Tomonori Sadamoto

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In this paper, we propose a design method of hierarchical distributed controllers for networked linear systems. The hierarchical distributed controller has an advantage that an L2-performance of the closed-loop system improves as improving a performance of local controllers that stabilize disjoint subsystems individually. Towards systematic design, we(More)
In this paper, towards efficient state estimation for large-scale linear systems, we propose a novel framework of low-dimensional functional state observers, which we call a projective state observer, with the provision of a systematic design procedure. The projective state observer can be regarded as a generalization of functional state observers that is(More)
This paper is concerned with how to develop a new system control theory for providing systematic design methods of hierarchical networked systems composed of various kinds of subsystems from the glocal (global/local) control view point. Through examinations of energy network control we first explain the idea and concept of glocal control and propose a(More)
In this paper, we propose a design method of hierarchical decentralized observers for networked linear systems. In this method, based on suitable state-space expansion of the network systems, we, first, find a high-dimensional dynamical compensator that can achieve ideal performance for decentralized state estimation. Next, fully utilizing model reduction(More)
In this paper, we propose an algorithm of adaptive optimal control scheme for systems whose dynamics are unknown and the states are contaminated by noises. The basic control law is Policy Iteration which can solve HJB equation recursively. In the proposed method, the value function is estimated using a nonlinear filtering but the state of the system is not(More)
In this paper, we construct a nonlinear reduced order model of a plasticization cylinder of injection machines, which has a spatially distributed nonlinear dynamics. First, a distributed parameter model for the overall control system is derived based on the physical laws. Next, we attempt to reduce the model complexity focusing on the specific structure of(More)
In this paper, we propose a design method of average state Kalman filters for networked linear systems with stochastic noises. The average state Kalman filter is a low-dimensional estimator capturing the average behavior of systems from a macroscopic point of view. In general, it is nontrivial to find a set of states that captures the average behavior of(More)
In this paper we address the growing concerns of wind power integration from the perspective of power system dynamics and stability. We propose a new retrofit control technique where an additional controller is designed at the doubly-fed induction generator site inside the wind power plant. This controller cancels the adverse impacts of the power flow from(More)
In this paper, we propose a retrofit control method for stable network systems. The proposed approach is a decentralized control method that, rather than an entire system model, requires a model of the subsystem of interest for controller design. To design the retrofit controller, we use a novel approach based on hierarchical state-space expansion that(More)