Naoyuki Hara

Model predictive control of DFIG-based wind turbines

This paper deals with model predictive control (MPC) of wind turbines with doubly fed induction generator (DFIG). MPC is applied to the blade speed control, which aims at maximum power extraction from the wind. An MPC controller uses the future prediction of wind speed, and the performance improvement by this preview action is investigated through numerical simulation.

Circular periodic motion generation for mobile robots using limit cycle systems

This paper considers the problem of circular periodic motion generation for nonholonomic mobile robots. By employing a nonlinear system exhibiting limit cycle behavior, we provide a control law that stabilizes a nonholonomic mobile robot to a circular path with the prescribed direction of rotation and speed. Stability of the resulting circular periodic motion of the mobile robot is shown by linear stability analysis of a suitably defined error system. A numerical example is provided to demonstrate the proposed method.

Reduced order model predictive control method based on decomposition of discrete-time linear systems

A reduced order model predictive control method is discussed for constrained discrete-time linear systems. By employing an alternative decomposition of finite-horizon linear systems, a model predictive control method, which works effectively for large systems, is obtained. The proposed method is illustrated with numerical examples.

Experimental verification of synchronization in pulse-coupled oscillators with a refractory period and frequency distribution

We propose herein globally pulse-coupled electronic-circuit oscillators with a refractory period and frequency distribution. The synchronization of such oscillators, which was analyzed by Konishi and Kokame [Chaos 18, 033132 (2008)], is verified by circuit experiments. Furthermore, we investigate a cluster state in the oscillators and analytically derive a simple condition to estimate the maximum possible number of clusters, which is confirmed by the circuit experiments.

Experimental evaluation of model predictive control of ball and beam systems

In this paper, we discuss the control of a ball and beam system subject to an input constraint. Model predictive control (MPC) approaches are employed to derive a nonlinear control law satisfying the constraint. The control law is given by solving the optimization problem at each sample time, where the primal-dual interior point algorithm is implemented and used as the optimization solver. An experimental comparison of three control methods, two different MPCs and saturated LQR, has been presented for the control of the ball and beam system.

Reduced order model predictive control - an approach based on system decomposition -

This paper considers a reduced order model predictive control (MPC) method for constrained discrete-time linear systems. By employing a system decomposition technique for discrete-time linear systems, a reduced order MPC law is derived. The MPC law is improved in terms of control performance and feasibility of the associated optimization problem.

Parallel model predictive control for constrained linear systems

This paper considers a parallel model predictive control (MPC) for input constrained linear systems. A dual of an optimization problem in MPC is decomposed into sub-problems, which can be solved in parallel. The proposed parallel MPC is demonstrated in numerical simulation.

Singular value decomposition for a class of linear time-varying systems with application to switched linear systems

Abstract The present paper considers singular value decomposition (SVD) for a class of linear time-varying systems. The class considered herein describes time-driven switched linear systems. Based on an appropriate input–output description, the calculation method of singular values and singular vectors is derived. The SVD enables us to characterize the dominant input–output signals using singular vectors, which form orthogonal systems in input and output spaces. The SVD is then applied to switched linear systems to improve the transient response. A numerical example is provided to demonstrate the proposed method.

Constrained control based on a decomposition of finite-horizon linear systems

This paper considers a design method of compensation law for constrained linear systems. By investigating the input-output relation of finite-horizon linear systems, we clarify a sequence of input and output signals which describes the dominant system dynamics. A control method is developed based on the proposed decomposition and the fundamental properties of the resulting system are discussed.

Partial state setting of controller for constrained systems

A state setting technique of controller is discussed for constrained linear systems. The relation between the changes of the partial state and the corresponding response is characterized by introducing an extended singular value decomposition (SVD). By employing the SVD, the partial state which fulfills system constraints is derived. The advantage of partial state setting is illustrated with numerical examples