Generalized minimum variance control (GMVC) is a control method that is widely used in industrial applications such as process control, similarly to model predictive control (MPC). Previous studies have proposed self-tuning controllers based on the transfer function approach, where parameter updating is suspended when the estimation error becomes zero. However, little research has focused on the state-space approach. In this paper, a new self-tuning controller based on the state-space approach is proposed. This controller uses an adaptive observer and suspends parameter updating when either the estimation error or the control error becomes zero. The effectiveness of the proposed method is demonstrated through a numerical example.

A self-tuning controller achieves its control objectives by adaptively adjusting the parameters of the controlled plant or the controller itself, and it has been a topic of research in recent years. This paper proposes a new method for adjusting the size of the estimation error in the parameter identification law using closed-loop data. The proposed self-tuning controller features a mechanism where parameter identification is suspended when the tracking error between the reference signal and the output reaches zero. The effectiveness of the proposed controller is demonstrated through a numerical example.

Generalized Predictive Control (GPC) is one of the model-based control methods. The control law is derived by a performance index consisting of the error between the reference signal and the output prediction, and the sum of squares of the control inputs. In recent research, we proposed a new output prediction and extended the control law so that the disturbance response characteristics can be adjusted without changing the output response characteristics. However, there was a problem that the amount of calculation increased when using the self-tuning controller. Therefore, in this paper, we propose a method to reduce the computational complexity while enabling readjustment of the disturbance response characteristics without changing the closed-loop characteristics by adopting a new method to reduce the computational complexity of the control law. The effectiveness of the proposed method is demonstrated by numerical simulations.

This paper gives an optimal control law to eliminate ripples in inter-sample intervals of transient state of multi-rate sampled-control systems. As for ripples in steady state, there already exist several methods to remove the ripples. But to reduce the ripples in transient-state, so far there exists only trial and error method and there does not exist a systematic method. In this paper, first a reference model is defined which generates a reference output with no ripples and at sampled points, it has the same outputs with continuous time multi-rate control systems. Then the ripples in transient state are measured by the integrals of squared output errors. And equations to calculate the integrals are given by solving of Lyapunov equations. Finally the optimal control law is derived by differentiating the equations by the control input. The obtained optimal control input has a state feedback form and can be calculated at the short sampling time.

This paper explores a strong stability system, which regulates safety for generalized minimum variance control (GMVC). GMVC is one of the control methods for application in industry and the controller is designed by generalized output to make the closed-loop system stable. Once the generalized output is designed, the derived controller cannot be re-designed without changing the closed-loop characteristic. For safe applications in industry, it is desirable that both of the closed-loop system and the controller are stable. That is, the strong stability system, which means that both of the closed-loop system and the controller are stable, is desirable to develop the applications. Although authors have proposed the extended GMVC design methods and the strong stability systems by using coprime factorization, there is a problem that the degree of controller may be higher than the conventional method because stable polynomial is needed in order to obtain coprime factorization. Therefore this paper directly extends GMVC without coprime factorization, and a strong stability system regulating safety is studied from the view point of the quantity of feedback signal. Some numerical examples are shown in order to check the characteristic of the proposed method.

This paper deals with estimation of thermal conductivity for temperature control of an aluminum plate considering radiative heat transfer. Aiming at accurate control results, model-based control method needs true values of plant parameters. In our previous research, the nominal values of plant parameters have been used for temperature control experiment. However, for the actual environment in industrial field, physical parameters such as thermal conductivity will change. Therefore this paper reports the estimation result of thermal conductivity of aluminum plate considering radiative heat transfer through experimental data.

The demand is growing that a robot manipulates a deformable object. Scenarios for both of a grasping point and transfer of grasped point are required, in order to manipulate a deformable object by a robot. Therefore, it is important for a robot to recognize its form by using image information. In this paper, three-dimensional points groups of a string are obtained by a camera that has distance measure equipment. A shape model called “point chain model” is obtained from points group based on proposed algorithm. In this algorithm, first, points which are estimated to be outside of target object are removed from obtained points groups. Secondly, points groups obtained from various viewpoints are combined to reconstruct three-dimensional shape of a string. Thirdly, central axes of a string are abstracted from combined points groups. Finally, central axes are chained to construct the point chain model. Effectiveness of proposed algorithm is confirmed by experiment.

In this paper, we propose a new index of dynamic manipulability for humanoid robot to estimate dynamic ability to change configuration by using remaining redundancy, while prior task is being controlled, e.g., face and eyes being directed to some object. Several indexes have been proposed so far to measure statical and dynamical capability of robot manipulator. For example, Dynamic Manipulability Ellipsoid (DME) describes a distribution of hand acceleration produced by normalized joint torque. On the other hand, Reconfiguration Manipulability Ellipsoid (RME) denotes a distribution of each link velocity produced by joint angular velocity. This paper shows new index of Dynamic Reconfiguration Manipulability (DRM) combined dynamic manipulability and reconfiguration manipulability, and we have adopted the DRM to a humanoid robot, exhibiting how the DRM indicates directly the configuration-changeability of walking humanoid robot.

Biped locomotion created by a controller based on Zero-Moment Point (ZMP) known as reliable control method looks different from human's walking on the view point that ZMP-based walking does not include falling state. However, the walking control that does not depend on ZMP is vulnerable to turnover. Therefore, keeping the walking of dynamical motion stable is inevitable issue for realization of human-like natural walking-we call the humans' walking that includes turning over states as “natural.” In our research group, walking model including slipping, impact, surface-contacting and point-contacting of foot has been developed. Although “Visual Lifting Stabilization” (VLS) strategy has been also proposed in order to enhance standing robustness and prevent the robot from falling down without utilizing ZMP, the torque generation strategy making lifted-leg step forward is derived by trial and error. Therefore, as a first step to realize humans' walking, this paper explores two degree-of-freedom generalized predictive control (GPC) method in order to generate the torque making lifted-leg step forward. Simulation results indicate that this strategy helps stabilize bipedal walking even though ZMP is not kept inside convex hull of supporting area.

In the model of the constrained dynamic system of a rigid robot contacting with rigid environment, constrained forces can be expressed as an algebraic function of states (instantaneous process) and a redundancy existing in constraint dynamics (constraint redundancy). Using these results, a force and position control law is proposed by taking the advantages of the redundancy of input generalized forces to the constrained forces and instantaneous process without involving any force sensor, using dual nature of constraint motion stated in this document. Then proof confirming by Lyapunov method that the exerting force equals instantaneously and constantly to desired one and that the motion of robot's hand in a movable space converges to desired hand's position. The effectiveness has been confirmed by a 2-link robot in simulations.

In this paper, we focus on how to control the robot end-effector to track an object, meanwhile, to approach it with a suitable posture for grasping. We named it "Approaching Visual Servoing". A proposed hand & eye-vergence dual control system is used to perform Approaching Visual Servoing, aiming at quick eye-tracking and stable hand servoing and approaching. This idea stems from hammerhead shark whose eyes turn to gaze at the target prey to be suited to triangulation, enhancing the ability to measure precisely the distance to the prey for catching it. This animal's visual tracking includes motion con trol by visual servoing and triangular eye vergence. Moreover, a 3-D pose tracking method that combines "1-Step GA (genetic algorithm)" and hand-motion feedforword compensation is proposed. Our approach differs from known tracking methods using optimization based on Taylor expansion, for it allows the proposed method not to be annoyed by how to sneak out of local minima. A convergence in time domain whether the 3-D pose tracking error decrease to zero in a successively input images by video rate , is discussed and verified through Lyapunov method. Both Lyapunouv-stable pose tracking and Approaching Visual Servoing are confirmed by experiments using a 7-link manipulator installed with two mobile cameras.