arXiv subjects

Takeshi Sano

Publications and source records attributed to Takeshi Sano.

5 recordsLinked to original sources

arXiv2020

Tuning of multivariable model predictive controllersthrough expert bandit feedback

For certain industrial control applications an explicit function capturing the nontrivial trade-off between competing objectives in closed loop performance is not available. In such scenarios it is common practice to use the human innate ability to implicitly learn such a relationship and manually tune the corresponding controller to achieve the desirable closed loop performance. This approach has its deficiencies because of individual variations due to experience levels and preferences in the absence of an explicit calibration metric. Moreover, as the complexity of the underlying system and/or the controller increase, in the effort to achieve better performance, so does the tuning time and the associated tuning cost. To reduce the overall tuning cost, a tuning framework is proposed herein, whereby a supervised machine learning is used to extract the human-learned cost function and an optimization algorithm that can efficiently deal with a large number of variables, is used for optimizing the extracted cost function. Given the interest in the implementation across many industrial domains and the associated high degree of freedom present in the corresponding tuning process, a Model Predictive Controller applied to air path control in a diesel engine is tuned for the purpose of demonstrating the potential of the framework.

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arXiv2019

Fast Calibration of a Robust Model Predictive Controller for Diesel Engine Airpath

A significant challenge in the development of control systems for diesel airpath applications is to tune the controller parameters to achieve satisfactory output performance, especially whilst adhering to input and safety constraints in the presence of unknown system disturbances. Model-based control techniques, such as model predictive control (MPC), have been successfully applied to multivariable and highly nonlinear systems, such as diesel engines, while considering operational constraints. However, efficient calibration of typical implementations of MPC is hindered by the high number of tuning parameters and their non-intuitive correlation with the output response. In this paper, the number of effective tuning parameters is reduced through suitable structural modifications to the controller formulation and an appropriate redesign of the MPC cost function to aid rapid calibration. Furthermore, a constraint tightening-like approach is augmented to the control architecture to provide robustness guarantees in the face of uncertainties. A switched linear time-varying MPC strategy with recursive feasibility guarantees during controller switching is proposed to handle transient operation of the engine. The robust controller is first implemented on a high fidelity simulation environment, with a comprehensive investigation of its calibration to achieve desired transient response under step changes in the fuelling rate. An experimental study then validates and highlights the performance of the proposed controller architecture for selected tunings of the calibration parameters for fuelling steps and over drive cycles.

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arXiv2019

Model Predictive Controller with Average Emissions Constraints for Diesel Airpath

Diesel airpath controllers are required to deliver good tracking performance whilst satisfying operational constraints and physical limitations of the actuators. Due to explicit constraint handling capabilities, model predictive controllers (MPC) have been successfully deployed in diesel airpath applications. Previous MPC implementations have considered instantaneous constraints on engine-out emissions in order to meet legislated emissions regulations. However, the emissions standards are specified over a drive cycle, and hence, can be satisfied on average rather than just instantaneously, potentially allowing the controller to exploit the trade-off between emissions and fuel economy. In this work, an MPC is formulated to maximise the fuel efficiency whilst tracking boost pressure and exhaust gas recirculation (EGR) rate references, and in the face of uncertainties, adhering to the input, safety constraints and constraints on emissions averaged over some finite time period. The tracking performance and satisfaction of average emissions constraints using the proposed controller are demonstrated through an experimental study considering the new European drive cycle.

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arXiv2015

New class of biological detectors for WIMPs

Weakly Interacting Massive Particles (WIMPs) may constitute a large fraction of the matter in the Universe. There are excess events in the data of DAMA/LIBRA, CoGeNT, CRESST-II, and recently CDMS-Si, which could be consistent with WIMP masses of approximately 10 GeV/c2. However, for MDM > 10 GeV/c2 null results of the CDMS-Ge, XENON, and LUX detectors may be in tension with the potential detections for certain dark matter scenarios and assuming a certain light response. We propose the use of a new class of biological dark matter (DM) detectors to further examine this light dark matter hypothesis, taking advantage of new signatures with low atomic number targets, Two types of biological DM detectors are discussed here: DNA-based detectors and enzymatic reactions (ER) based detectors. In the case of DNA-based detectors, we discuss a new implementation. In the case of ER detectors, there are four crucial phases of the detection process: a) change of state due to energy deposited by a particle; b) amplification due to the release of energy derived from the action of an enzyme on its substrate; c) sustainable but non-explosive enzymatic reaction; d) self-termination due to the denaturation of the enzyme, when the temperature is raised. This paper provides information of how to design as well as optimize these four processes.

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arXiv2015

New Dark Matter Detectors using DNA or RNA for Nanometer Tracking

Weakly Interacting Massive Particles (WIMPs) may constitute most of the matter in the Universe. The ability to detect the directionality of recoil nuclei will considerably facilitate detection of WIMPs. In this paper we propose a novel type of dark matter detector: detectors made of DNA or RNA could provide nanometer resolution for tracking, an energy threshold of 0.5 keV, and can operate at room temperature. When a WIMP from the Galactic Halo elastically scatters off of a nucleus in the detector, the recoiling nucleus then traverses hundreds of strings of single stranded nucleic acids (ssNA) with known base sequences and severs ssNA strands along its trajectory. The location of the break can be identified by amplifying and identifying the segments of cut ssNA using techniques well known to biologists. Thus the path of the recoiling nucleus can be tracked to nanometer accuracy. In one such detector concept, the transducers are nanometer-thick Au-foils of 1m x 1m, and the direction of recoiling nuclei is measured by "NA Tracking Chamber" consisting of ordered array of ssNA strands. Polymerase Chain Reaction (PCR) and ssNA sequencing are used to read-out the detector. The proposed detector is smaller and cheaper than other alternatives: 1 kg of gold and 0.1 to 4 kg of ssNA (depending on length and strand density), packed into 0.01m$^3$, can be used to study 10 GeV WIMPs. A variety of other detector target elements could be used in this detector to optimize for different WIMP masses and to identify WIMP properties. By leveraging advances in molecular biology, we aim to achieve about 1,000-fold better spatial resolution than in conventional WIMP detectors at reasonable cost.

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