This paper proposes a new LMI approach to analysis of linear systems depending on scheduling parameter in polynomial forms: we first propose a method to reduce the parameter dependent LMI condition, which characterizes internal stability and L 2 gain, to the finite number of LMI conditions by introducing a convex polyhedron which includes a polynomial curve parameterized by scheduling parameter; next we propose a systematic procedure to construct the convex polyhedron. Our approach enable us to analyze L 2 gain of linear systems with scheduling parameter in polynomial forms through computation of the finite number of LMIs. To show efficacy of our approach, we finally make a numerical experiment of L 2 gain analysis for a gasturbine engine model which is described as a linear system with a scheduling parameter in polynomial form of two degree.
In this paper, an method to system identification over networks using 1 bit delta-sigma transformation is proposed and the efficacy of the proposed method is verified based on experimental results. Accurate mathematical models are needed to achieve intelligent control with good performances in control engineering. It is easy to obtain those mathematical models if exact input-output data of a controlled object is available by applying system identification techniques. However it is difficult to obtain the exact input-output data over networks because the data is transformed from analog data into digital data. The proposed method provides a method to build mathematical models of controlled objects over networks.
This paper considers vision-based motion control with the manipulator dynamics using position measurements and visual information, which we term dynamic visual feedback control. Firstly the visual feedback system of rigid body motion is described in order to derive the dynamic visual feedback system. Secondly we propose a dynamic visual feedback control law which guarantees local asymptotic stability of the overall closed-loop system using a Lyapunov function. L2-gain performance analysis for the proposed control law has been discussed using the energy function which plays the role of a storage function. Next, we show that the control law is based on passivity and the dynamic visual feedback system is constructed from two passive systems. Finally simulation results confirm the effectiveness of the dynamic visual feedback control law.
This paper considers a design problem of controllers for our developed networked control system based on state predictive control. Our developed system consists of a wire-less vehicle, a router in a computer network and a computer as the controller. Because the router has an AQM mechanism to keep the queue size constant, our networked control system can be described as linear systems with an input time-delay. Thus the state predictive controller with an integrator can be applied to stabilize our developed networked control system. The efficacy of the designed controller is demonstrated in a numerical example.
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This paper considers a least-squares method for state space models by using periodic signals and two theoretical properties of the least-squares method are shown. Moreover the least-squares method considered in this paper is applied to an estimation problem of protein networks for cell cycle in budding yeast. The derived properties of the least-squares method are verified in the estimation problem and the approach to estimate protein networks for cell cycle is demonstrated.
In this paper, we consider dynamical models of computer networks and derive a synthesis method for stabilizing congestion controllers. Moreover we verify the efficacy of the designed stabilizing congestion controllers using our developed network testbed. First we show dynamical models of TCP/AQM (transmission control protocol/active queue management) networks. The dynamical models of TCP/AQM networks consists of models of TCP window size, queue length and AQM mechanisms. Second we propose to describe the dynamical models of TCP/AQM networks as linear systems with self-scheduling parameters, which also depend on information delay. Here we focus on the constraints on the maximum queue length and TCP window-size, which are the network resources in TCP/AQM networks. Linear system with a self-scheduling parameter and an information delay are derived for dynamical models of TCP/AQM networks. We show a design method of memoryless state feedback controllers for derived linear system with a self-scheduling parameter and an information delay. Finally the effectiveness of the proposed method is evaluated by using ns-2 (Network Simulator Ver.2) simulator and our developed network testbed.
This paper discusses a robustness analysis of a 10 dimensional cell cycle system and focuses on understanding functions of Cdc25 and Weel proteins. The robustness of the cell cycle is analyzed based on the sensitivity analysis for a mathematical model. From the first analysis result, it was shown that Cdc2 and Cyclin proteins have main roles for cell cycle in this model but the robustness is not high against perturbation on its parameters. By introducing Cdc25 and Weel proteins to the mathematical model, it was verified by the sensitivity analysis that the modified has higher level of robustnesses than the original model does. Numerical examples are shown to demonstrate the original model and the modified model have almost identical cell cycle behaviors leaving robustness as a salient difference.
This paper discusses a robustness analysis of eukaryotic cell cycle and focuses on understanding functions of Cdc25 and Weel proteins. The robustness of the eukaryotic cell cycle is analyzed based on the sensitivity analysis for a mathematical model. From the first analysis result, it was shown that Cdc2 and Cyclin proteins have main roles for eukaryotic cell cycle in this model but the robustness is not high against perturbation on its parameters. By introducing Cdc25 and Weel proteins to the mathematical model, it was verified by the sensitivity analysis that the modified has higher level of robustnesses than the original model does. Numerical examples are shown to demonstrate the original model and the modified model have almost identical cell cycle behaviors leaving robustness as a salient difference
