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Hybrid Model Predictive Control Based on Wireless Sensor Feedback: An Experimental Study
"... Abstract — This paper presents the design and the experimental validation of model predictive control (MPC) of a hybrid dynamical process based on measurements collected by a wireless sensor network. The proposed setup is the prototype of an industrial application in which a remote station controls ..."
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Abstract — This paper presents the design and the experimental validation of model predictive control (MPC) of a hybrid dynamical process based on measurements collected by a wireless sensor network. The proposed setup is the prototype of an industrial application in which a remote station controls the process via wireless network links. The experimental platform is a laboratory process consisting of four infrared lamps, controlled in pairs by two on/off switches, and of a transport belt, where moving parts equipped with wireless sensors are heated by the lamps. By approximating the stationary heat spatial distribution as a piecewise affine function of the position along the belt, the resulting plant model is a hybrid dynamical system. The control architecture is based on the reference governor approach: the process is actuated by a local controller, while a hybrid MPC algorithm running on a remote base station sends optimal belt velocity set-points and lamp on/off commands over a network link exploiting the information received through the wireless network. A discrete-time hybrid model of the process is used for the hybrid MPC algorithm and for the state estimator. I.
Stochastic Optimal Control for Hybrid Systems with Uncertain Discrete Dynamics
"... Abstract — This paper considers the task of computing (sub-) optimal continuous and discrete control trajectories for hybrid systems with a probabilistic discrete transition structure. The discrete inputs are used to block undesired transitions and to realize evolutions that are goal-attaining with ..."
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Abstract — This paper considers the task of computing (sub-) optimal continuous and discrete control trajectories for hybrid systems with a probabilistic discrete transition structure. The discrete inputs are used to block undesired transitions and to realize evolutions that are goal-attaining with high probability. An approach is proposed which combines the computation of discrete shortest-paths for given probability-levels with embedded continuous optimal control problems to fix the continuous controls. The result is a control strategy which leads to a system evolution that maximizes a weighted sum of performance and probability of success. The approach is illustrated for an automated transportation scenario. I.
Optimal control of gene regulatory networks with effectiveness of multiple drugs: a boolean network approach,”
- BioMed Research International,
, 2013
"... Developing control theory of gene regulatory networks is one of the significant topics in the field of systems biology, and it is expected to apply the obtained results to gene therapy technologies in the future. In this paper, a control method using a Boolean network (BN) is studied. A BN is widel ..."
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Cited by 3 (3 self)
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Developing control theory of gene regulatory networks is one of the significant topics in the field of systems biology, and it is expected to apply the obtained results to gene therapy technologies in the future. In this paper, a control method using a Boolean network (BN) is studied. A BN is widely used as a model of gene regulatory networks, and gene expression is expressed by a binary value (0 or 1). In the control problem, we assume that the concentration level of a part of genes is arbitrarily determined as the control input. However, there are cases that no gene satisfying this assumption exists, and it is important to consider structural control via external stimuli. Furthermore, these controls are realized by multiple drugs, and it is also important to consider multiple effects such as duration of effect and side effects. In this paper, we propose a BN model with two types of the control inputs and an optimal control method with duration of drug effectiveness. First, a BN model and duration of drug effectiveness are discussed. Next, the optimal control problem is formulated and is reduced to an integer linear programming problem. Finally, numerical simulations are shown.
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"... An integer programming approach to optimal control problems in context-sensitiveprobabilisticBooleannetworks Koichi Kobayashi a, Kunihiko Hiraishi a, ..."
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An integer programming approach to optimal control problems in context-sensitiveprobabilisticBooleannetworks Koichi Kobayashi a, Kunihiko Hiraishi a,
Trends in systems and signals Status report prepared by the IFAC Coordinating Committee on Systems and Signals
, 2006
"... This report discusses problems and methodologies that lie in the broad scope of systems and signals, with special focus on modeling, identification and signal processing; adaptation and learning; discrete event and hybrid systems; and stochastic systems. A common theme underlying all these areas is ..."
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This report discusses problems and methodologies that lie in the broad scope of systems and signals, with special focus on modeling, identification and signal processing; adaptation and learning; discrete event and hybrid systems; and stochastic systems. A common theme underlying all these areas is that problems in control systems and signals are usually defined and best studied in the framework of stochastic approaches. Although there are common precepts among all these technologies, there are also many unique topics within each area. Therefore, the current key problems in each technology are explained, followed by a discussion of recent major accomplishments with trends, and finally some forecasts of likely developments are provided. The conclusion summarizes some general forecasts for the overall field of systems and signals.
Deliverable number D3.7.1 Title Work package WP3
, 2007
"... Actual submission date 10/08/2007 v1.1 Organisation name(s) of lead contractor for this deliverable Author(s) Report on tools and methods for the description and execution of stochastic hybrid models ETH ..."
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Actual submission date 10/08/2007 v1.1 Organisation name(s) of lead contractor for this deliverable Author(s) Report on tools and methods for the description and execution of stochastic hybrid models ETH
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"... Abstract — We develop a notion of approximate bisimulation for a class of stochastic hybrid systems, namely, the jump linear stochastic systems (JLSS). The idea is based on the construction of the so called stochastic bisimulation function. With this function, we can quantify the distance between tw ..."
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Abstract — We develop a notion of approximate bisimulation for a class of stochastic hybrid systems, namely, the jump linear stochastic systems (JLSS). The idea is based on the construction of the so called stochastic bisimulation function. With this function, we can quantify the distance between two jump linear stochastic systems. The function is then used to quantify the distance between a given JLSS and its abstraction, and hence quantify the quality of the abstraction. We show that this idea can be applied to simplify safety verification for JLSS. We also show that in the absence of input, and by assuming that the stochastic bisimulation function is of quadratic form, we can pose the construction as a tractable linear matrix inequality problem.
Stability Analysis of Hybrid Jump Linear Systems with Markov Inputs
"... Abstract — Hybrid jump linear systems (HJLS’s) were introduced to study the properties of supervisory control systems. In a recent publication, a mean square (MS) stability test was introduced for HJLS’s with Moore output maps and i.i.d. inputs. In this paper, a similar test is developed for HJLS’s ..."
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Abstract — Hybrid jump linear systems (HJLS’s) were introduced to study the properties of supervisory control systems. In a recent publication, a mean square (MS) stability test was introduced for HJLS’s with Moore output maps and i.i.d. inputs. In this paper, a similar test is developed for HJLS’s of this type but with Markov inputs. The test requires one to first construct an auxiliary HJLS with equivalent stability properties. Then, a particular matrix, A, is constructed taking into consideration the auxiliary system’s structure and associated Markov kernel. Finally, the spectral radius of A is compared against 1 to determine the stability of the original HJLS. N ( k) Supervisor x ( k) A/S � ( k)
Research Article Optimal Control of Gene Regulatory Networks with Effectiveness of Multiple Drugs: A Boolean Network Approach
"... Copyright © 2013 K. Kobayashi and K. Hiraishi.This is an open access article distributed under the Creative CommonsAttribution License, which permits unrestricted use, distribution, and reproduction in anymedium, provided the originalwork is properly cited. Developing control theory of gene regulato ..."
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Copyright © 2013 K. Kobayashi and K. Hiraishi.This is an open access article distributed under the Creative CommonsAttribution License, which permits unrestricted use, distribution, and reproduction in anymedium, provided the originalwork is properly cited. Developing control theory of gene regulatory networks is one of the significant topics in the field of systems biology, and it is expected to apply the obtained results to gene therapy technologies in the future. In this paper, a control method using a Boolean network (BN) is studied. A BN is widely used as a model of gene regulatory networks, and gene expression is expressed by a binary value (0 or 1). In the control problem,we assume that the concentration level of a part of genes is arbitrarily determined as the control input. However, there are cases that no gene satisfying this assumption exists, and it is important to consider structural control via external stimuli. Furthermore, these controls are realized by multiple drugs, and it is also important to consider multiple effects such as duration of effect and side effects. In this paper, we propose a BNmodel with two types of the control inputs and an optimal control method with duration of drug effectiveness. First, a BN model and duration of drug effectiveness are discussed. Next, the optimal control problem is formulated and is reduced to an integer linear programming problem. Finally, numerical simulations are shown. 1.
Stability Analysis of Stochastic Hybrid Jump Linear Systems Using a Markov Kernel Approach
"... Abstract—In this paper, the state dynamics of a supervisor im-plemented with a digital sequential system are represented with a finite state machine (FSM). The supervisor monitors a symbol sequence derived from a linear closed-loop system’s performance and generates a switching signal for the closed ..."
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Abstract—In this paper, the state dynamics of a supervisor im-plemented with a digital sequential system are represented with a finite state machine (FSM). The supervisor monitors a symbol sequence derived from a linear closed-loop system’s performance and generates a switching signal for the closed-loop system. The ef-fect of random events on the performance of the closed-loop system is analyzed by adding an exogenous Markov process input to the FSM, and by appropriately augmenting a switched system repre-sentation of the supervisor and the closed-loop system. For this class of hybrid jump linear systems, the switching signal is, in gen-eral, a non-Markovian process, making it hard to analyze its sta-bility properties. This is ameliorated by introducing a sufficient mean square stability test that uses only upper bounds on the one-step transition probabilities of the switching signal. These bounds are explicitly derived from aMarkov kernel associated with the hy-brid system model. This stability test becomes necessary and suffi-cient when the switching signal is Markovian. To determine tighter stability bounds, procedures to determine the upper-bound tran-sition probability matrices when the FSM has a Moore or a Mealy type output map are presented. Two examples illustrate the appli-cability of the presented results. Index Terms—Finite state machine (FSM), hybrid systems,
