Kazushi Nakano

A design of robust adaptive control system with a relaxed strictly-positive-realness condition

In this paper, we extend the exact model matching by observer-controllers to that by all two-parameter compensators and give an adaptive control scheme with free parameter Q using coprime factorization. The parameter adjustment law using a Riccati equation which guarantees the boundedness of the dynamic error system is proposed. Moreover, we construct the adaptive control system for a plant with output disturbances or unmodelled dynamics by designing the transfer function of error system and Q parameter to meet some desired robust performance properties.

Research and development of model-based battery state of charge indicator

A novel approach to developing a battery state of charge indicator for an electric vehicle is discussed. An approach to determining the state of charge by combing the available data of discharge characteristics of a lead-acid battery with an identification technique based on the battery mathematical model is presented. The basis for the approach is to introduce a nonlinear battery mathematical model, and to estimate the battery state of charge by least squares estimation. This approach was realized by a digital signal processor and its validity was confirmed by simulation tests using data measured during urban driving and road tests.<<ETX>>

Wavelet analysis approach to identification of systems with dead time application to boiler process

The wavelet analysis is superior to the Fourier analysis in the detectability of temporal (or spatial) information of signals. Therefore, the use of this time-frequency analysis approach makes it possible to estimate such singular points as dead time, and the use of the analyzing wavelet which exists locally in the frequency domain makes it possible to estimate the frequency response of the transfer function. First, we present a dead time identification technique by using the wavelet transform of the cross-spectra of input/output (I/O) data. Secondly, we present a method for obtaining the frequency response of the system to be considered by directly using the wavelet transform of the auto-/cross-correlation functions of the I/O data. Thirdly, we determine the parameters in the transfer function by using the curve fitting in the least squares sense. Finally, we demonstrate the feasibility and validity of our identification procedure through experiments for an actual boiler process.

A Parametrization of all Stabilizing Compensators with a Static Output Feedback in the Central Part and its Application to PID Controller

Abstract The Youla parametrization of all stabilizing compensators consists of a full-order observer based controller and free parameters in RH ∞ . In this paper, we derive a parametrization of all stabilizing compensators, which has a static output feedback term in the central part, by state-space methods instead of coprime factorization methods. Using the parametrization obtained here, we give a parametrization of all stabilizing compensators based on a PID controller and point out that our parametrization based on PID controller can be interpreted as a PID controller with an internal model. Finally, we show an example of an I-PD controller-based parametrization by using SIMULINK.

Identification of Pulse Transfer Function in the Presence of Input and Output Noise

Abstract The numerical instabilities of the bias compensated least-squares (BCLS) algorithm are discussed in the case where input and output measurements are corrupted by white noise. For improving the stability of BCLS algorithm, an estimator constructed by filtered data vectors is developed. The identifiability in the special case where input signal is white is also discussed. Some simulation results are presented to demonstrate the numerical robustness of the proposed BCLS algorithm

Small controller for an ideal transient control performance

The authors have configured a control signal to achieve an ideal control performance taking advantage of ZIR (zero input response) and ZSR (zero state response). First, they define both an ideal transient dynamics and control performance on frequency domain. Then, they construct a simulator based on a physical model of a nonlinear plant, and identify not only parameters but also initial states of state variables. Since the dynamics of the nonlinear plant output can be foreseen with information of the internal states of the nonlinear simulator, an ideal control performance is achieved taking advantage of ZIR and ZSR.

Wavelet-Based Identification for Transfer Function with Dead Time and Its Application

Abstract Wavelet analysis is used in identifying a continuous-time system with dead time. First, we present a dead-time identification technique by using the wavelet transform of the cross-specta of input/output (I/O) data. Secondly, we present a method for obtaining the frequency response of the system to be considered by directly using the wavelet transform of the auto-/cross-eorrelation functions of the I/O data. Thirdly, we determine the parameters in the transfer function by using the curve-fitting in the least squares sense. The adventage of our identification procedure is that the estimates of parameters can be obtained separately from the delay-time estimate. Finally, we demonstrate the feasibility and validity of our procedure through experiments with an actual boiler process.

A Three-Step Estimation Procedure for the Pulse Transfer Function from the Viewpoint of a Reductive Parameter Transformation

Abstract The problem is considered of estimating unknown parameters in the pulse transfer function by using estimates of the noise auto-correlation function, from input and output data corrupted by colored noise. The three-step estimation procedure has already been proposed to obtain improved parameter estimates in the final step, by making good use of the extended input/output correlation functions. For quantitatively evaluating this procedure, the reductive parameter transformation from the first step to the final step is introduced. Then, the final parameter estimates hold the good properties of satisfying the minimum error criteria not only for the parameter transformation but also for the bias-compensated least-squares estimation.

Optimum Design of Tractor-Rotary Tillage System by Parameter Identification

Abstract From the viewpoint of evaluation of torque curve generated by tillage resistance of rotary blade, reliable techniques of simulation and identification through torque curve separation by using the Gauss-Newton method (GNM) are discussed. A simple method for identifying the parameters is established, which are characterized by soil condition and are of importance for the design of the tractor-rotary tillage system in agricultural machinery . It is clarified that the order of the values of mean and standard deviation of measured torque curve can be estimated by the simulation using the torque curve quadrilateral model.

Generalized-inverse approach to model following control for nonlinear mechanical systems and its extensions

Extensions of the results of the model reference adaptive control (MRAC) to nonlinear systems have been attempted. In particular, designs of MRAC for nonlinear mechanical systems, such as a manipulator and or an inverted pendulum, have been studied with much interest. For this purpose, we propose a design method for model following control systems (MFCS) as a first step towards MRACS for nonlinear mechanical systems affine in the control. First, we consider Hirschorns algorithm concerning the invertibility of nonlinear control systems. However, it is difficult to apply the algorithm directly to the control objective with the small number of inputs. Secondly, we propose an alternative MFCS design, based on a kind of generalized-inverse technique which makes it possible to assign any following characteristics. Thirdly, we consider an example of the application to the inverted pendulum to demonstrate the feasibility and efficiency of the proposed control design strategy. Finally, we discuss two extensions of the present method to both cases of modeling error and of non-affine type control.