriented designs, the controller robustness is enhanced with each newly added pipe. We show the feasibility of our technique by implementing a realistic example in a Hardware-in-the-Loop simulation.

Subject

Image-based control
Pipelined sensing control
Robustness analysis
Particle Swarm Optimization
Trade-off analysis
LQR tuning
Hardware-software codesign
Yield and cost optimization
Computer systems organization
Multicore architectures
Embedded hardware
Embedded software
Sensors and actuators