Hiroyuki Osuga

Determining parameter sets for low-frequency-oscillation-free operation of Hall thruster

We performed a theoretical and experimental study of low-frequency oscillation in a Hall thruster. The oscillation phenomenon depends on various external control parameters. However, we found that such dependence can be observed very clearly using certain expressions, which are combinations of external control parameters. Using these expressions, one can observe the oscillation strength and oscillation mode for a given set of external control parameters. We considered that low-frequency oscillation can be essentially suppressed by a method of determining parameter sets. The method of determining the parameter sets is very important for Hall thruster design and control; in particular, it makes it easy to manage electromagnetic compatibility with the other equipments in a satellite, using a power supply control.

A new digital control DC-DC converter with neural network predictor

The purpose of this paper is to present a new digital control method of a forward type multiple-output dc-dc converter with both a P-I-D feedback and a new feed forward control. In this converter, a new method with a neural network predictor is presented. The dynamic characteristics of digital control dc-dc converter are improved as compared with the conventional one. Especially, the digital control dc-dc converter with the neural network predictor can realize excellent dynamic characteristics. As a result, the undershoot voltage, the overshoot voltage and the convergence time of the output voltage are improved to 43%, 65% and 63% respectively.

A new STS model DC-DC converter

This paper presents a new STS (steady-state-error and transient suppression) model based digital control dc-dc converter. In this method, not only the conventional P-I-D control as the feedback one but also the new STS model as the feed-forward one is used. The proposed STS model is consist of two superior functions, one is the steady-state function for expanse of regulation range of output voltage, and another is the exponential function for improvement of transient response. As a result, the proposed method has no steady-state-error against the changes of input voltage Ei and output current Io. In addition, the undershoot of output voltage and the overshoot of reactor current are suppressed to about 8% and 11% as compared with the conventional one in the step change of load resistance from 100Ω to 5Ω. Especially, the convergence time for output voltage is converged instantly. It is confirmed that the new STS model control realizes good characteristics for both the steady and transient state.

A new quick transient response digital control dc-dc converter with smart bias function

The purpose of this paper is to present a new quick transient response digital control dc-dc converter with smart bias function and its design criterion. In the proposed method, not only the conventional P-I-D control as the feedback one but also the smart bias function as the feedforward one is used. The smart bias function consists of two superior functions. One is the steady-state function for the expanse of regulation range of output voltage, and another is exponential function for the improvement of transient response. By using these functions, the proposed method has no steady-state-error against the changes of the input voltage and the output current. In addition, the undershoot of output voltage and the overshoot of reactor current are approximately 92% and 89% smaller than the conventional method in the step change of load resistance from 100Ω to 5Ω. Especially, the convergence time for output voltage is converged instantly. It is confirmed that the smart bias function control technique is useful to realize the high performance digital control method.

A New Control Method for dc-dc Converter by Neural Network Predictor with Repetitive Training

This paper proposes a novel prediction based digital control dc-dc converter. In this method, a neural network control is adopted to improve the transient response in coordination with a conventional P-I-D control. The prediction based control term is consists of predicted data which are obtained from repetitive training of the neural network. This works to improve the transient response very effectively when the load is changed quickly. As a result, the undershoot of the output voltage and the overshoot of the reactor current are suppressed effectively as compared with the conventional one in the step change of load resistance. The proposed method is based on the neural network learning, it is expected that the proposed approach has high availability in providing the easy way for the design of circuit system since there is no need to change the algorithm. The adequate availability of the proposed method is also confirmed by the experiment in which P-I-D control parameters of the circuit are set to non-optimal ones and the proposed method is used in the same manner.

Electric Propulsion Development Activity at MELCO

MELCO has been developing electric propulsions for about 30 years under some national projects in Japan. The 20mN class xenon ion engine subsystem (IES) has arrived at the practical stage of a satellite NSSK propulsion. The IES is applied for NSSK of the engineering test satellite of JAXA, which will be launched in FY2006. Furthermore, now MELCO is developing 200mN class hall thruster and power processing unit for high power next generation satellite. The target specification is that the thrust level is over 250mN, the specific impulse is over 1,500s under the PPU input power of 5kW, and the lifetime is over 3,000 hours. To date, the development status is engineering model (EM) phase after the evaluation of breadboard model (BBM) and development model (DM). The thruster EM showed 264mN of the thrust level and 1,721s of the specific impulse under the thruster input power of 4.56kW. The PPU EM showed the anode efficiency was over 93% for 250V and 350V at output power between 1.75-4.5kW. We will start the endurance test of the thruster EM from the middle of 2006 after the coupling test between the thruster and PPU EM.

A new digital model control for multiple-output dc-dc converter

The purpose of this paper is to present a new digital model control which detects multiple output values of multiple-output dc-dc converter. In this method, the P-I-D control and the static equation model are performed. The dynamic characteristics of digital control converter are improved as compared with the conventional one.

A new auto-bias method for digital control dc-dc converter

Main content of this paper is a new auto-bias method for digital control dc-dc converter. In the proposed method, not only the P-I-D control as the feedback one but also the new auto-bias method as the feedforward one is used. The new auto-bias method consists of two superior functions. One is the steady-state function for the expanse of regulation range of output voltage, and another is exponential function for the improvement of transient response. By using these functions, the proposed method has no steady-state-error against the changes of the input voltage and the output current. In addition, the undershoot of output voltage and the overshoot of reactor current are approximately 92% and 89% smaller than the conventional method in the step change of load resistance from 100Ω to 5Ω. Especially, the convergence time for output voltage is converged instantly. It is confirmed that the new auto-bias model control technique is useful to realize the high performance digital control method.

A New Prediction Based Digital Control DC-DC Converter

This paper presents a novel prediction based digital control dc-dc converter. In this method, addition to the P-I-D control as the feedback control, the prediction based control is used as the feedfoward control. In the feedfoward control, the neural network based method is adopted. This works to improve the transient response very effectively when the load is changed quickly. As a result, the undershoot of the output voltage and the overshoot of the reactor current are suppressed effectively as compared with the conventional one in the step change of load resistance. It is confirmed that the prediction based control technique is useful to realize the high performance digital control method for the dc-dc converter.

A smart control approach for digitally controlled multiple-output DC-DC converter

This paper presents a smart control approach for digitally controlled forward type multiple-output dc-dc converter. In this case, the central problem of design is how to decide the integral coefficient. Since the decision of integral coefficient depends on the static characteristics, the selected integral coefficient is not suitable to perform the superior dynamic characteristics. Then, it is important to set the suitable the integral coefficient for not only static characteristics but also dynamic characteristics. As a result, overshoot and the convergence time of the output voltage are improved 30% and 30%. The overshoot of reactor current is improved 11%. Moreover, to achieve the improvement of the dynamic characteristic, the number of bits of the calculation part of the digital control circuit set enlarged. As a result, the overshoot and the convergence time of the output voltage are improved 78% and 30%. The overshoot of reactor current is improved 17%.