Semi-Markov jump linear systems with bi-boundary sojourn time: Anti-modal-asynchrony control

This paper investigates the problem of control synthesis for a class of discrete-time semi-Markov jump linear systems, in which the sojourn time of each mode is bi-boundary (with upper and lower bounds). The system is subject to modal asynchrony, which means that the switchings of the mode-dependent controller to be designed lag behind the ones of the controlled plant, and the lag is mode-dependent. In contrast with the traditional mode-independent lag commonly assumed in the existing studies, not only is the modal lag more practical and general, but also it yields less conservatism of the controller design. By virtue of the semi-Markov kernel approach, the conditions on the existence of the anticipated stabilizing controllers capable of overcoming the modal asynchrony are derived. Illustrative examples including a class of vertical take-off and landing (VTOL) helicopter models are presented to demonstrate the necessity and the validity of the designed anti-modal-asynchrony controllers

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

A survey on multi-agent reinforcement learning and its application

Multi-agent reinforcement learning (MARL) has been a rapidly evolving field. This paper presents a comprehensive survey of MARL and its applications. We trace the historical evolution of MARL, highlight its progress, and discuss related survey works. Then, we review the existing works addressing inherent challenges and those focusing on diverse applications. Some representative stochastic games, MARL means, spatial forms of MARL, and task classification are revisited. We then conduct an in-depth exploration of a variety of challenges encountered in MARL applications. We also address critical operational aspects, such as hyperparameter tuning and computational complexity, which are pivotal in practical implementations of MARL. Afterward, we make a thorough overview of the applications of MARL to intelligent machines and devices, chemical engineering, biotechnology, healthcare, and societal issues, which highlights the extensive potential and relevance of MARL within both current and future technological contexts. Our survey also encompasses a detailed examination of benchmark environments used in MARL research, which are instrumental in evaluating MARL algorithms and demonstrate the adaptability of MARL to diverse application scenarios. In the end, we give our prospect for MARL and discuss their related techniques and potential future applications

Stability analysis and stabilization of semi-Markov jump linear systems with improved efficiency of probabilistic information utilization

This article establishes a systematic methodology to improve the utilization efficiency of probabilistic information for the stability analysis and stabilizing control of discrete-time semi-Markov jump linear systems (SMJLSs). The transition and sojourn information is incompletely known, and the coupling between the known (or unknown) transition and unknown (or known) sojourn information renders the known probabilistic information difficult to be fully leveraged, which can lead to conservative results in system analysis and synthesis. To approximate the unknown transition and sojourn information, a polyhedral approach is developed, which facilitates the incorporation of the known probabilistic information coupled with unknown information. Accordingly, novel vertex-based Lyapunov functions are proposed to establish stability conditions. New criteria are established for the stability analysis and control of SMJLSs by incorporating all the jointly known transition and sojourn information, all the known probabilistic information, and both the known and the approximation of unknown probabilistic information, respectively. The effectiveness and superiority of the theoretical results are illustrated by a numerical example and a simulated continuous stirred tank reactor process.Ministry of Education (MOE)National Research Foundation (NRF)Public Utilities Board (PUB)Submitted/Accepted versionThis research is supported by the National Research Foundation, Singapore, and PUB, Singapore’s National Water Agency under its RIE2025 Urban Solutions and Sustainability (USS) (Water) Centre of Excellence (CoE) Programme, awarded to Nanyang Environment & Water Research Institute (NEWRI), Nanyang Technological University (NTU), Singapore. This research is also supported in part by Ministry of Education, Singapore, under its Academic Research Fund Tier 1 (RS15/21 & RG63/22), and in part by the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship, a program of Schmidt Futures

Asynchronous quantized control of piecewise-affine systems

This technical note proposes a novel asynchronous control approach for discrete-time piecewise-affine (PWA) systems with logarithmic quantization of both multi-inputs and multi-state measurements. Since the actual system state and the quantized state may not always be in the same operating region due to quantization-induced uncertainties, the operating modes of the PWA system and the controller which depends on the quantized states may be asynchronous. Aiming at reducing the computational cost and the conservatism of the results, a mapping region-based algorithm is first proposed to determine the reachable dwelling regions for the quantized state. By using a convex combination model to approximate the quantization-induced uncertainties, a novel piecewise Lyapunov function taking into consideration the uncertainties is then proposed. It is shown that with the newly proposed Lyapunov function, the desired asynchronous controller can be obtained and the resulting closed-loop system is asymptotically stable. A simulated chemical reactor example is presented to illustrate the effectiveness and the superiority of the proposed asynchronous control approach.Ministry of Education (MOE)Nanyang Technological UniversitySubmitted/Accepted versionThis work is supported by Ministry of Education, Singapore, under its Academic Research Fund Tier 1 (RS15/21), and Nanyang Technological University, Singapore (Start-Up Grant)