Exploring the trade-off between processing resources and settling time in image-based control through LQR tuning

Comparing Platform-aware Control Design Flows for Composable and Predictable TDM-based Execution Platforms

“…The literature on platform-aware control design can broadly be classified based on the resource category, namely computation [Aminifar et al 2015[Aminifar et al , 2016Biondi et al 2018;Cervin et al 2003Cervin et al , 2011Medina et al 2017;Samii et al 2009;, communication [Bauer et al 2014;Deng et al 2016;Roy et al 2016], memory [Chang et al 2017], and power [Chang et al 2014].…”

“…The key considerations of computation-aware control design methods are the trade-off analysis between resource usage and control performance, efficient implementation and performance optimisation. A trade-off analysis between the number of processing units used for the control application and the performance is presented in [Medina et al 2017] for data intensive control loops. Integrated communication and computation (priority-based) scheduling for distributed control is solved by constraint logic programming formulation in [Samii et al 2009].…”

“…In order to, minimise the settling time and maximise the QoC as per Equation 7an LQR tuning is used to find the values ofQ andR. In this work, the PSO algorithm of [Medina et al 2017] has been used. This algorithm explores the tuning of theQ andR matrices as a parallel problem.…”

“…Thus, the LQR is tuned to optimise the performance. We use Particle Swarm Optimization (PSO) for the LQR tuning [Medina et al 2017]. We show that the SR design flow is suitable when the demand for the performance is relatively low (i.e., a longer settling time is acceptable).…”

Cross-Domain Modeling and Optimization of High-Speed Visual Servo Systems

“…In [12], couplings between illumination, optics, image sensors, and vision algorithms, as well as their impacts on measurement errors are explored. In [13], effects of processing resource on sample rate, delay, controller gain, and the resulted control performance are examined. In [14], a controller is optimized by taking into account a large delay induced by visual feedback.…”