Makoto Kumon

Brief paper: Adaptive output feedback control of general MIMO systems using multirate sampling and its application to a cart-crane system

In adaptive output feedback control based on almost strictly positive real conditions, a technical difficulty arises when the multi-input multi-output (MIMO) system under consideration is non-square, and in particular, has less inputs than outputs. To overcome this, we propose the idea of multirate sampled-data control-by carefully choosing faster input sampling rates, we obtain a lifted discrete-time system, which has the same number of inputs and outputs and does not give rise to the causality constraint. The adaptive control strategy is then applied to the lifted system, resulting in a multirate adaptive output feedback controller which is implementable digitally and provides closed-loop stability under certain conditions. The results reported here are validated on an experimental cart-crane system.

CONTROLLED SYNCHRONIZATION OF TWO 1-DOF COUPLED OSCILLATORS

Two 1-DOF pendulums coupled with a weak spring are considered. This system is a coupled Controlled Hamiltonian Systems that has been studied widely in these days. The control objective is to make pendulums swing synchronously with small input. To this end, Speed Gradient Energy method proposed by Fradkov is adopted to design the controller. Although experimental results showed that the method succeeded in achieving the objective, the mechanism of synchronization was not clear. In this study, the contracted dynamics of the whole system is analyzed and properties of the system are investigated. Through the investigation, a criteria to define the feedback gain of the controller is revealed. Computer simulation and experimental results showed the validity of the method.

Wind Estimation by Unmanned Air Vehicle with Delta Wing

In this paper, an algorithm to estimate wind direction by using a small and light Unmanned Air Vehicle(UAV) called KITEPLANE was proposed. KITEPLANE had a big main wing which is a kite-like delta shape and, therefore, it was easy to be disturbed by wind. However, this disadvantage implies that the KITEPLANE has an ability to sense wind and that it is expected to use the KITEPLANE as a sensor for wind estimation. In order to achieve this feature, dynamics of the KITEPLANE under wind disturbance were derived and a numerical estimation method was proposed. Devices equipped on board were also developed and the proposed method was implemented. Results of an experiment showed the effectiveness of the proposed method.

Autopilot System for Kiteplane

This paper proposes an autopilot system for a small and light unmanned air vehicle called Kiteplane. The Kiteplane has a large delta-shaped main wing that is easily disturbed by the wind, which was minimized by utilizing trim flight with drift. The proposed control system for autonomous trajectory following with a wind disturbance included fuzzy logic controllers, a speed controller, a wind disturbance attenuation block, and low-level feedback controllers. The system was implemented onboard the aircraft. Experiments were performed to test the performance of the proposed system and the Kiteplane nearly succeeded in following the desired trajectory, under the wind disturbance. Although the path was not followed perfectly, the airplane was able to traverse the waypoints by utilizing a failsafe waypoint updating rule

Audio servo for robotic systems with pinnae

Sound localization is one of important abilities for robots which utilize auditory information. Binaural information such as interaural time difference (ITD) or interaural intensity difference(IID) is effective for horizontal sound localization. In order to extend this ability to vertical sound localization, spectral cues were utilized in this paper instead of increasing number of microphones. Spectral cues were the information about the vertical position of the sound source on frequency domain. Since spectral cues strongly depended on the shape of pinnae, artificial pinnae for auditory robots were designed based on diffraction-reflection model. A method to detect spectral cues was also developed. By utilizing them, a controller which made the robot orient to the sound source was proposed. Results of an experiment showed the validity of the proposed method.

Spectral Cues for Robust Sound Localization with Pinnae

An important ability in auditory robots is the localization of sound source. In this paper, a robust method to localize the vertical direction of the sound source with two microphones and pinnae is proposed. In order to achieve vertical sound source localization, the method of detecting spectral cues, the relationship between spectral cues and source direction are studied. In addition, this paper considers sound source separation in order to recognize and isolate spectral cues only from the sound source in order to make the method robust to extraneous noise. Furthermore the authors designed an audio servo with the proposed spectral cues and implemented the method in an actual robot. The experimental results confirmed the effectiveness of the method

Design model of microphone arrays for multirotor helicopters

Unmanned multirotor helicopters have been expected for various critical tasks such as rescue missions, and it is important to sense the environment to achieve those tasks. In order to realize such sensor systems, this paper considers acoustic information recognition from a hovering helicopter which a microphone array system. As the noise of rotors distorts the acoustic information, noise reduction is necessary. Since the rotor noise varies even at the hovering flight, an acoustic model of the rotor noise is derived taking the dynamics of the helicopter into account, and the model is utilized to evaluate the performance of the microphone array. The proposed approach was verified by evaluating the optimality of a real device that was empirically tuned in authors previous work, and the computed configuration of the microphone array and the developed one coincide well, which ensures the validity of the approach. As the validation through a practical application, the signal was processed by Delay-and-Sum Beam Former to localize the sound source. The system was able to find peaks of the power that corresponded to the sound source.

Hovering control of vectored thrust aerial vehicles

In this paper, a vectored thrust aerial vehicle( VTAV) that has three ducted fans is considered. Since ducted fans are powerful and effective in providing lift, they are suitable for thrusters of UAVs, but modeling their aerodynamic effects such as ram drag is very difficult. The VTAV has one ducted fan fixed to its body and two ducted fans that can be tilted in order to make rotational moments, which makes the system dynamics even more complicated. This paper focuses on giving a precise dynamical model that includes aerodynamic effects of ducted fans. Then it presents a hovering controller based on the dynamical model developed. Since the horizontal dynamics are under actuated, a switching control approach is introduced to realize a stabilizing controller. Numerical simulations prove the validity of the approach.

A microphone array configuration for an auditory quadrotor helicopter system

In order to achieve acoustic surveillance by using a multirotor helicopter, a microphone array specially tailored for the helicopter is considered in this paper. Several preliminary experiments were conducted to evaluate how the noise generated by rotors distorted the target sound signal from the view point of sound source localization, and the microphone array was developed based on results of the experiments. The microphone array was also installed on the helicopter, and it was tested to record the human voice during an autonomous waypoint flight in an outdoor environment. Investigating the measured auditory signal, it was shown that the proposed mechanism was capable to be utilized for the acoustic search in the outdoor environment.

Motion planning based on simultaneous perturbation stochastic approximation for mobile auditory robots

In this paper, a motion planning method for mobile auditory robots is proposed based on an optimization technique. Since it is one of the most important abilities for auditory robots to recognize vocal messages correctly, the proposed method is designed to maximize the confidence measure of a speech recognition since the measure is thought to be strongly related to the accuracy of the speech recognition. However, the cost function to optimize is hard to model explicitly, and it is difficult to obtain the gradient that is normally utilized to derive the motion. In order to overcome this difficulty, simultaneous perturbation stochastic approximation(SPSA) that does not require an explicit model of the cost function is applied to generate robot motion. The effectiveness of the approach was verified through real experiments: the robot could get better speech recognition rate after it approached the sound source by measuring the confidence measure.