Katsunobu Konishi

A sequential failure detection approach and the identification of failure parameters

This paper is concerned with the problem of a failure diagnosis for a discrete-time system with parametric failure, in which the occurrence time and mode of parametric failure cannot be estimated in advance. The failure diagnosis system which is proposed consists of three parts : (i) a normal mode filter, (ii) a detector for anomaly states, and (iii) an adaptive extended Kalman filter. The normal mode filter is called the optimal Kalman filter and transports the information of its innovation sequence to the detector. The detector which is based on the SPRT approach detects anomaly states affected by the parametric failure. The adaptive extended Kalman filter estimates simultaneously system parameters and the states under the failure mode. The adaptive procedure is directed by increasing the calculated covariance on the basis of hypothesis tests for the estimation errors of unknown parameters. Numerical results for a simple plant model illustrate the effectiveness of the proposed failure diagnosis system.

Technical communique: A modified extended Kalman filter for linear discrete-time systems with unknown parameters

This technical communique presents a modified extended Kalman filter for estimating the states and unknown parameters in discrete-time, multi-input multi-output linear systems. The hyperstability of the filter is guaranteed by introducing a compensator into the estimation mechanism. It is proved that the estimates for the states and unknown parameters converge to the exact values if some conditions are assumed to the estimation mechanism. A numerical example shows that the proposed filter is much more effective than the extended Kalman filter in the estimation of unknown parameters.

Identification of unknown parameters in linear discrete-time systems by a modified extended Kalman filter

Abstract This paper treats an identification technique for discrete-time linear systems whim noisy measurements are taken. The technique is based on the extended Kalman filter and the model reference adaptive approach. Firstly, the extended Kalman filter derived by augmenting unknown parameters as the state variables is modified by neglecting the information between the states and unknown parameters ; and secondly the stability of the modified filter is compensated by the idea of the model reference adaptive approach. Lastly, the convergence of the obtained estimates for unknovm parameters to the exact values is proved. A numerical example shows the effectiveness of the proposed method.

Active vibration control of aerial vehicles

This Paper Presents A Scheme To Suppress The Vibration Of Manipulator Hand Mounted On The Bucket Of Aerial Vehicles. The Scheme Consists Of A Sliding Mechanism Attached To The Top Of The Boom To Introduce The Relative Displacement Between The Bucket And The Boom, And A Controller To Adjust The Relative Displacement. Equations Of Vibrating Motion For The Aerial Vehicle, Controller Design Based On The LQ Method And Disturbance Observer, And Numerical Simulations For Various Types Of Disturbance Force Are Shown.

ADAPTIVE POLE-PLACEMENT ALGORITHM BASED ON COMMON FACTOR ELIMINATION

Abstract This paper presents an indirect adaptive pole-placement algorithm for noiseless SISO systems. The control input consists of a feedback term and a self-excitation term. The latter is used to guarantee the global stability of the closed loop system. The former, the main part of this paper, is computed by eliminating the common factor included in the estimated parameters. A feature of the algorithm is that it is applicable to the plant whose order is not exactly known. However, a lower bound of the Sylvester resultant of plant polynomials is needed to estimate the order of the plant. Numerical examples are given to illustrate the effectiveness of the proposed algorithm.

Adaptive Force Control of a Pneumatic Cylinder Using a Pressure Control Loop.

The performance of a pneumatic force control system is affected by the characteristics of objects, compressibility of air, friction between cylinder and piston, etc. To suppress the influence of these factors, a combined control method using a P-D pressure controller for the cylinder and an adaptive model reference controller for the total system is presented in this paper. The P-D gains are determined experimentally, and the pressure command signal is produced by the adaptive controller, which is constructed based on the discretization of the third-order continuous-time transfer function with a lag time.Force control experiments were carried out for hard and soft objects using two kinds of controllers, that is, (A) adaptive controller without pressure control and (B) adaptive controller with pressure control. Comparing the experimental results by (A) and (B), the tracking error between the reference force signal and applied force was greatly improved by the proposed controller (B), and especially, steady-state error of (B) was 0.5N for hard object and 0.7N for soft object in the sense of the root mean square of 30 trials. The robustness of (B) to the sudden change in the supplied pressure was also confirmed.

Active Vibration Control of a Flexible Arm Using Hydraulic Cylinders and a Tendon Mechanism.

An active vibration control scheme for a one-link flexible arm is presented, where the actuator is a pair of hydraulic cylinders mounted at the root, and their forces are conducted to the tip by two wires to directly manipulate its displacement. The distance between a wire and the arm is kept constant by spacers in order to prevent buckling of the arm and to conduct the arm deflection faithfully to the cylinders. Experimental results show that the ratio of the settling time to the free vibration period is about 60%, which is less than the ratio of about 150% for the conventional scheme. A model of the arm system and the stability of the controller are given.

Speed Control of a Pneumatic Motor by Using an Adaptive Control Scheme.

This paper describes an adaptive speed control scheme for a pneumatic servo system which is composed of an axial piston motor and an electro-pneumatic proportional valve. The features of the adaptive control scheme are that it is applicable to non-minimum phase systems and that its structure is as simple as the MRAC.Experiments of the adaptive speed control were carried out for several conditions, and their results were compared with those of the conventional PI-D control. From the experimental results summarized below, the effectiveness of the proposed scheme was confirmed : (1) Three sampling periods (Ts=36, 71, 106msec) were tested, and the stability of the adaptive control system was confirmed for each Ts even through the identified plant model was non-minimum phase. The steady state error was not influenced by Ts, and its maximum value (±1.0rpm) was smaller than that of PI-D control (±2-±2.5rpm) for a reference speed larger than 300rpm.(2) The second order reference model was used to specify the wave-form of the step response, and good tracking performance was obtained for several damping coefficients and natural frequencies. The distortion of the step response for large amplitude inputs was much smaller than that of PI-D control.(3) A sudden change of the load torque or supplied air pressure was applied to the control system as a disturbance. The speed fluctuation was much the same as that of PI-D control.

Stable identification scheme for linear discrete-time systems

Abstract This paper is concerned with the problem of identifying parameters in stochastic systems described by single-input single-output linear discrete-time equations. A stable estimation error system is developed by using the extended Kalman filter technique and the concept of strictly positive real transfer function. The identifier corresponding to the estimation error system is constructed, and the convergence of parameter estimates to the exact values is proved under some bounded conditions. It is shown that the recursive maximum likelihood identifier and the recursive extended least squares identifier are obtained by neglecting the correction terms in the proposed identifier. Numerical examples for a fourth-order system are presented to illustrate the effectiveness of the proposed method.