An adaptive control system is configured simply by output feedback when the controlled system is almost strictly positive real (ASPR). ASPR conditions are, however, very severe restrictions for actual systems. The parallel feedforward compensator (PFC), which is designed for making augmented controlled system ASPR, has been proposed to solve this problem. We propose a performance-driven adaptive output feedback control system with a PFC designed via direct design. Our proposed adaptive control system is to be used for systems whose properties change during operation. Our PFC’s direct design uses the system’s input/output data and readjusts output feedback gain based on a performance index. The effectiveness of the proposed method is confirmed through experiments using liquid level control for the two-tank process system.

In order to work effectively, a robot should be able to adapt to different environments by deciding its correct course of action according to the situation, using determinants other than pre-registered commands. For this purpose, the ability to predict the future state of a robot would be effective. On the other hand, the future state of a robot varies infinitely if it depends on its current action. Therefore, it is difficult to predict only the future state. Thus, it is important to simultaneously predict the state and the action that the robot will adopt. The purpose of this study was to investigate the prediction of the advanced future state and action of a robot. In this paper, the results of the study are reported and methods that allow a robot to decide its appropriate behavior quickly, according to the predicted future state are discussed. As an application example for evaluating the proposed method, the inverted pendulum model is used and the prediction results are compared with the robot’s actual responses. Then, two methods will be discussed for predicting the robot’s state and action. To perform state and action prediction, two methods are used, firstly the Online SVR (Support Vector Regression) and secondly Online SVR and the LQR (Linear Quadratic Regulator).

In Earth orbit, a space telescope is free from any absorption or disturbances from the Earth’s atmosphere. Therefore, a large space telescope is planned for the future. We discuss the assembly of a large telescope reflector performed by a robot arm. For the assembly work, positioning of the arm using visual servo control to colored markers is proposed. A ground test-bed is used to test the characteristics of the new image processing method for colored markers. The results of the tests are also given.

Output by a photovoltaic array is nonlinear and changes with solar irradiation and cell temperature. Maximum Power Point Tracking (MPPT) is needed to maximize the energy produced. Most MPPT techniques include the time derivative of current and voltage. These electrical signals are disturbed by high-frequency noise such as from the power device switching. Lowpass filters are used to reduce circuit noise, but estimation error occurs when the maximum power point is calculated. We therefore apply an adaptive observer to estimate the time derivative of noisy signals. Specifically, we propose an auto-tuning velocity estimator with a forgetting factor based on the adaptive observer. We also improve the incremental conductance method by using an auto-tuning velocity estimator.

Commercially available robotic grippers are often expensive and not easy to modify for specific purposes of robotics research and education. To extend the choice of robotic end effectors available to researchers, this paper presents the preliminary work on prototype design and analysis of a three-finger underactuated robotic end effector with a breakaway clutch mechanism suitable for research in robot manipulation of objects for industrial and service applications. Kinematic models of the finger and the breakaway clutch mechanisms are analyzed aiming to define selection criteria of design parameters. Grasping performance of the end effector prototype manufactured with a 3D printing technology and off-the-shelf components is evaluated using simulation and experimental analyses. Comparison with widely applied available robotic end effectors shows the potential advantages of the proposed end effector design.

In this research, tube-type dielectric elastomer actuators (DEAs) are employed to develop a 3-DOF flexible parallel link mechanism instead of traditional actuators such as linear motors and pneumatic cylinders. As an application case, the developed mechanism fixed with a marker pen is used to implement one stroke draw and human like draw of alphabets on a plane. According to the prototype of this mechanism, kinematics and inverse kinematics problems are considered. Based on the kinematics and inverse kinematics equations, the numerical simulations are done for searching the reachable area of the tip of the marker pen and checking the lengths of DEAs during drawing. Finally, experiment results show the practicability of the developed mechanism.

Complicated dynamic behavior will happen while nonlinear four degree-of-freedom (DOF) semi-vehicle model is under irregular road excitation. The complex nonlinear vibration influences the ride comfort and safety. In this paper, the study is aimed at analyzing the chaotic vibration and comfort analysis of a vehicle passing the consecutive speed control humps (SCHs). A four-DOF half-vehicle model and combined sine-trapezoidal wave of variable frequency are applied. Occurrence of chaotic vibration is analyzed by bifurcation diagram, time history, Poincaré map. The numerical simulation results show that chaotic vibration phenomenon possibly appears as vehicles are driven on consecutive SCHs. In addition, the exact range of vehicle speed that results in chaotic vibration is derived. Further studies indicate that the influence of quasi-periodic motion state to vehicle on driving comfort is the biggest. This paper uses direct variable feedback control method to control chaotic vibration, and analyzes the control effect from the feedback gain control effect and the delay of the feedback control. The results will help dynamic characteristic analysis of vehicles and the design of the continuous speed bumps.

Speech recovery in the presence of very harsh noise is calling for R&D that take approaches different from those established to date, as the conventional systems and algorithms for speech denoising may suffer from serious performance degradation. In this paper, we propose a hybrid nonlinear adaptive noise canceller (ANC) to perform the speech enhancement task using both bone- and air-conducted measurements. In the proposed ANC, the bone-conducted speech serves as a reference signal while the air-conducted measurement with very large additive noise is adopted as a primary noise. A Volterra filter and a functional link artificial neural network (FLANN) are placed in parallel, forming a hybrid nonlinear ANC. Simulations using real bone- and air-conducted speech measurements are provided to demonstrate that the proposed system outperforms ANCs equipped with FIR filter or Volterra filter or FLANN alone.

Gait training is an important rehabilitation exercise that requires large space and support. To help it succeed, we developed an automatic speed-controlled treadmill with a sensor frame. A Microsoft Kinect sensor detects the user’s legs, measuring step length and stride width. Leg information is used to control treadmill belt speed. Force sensors in the sensor frame measure support force and its center. Gait analysis using these values is discussed without including treadmill speed control. Subjects were healthy young males aged 22 to 23. Step length indicates the suitable belt speed for a subject. In experiments with automatic belt-speed control, the controller adjusts belt speed automatically based on how a user walks.

This paper reports on a simple sliding mode controller that is based on a low-cost camera and being developed for application to a compact, mobile snow-removal robot. We adopt a sliding mode controller for the lightweight, tracked robot to be used under slippery conditions. Assuming the snow-removal task can be carried out by following straight paths, this paper focuses on the path control problem by using a low-cost camera and a simple marker placed on the work site. The transient motion control during the converging state to the line paths is discussed in particular. In our snow-removal application, robustness against disturbances due to snow pressure or track slips is important. In addition, rotation should not be excessive during the transient response so that the robot does not lose sight of the marker. The sliding mode controller is a useful solution, filling these requirements. The problem of robustness in the face of track slip is analyzed theoretically, based on a model with parameter error and input disturbance. The expected tracking accuracy is evaluated in terms of the disturbance values and feedback gains. Experiments are carried out on a slippery surface of polystyrene beads. Robustness against disturbance is tested on an inclined surface.

In this paper, we discuss how to generate defensive motions for a sword-fighting robot based on quick detection of the opposite player’s initial motions. Our sword-fighting robot system, which has a stereo high-speed vision system, recognizes both the position of a human player and that of the sword grasped by the robot’s hand. Further, it detects the moment when the human player initiates a move using ChangeFinder, which is a method of detecting change points. Next, using least squares method, it predicts the possible trajectories of the sword of the human player from the moment when the attack starts. Finally, it judges the type of the attack and generates an appropriate defensive motion. The effectiveness of the proposed algorithm is verified by experimental results.

This paper describes a new control method for stable robot positioning by means of a three degree-of-freedom robotic manipulator that consists of six wire-driven actuators located at each rotational joint. The actuator contains a direct-current (DC) motor capable of pulling a wire to which a high-stiffness spring is connected in series. We demonstrate that the positioning control method used by the redundant robot, which is based on task-space control given in Cartesian coordinates, works well in the vertical plane under gravity. With the use of the reliable positioning controller, we propose a simple algorithm to absorb impulsive forces exerted on the tip position of the robot. In addition, we reveal that the control method presented in this study enables the redundant robot to change its stable posture while maintaining the tip position on which a heavy load is placed. We finally verify that a simple algorithm, based on positioning control, which involves suspending and restarting the switching of the integral controller forming a fictitious target-trajectory of joint angles, realizes recovery motion towards a former posture attained before the impulsive force.

In our research, we have focused on investigating the application of brain-inspired technology by developing a robot with consciousness resembling that of a human being. The goal was to enhance intelligent behavior/emotion, and to facilitate communication between human beings and robots. We sought to increase the robot’s behavioral/emotional intelligence capabilities so that it could distinguish, adapt and react to changes in the environment. In this paper, we present a behavioral/emotional expression system designed to work automatically by two processes. The first is a classification of behavior and emotions by determining the winner node based on Self-Organizing Map (SOM) learning. For the second, we propose a stochastic emotion model based on Markov theory in which the probabilities of emotional state transition are updated with affective factors. Finally, we verified this model with a conscious behavior robot (Conbe-I), and confirmed the effectiveness of the proposed system with the experimental results in a realistic environment.

We have been studying and developing an underwater robot for coral reef conservation. This paper describes the development of an acetic acid injection device mounted on an underwater robot for use in exterminating crown-of-thorns starfish that damage corals. First, we outlined the ecology and morphology of the crown-of-thorns starfish to identify requirements for the acetic acid injection device. Based on the requirements identified, we designed and prototyped an acetic acid injection device to be installed on an underwater robot. Next, we installed the developed injection device on a remotely operated vehicle and injected acetic acid into crown-of-thorns starfish under water. We describe the effectiveness of this acetic acid injection device for exterminating crown-of-thorns starfish. The experimental results prove that the developed acetic acid injection device can inject acetic acid into crown-of-thorns starfish just as intended, and that an underwater robot installed with such device can be used effectively to aid in the extermination of crown-of-thorns starfish.

The avoidance obstacle path planning problem is stated in an obstacle environment. The minimum Steiner tree theory is the basis of the global shortest path. It is one of the classic NP-hard problem in nonlinear combinatorial optimization. A visualization experiment approach has been used to find Steiner point and system’s shortest path is called Steiner minimum tree. However, obstacles must be considered in some problems. An Obstacle Avoiding Steiner Minimal Tree (OASMT) connects some points and avoids running through any obstacle when constructing a tree with a minimal total length. We used a geometry experiment approach (GEA) to solve OASMT by using the visualization experiment device discussed below. A GEA for some systems with obstacles is used to receive approximate optimizing results. We proved the validity of the GEA for the OASMT by solving problems in which the global shortest path is obtained successfully by using the GEA.

We have developed the RT-Mover series of mobile robots because of the strong demand for mobile robot platforms for use on rough terrain. They look like ordinary four-wheel vehicles but are mobile enough to operate on targeted rough terrain encountered in daily life. The advantage of this series is that individual wheels negotiate obstacles with their own leg motion mechanisms.