Witold Ilewicz

Evaluation of calibration results using the least median of squares method in the case of linear multivariate models

Robust estimation procedures make it possible to reduce the leverage of outliers on the measurement results. Application of the least median of squares (LMS) method to determine the calibration curves of measuring instruments involves the need to evaluate the obtained results. This paper proposes the method of estimating the variance of the LMS regression coefficients, which allows the evaluation of the quality of the set regression coefficients. The concept of an a priori estimation consists in performing an estimation before the measurement experiment. The a posteriori estimation uses the data from the previously conducted measurement experiment, thus making it possible to obtain much more accurate results compared with the a priori method. Simulation tests were carried out in order to compare the estimation results with the ones obtained in the course of the simulated experiment. The obtained results confirm that the proposed concepts are correct.

On transformation of conditional action planning to linear programming

Planning in Artificial Intelligence is a problem of finding a sequence of actions that transform given initial state of the problem to desired goal situation. In this work we consider computational difficulty of so called conditional planning. Conditional planning is a problem of searching for plans that depend on sensory information and succeed no matter which of the possible initial states the world was actually in. Finding a plan of such problems is computationally difficult. To avoid this difficulty a transformation to Linear Programming Problem, illustrated by an example, is proposed.

Direct Method of IMU Calibration

In the paper a method for fast IMU calibration is described. The method need previously calibrated IMU, called standard IMU. Standard IMU and IMU to be calibrated have to have a solid mechanical connection. Then a sequention of movement is done and an outputs from both IMUs are recorded simultaneously. Outputs can be recorded with different sampling frequency for each IMU. Then an iterative procedure is employed for simultaneous fitting signal from calibrated IMU to standard IMU and aligning both signals, using least squares method. The point in 2-parameter space, that give best fit allows to calculate a calibration matrixes that describes linear dependence beetwen calibrated and sandard sensors. A method allows to calibrate all three-axis sensors (accelerometers, angular rate sensors and magnetometers) at the same time. Method is not-time-consuming and can be used to convenient in-field and on-object calibration of IMUs without a complicated calibration setup.

Influence of temperature on measurements of 3-axial accelerometers and gyroscopes: Embedded into inertial measurement unit

This paper presents the results of the study of influence of ambient temperature on the measurements of 3-axis linear acceleration sensors and gyroscopes used in IMU modules. The study was conducted using a climatic chamber, in which the six IMU modules were tested. Conducted tests covered a range of temperatures from -10 C to +60 C. The effect of ambient temperature on the values of zeros and gains of tested sensors was examined.

Comparison of baseline estimation algorithms for chromatographic signals

Baseline in signals is a relatively complicated problem in analysis of signals obtained in various analytical techniques such as chromatography and spectroscopy. In this article there are presented results of tests on four algorithms for a baseline estimation in chromatographic signals. Two of them are based on a polynomial fitting in a region of detected peaks. Another two algorithms, i.e. assymetric least squares method and iterative polynomial fitting with the automatic treshold, estimate the baseline under the whole signal and generally does not require peak detection. The tests of the algorithms are performed on both simulated and experimental signals.

Temperature Correction of Measurements Results of 3-Axis Accelerometers in IMU Modules

During temperature tests of 18 acceleration sensors in 6 IMU modules, conducted in a climate chamber at a temperature range from −10 to +60 °C, temperature characteristics of zeros and gains of tested sensors were obtained. An algorithm is presented for compensation of the sensor readings using temperature characteristics. We also report results of the effectiveness studies of temperature characteristics approximation by polynomials of various degrees.

Isopropanol concentration control in the ultrasonic nebulization process

The paper presents the application of the linearizing control technique for stabilization of the isopropanol concentration in the ultrasonic nebulization process. The isopropanol concentration has to be kept constant to make the nebulization process more efficient. This is achieved by manipulating the inlet flow rate of a fresh isopropanol-water mixture. Because the content of the vessel is not well-mixed, it was shown that by measuring only the isopropanol concentration at the bottom of the vessel, the control system performance could be improved by the optimal selection of controller parameters. Moreover, the simulation results have shown that the closed-loop system was stable and exhibited similar behavior, even if the nebulization rate was not know precisely.

On-line spectrophotometric measurements of isopropanol concentration in process of nebulization

The paper presents preliminary results for online measurement method of isopropanol concentration in the ultrasonic nebulization process using BW-Tek compact UV/Vis spectrophotometer. The experimental setup with nebulization vessel was constructed with a probe for on-line measurements. The tests were performed using a standard mixture of isopropanol and water with the volume isopropanol concentration in the range 19% to 83%. The results of on-line spectrophotometric method were verified using stationary spectrophotometer and a gas chromatography method. Linear calibration for the obtained data was performed and measurement uncertainties for the tested method were evaluated as confidence intervals.

On translation of conformant action planning to linear programming

Planning in Artificial Intelligence is a problem of finding a sequence of actions that transform given initial state of the problem to desired goal situation. In this work we consider computational difficulty of so called conformant planning. Conformant planning is a problem of searching for non-conditional plans that do not depend on sensory information, but still succeed no matter which of the possible initial states the world is actually in. Finding a plan of such problems is computationally difficult. To avoid this difficulty a transformation to Linear Programming Problem, illustrated by an example, is proposed.