It is difficult for general public to control biped walking robots because various technical knowledge is required. In this paper, a simple control method of biped locomotion robots using master slave system with visual information is developed. First, we propose a motion capture system which gets human motions. This method allow a human to operate a robot intentionally in real time. Moreover, a walking pattern, called Double Inverted Pendulum Mode, is mounted for stability of robot's postuer.

In this paper, a method of rendezvous docking to an uncooperative target is presented by using adaptive control. When the docking to an uncooperative target is done, the inertia of the combined spacecraft is uncertain. Adaptive control can manage these uncertainties and the asymptotic tracking control is achieved by using backstepping technique in the framework of the globally nonsingular unit quaternion representation of a spacecraft.

In this paper, a design method of a hybrid system for active steering based on model reference adaptive control is proposed. A controller to track a desired yaw rate is applied to a linear model because a driver is conscious of a yaw rate in normal situation. The controller is switched to a nonlinear controller to track a lateral acceleration because of the importance of lateral movement in critical situation. The timing of the controller switching is considered for the proposed model reference control system. Some simulation results show the capability of this hybrid controller.

Presents a model reference adaptive control strategy for active steering of 2WS cars which is realized by steer-by-wire technology. The ideal fixed property of a steering system which is provided by a reference model is attained by D* control. The proposed method can treat the nonlinear relationships between the slip angles and the lateral forces on tires, and the uncertainties on the friction of the road surface, whose compensations are proved to be very important under critical situations. Some results of real time simulation with a steering equipment show the effectiveness of the proposed method.

The performance on braking of a vehicle is recently improved in the generation of brake-by-wire systems. In this paper, a new brake system is proposed by using the brake-by-wire technology. The velocity of a vehicle is controlled to track a nominal velocity which is calculated from an ideal tire-road friction model and a driver's input. However, the saturation of the tire-road friction makes tracking impossible when the slip becomes large. It is required that the control objection should be changed to prevent the wheel slip from being over a certain value. A hybrid brake system based on model reference adaptive control is designed to attain these control objectives under various road conditions. The stability of this system is theoretically proved, and then it is confirmed by simulations.

In this paper, a method of cooperative control between steer-by-wire system and brake-by-wire system based on model reference adaptive control is proposed. The controller can treat the tire nonlinear characteristic. The vehicle has two wheel steering (2WS) which is equipped with steer-by-wire technology, and all the wheels are equipped with brake-by-wire technology respectively. The validity of the controler is shown by the simulation based on a multi DOF model of vehicle.

Iterative learning control (ILC) obtains a desired input that exactly generates a desired output through repetitions of the similar tasks. The adjoint-type ILC, which is based on the gradient method, can obtain the bounded desired input for a finite dimensional and non-minimum phase system. This aspect suggests that the adjoint-type ILC can achieve good output tracking for a flexible arm, which is a infinite dimensional and non-minimum phase system. In this paper, we propose an update law and give a convergence condition for the adjoint-type ILC applied to a single-link flexible arm. In order to verify the effectiveness of the adjoint-type ILC for the single-link flexible arm, an experiment is carried out. Several researchers have proposed a iterative learning controller for the flexible arm by using assumed modes method. In this paper, a simple model of the single-link flexible arm is used because ILC dose not require the accurate model. Experiments result show that, even if the single-link flexible arm is modeled by the simple method and has some uncertainties, good output tracking is achieved. Moreover, pre-actuation, which is remarkable aspect of the adjoint-type ILC, is observed.

ABSTRACTIn this paper, we investigate iterative learning control (ILC) for non‐minimum phase systems from a novel viewpoint. For non‐minimum phase systems, the magnitude of a desiredinput obtained by ILC using forward‐time updating and Silverman's inversion are too large because of the influence of the unstable zeros. On the other hand, stable inversion constructs a bounded desired input by using non‐causal inverse for non‐minimum phase systems.In this paper, we first clarify that ILC using an adjoint system achieves the desired input defined by stable inversion. Hence, ILC using an adjoint system is an effective method for the control of non‐minimum phase systems with uncertainty. However, a useful convergence condition of ILC using an adjoint system was not achieved. Next, we develop a simple convergence condition in the frequency domain.

Iterative learning control (ILC) obtains a desired input that exactly generates the desired output through repetitions of the same tasks. In this paper, a numerical simulation of the adjoint-type ILC, which can obtain desired inputs even if the objective system is that of a nonminimum phase, is carried out for a planar model of a helicopter.

It is important in practice use for robots to contact an object or environment around the robot. At the moment of the contact, an impulsive force, or impact, may cause a discontinuous change of the state of the robot. Since the impact strongly depends on the configuration of the robot at the moment of the contact, the precise control of the configuration of the robot is needed. Authors have proposed a path following control method based on dynamic parametrization, that makes the robot follow the desired path efficiently. In this paper, the above method is applied to a manipulator system with impact. And it is shown that this controller with high feedback gain can stabilize the system with impact. Results of computer simulations validate this result.

ABSTRACTIn this paper, an adaptive control method is proposed for systems whose structures can be divided into a known part and an unknown part. A non‐adaptive control design, such as H∞ control design can be introduced into the known part of the system, and adaptive control can cope with the unknown part to realize the property designed by non‐adaptive control. This is achieved by means of backstepping. This method is applied to the control design of an active suspension system for a railway vehicle, which is divided into two parts: a main car body part and an actuator part. Some simulation results of the control system designed using H∞ control for the body part and adaptive control for the actuator part are provided.

An adaptive control method for a special chained form system with drift terms and unknown parameters is discussed. Tracking controllers have been considered to be effective for solving the problem of the stability of nonholonomic control systems. Since a tracking control system can be transformed to the special chained form system, a tracking controller using the backstepping method is proposed for the nonholonomic chained form system. The asymptotic stability of the system is guaranteed by using Lyapunov's direct method and using adaptive control method, an adaptive controller is proposed for the nonholonomic system with unknown parameters. The ability of the proposed controller is illustrated by simulations. Furthermore, based on a nonholonomic mobile robot, a typical example of nonholonomic system, we demonstrate the efficiency of the proposed method.

Iterative learning control (ILC) obtains a desired input that exactly generates the desired output through repetitions of the similar tasks. In this paper, an experiment of the adjoint-type ILC based on the gradient method is carried out by using a single-link flexible arm. Experimental results showed that, even if the single-link flexible arm is modeled by a simple method and has some uncertainties, exact output tracking is achieved. Moreover, pre-actuation, which is remarkable aspect of the adjoint-type ILC, is observed.

The objective of this article is to provide the basic formulation of the affordance of environment. Study on affordance has been mostly focusing on the significance of perception, behavior and workspace, while leaving the problem of application unaddressed. Using the proposed method, it is possible to apply reinforcement learning algorithm on the robot within a certain environment, making the abstraction of affordance of the environment with interaction between the reinforcement learning agent and the environment available. Conclusion is made in the latter part of the paper that the percipient(robot) should simplify the number of perception in order to get enough valid equivalence relationship which abstracts affordance from environment with in the limit of incomplete perception; and the structure of the environment(workspace) would restrict the robot’s behavior. The prospect of this study, therefore, focuses on the interactive processes between the robot and the workspace from which the robot could set up it’s perception for particular tasks, and on how the robot could continuously manage it’s perception.

Q-learning is one of the famous algorithms for reinforcement learning. A usual way for expressing a Q-value function is using a Q-table which is a look-up table. But it is difficult to specify the discretize size of the state spaces without prior knowledge. In this paper, the method of the adaptive construction of state spaces on Q-learning by storing the data an agent has experienced is proposed. The effectiveness of this method is confirmed by some simulations of path-planning problems. Furthermore, the method of automatically setting the parameter for resolving the trade-off between exploration and exploitation is proposed.

ABSTRACTPath following is a basic skill for robots in industrial use. Since the objective of path following is to make a robot follow the reference path, the velocity of the robot or the timing of the motion does not need to be strictly controlled. In this paper, the reference path is defined as a function of the parameter that has dynamics. Using this parameter, we can define the contour error, which is the error that enables us to measure the distance from the reference path to the configuration of the robot. Although the contour error is suitable for use in path following, the dynamics of the parameter contain singular points at which the dynamics cannot be defined. In order to overcome this difficulty, globally defined dynamics are introduced, and two dynamics are integrated with a switching scheme. In this paper, the asymptotic stability of the whole system is proved theoretically. Computer simulation results also show the effectiveness of the method.

It is difficult to apply the existing adaptive control methods to an inverted pendulum and cart system if it is assumed that all physical parameters are unknown, because the number of control inputs is less than that of outputs. Regarding the inverted pendulum system, the parameter uncertainties of the cart are larger than those of the pendulum. In this paper, the partially adaptive control system is designed considering that the parameter uncertainties exist only in the cart. The inverted pendulum and cart system is divided into the known part which includes only the parameters of the pendulum and the unknown part which includes the parameters of the cart. Therefore, LQ control is applied to the known part and adaptive control treats the unknown part based on the backgtepping technique. Finally, the experimental results are provided and the usefulness of this technique is confirmed.

The asymptotic tracking control problem of a rigid spacecraft is considered in this paper. Three type control laws are presented by using a backstepping technique in the framework of the globally nonsingular unit quaternion representation of a spacecraft. The first one is a PD-type control law which does not require much information about the spacecraft model. The second is model-dependent control law, that is, the inertia matrix is exactly known. And the last one is provided by adaptive control assuming that the inertia matrix is unknown. The effectiveness of the proposed method is also confirmed by some simulation results.

This paper addresses the problem of adaptive tracking control for nonholonomic two actuated wheels mobile robot systems with unknown parameters. An adaptive tracking controller is proposed for a kinematic model of two-wheel mobile robot with unknown kinematic parameters by using integrator Backstepping approach, and the asymptotic stability of the control system is guaranteed by the Lyapunov's direct method. Furthermore, based on a further backstepping approach, an adaptive torque controller is applied to a dynamic model with unknown dynamic parameters. Simulation examples of a mobile robot with two actuated wheels are provided for illustrating the tracking ability of the controller for both the kinematic models and dynamic models.