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High‐performance active RC‐filters realised as a thick or thin‐film hybrid integrated circuit present special fabrication problems. Due to manufacturing tolerances of the circuit elements a vast majority of the filter circuits will probably not meet the performance specifications. As a consequence, the filter networks must be tuned after fabrication. In this paper, two recent algorithms amenable to computer automated functional tuning are reviewed. The algorithms formulate the tuning problem as an optimisation problem which is solved for the tuning amounts required. Then the tuning resistors are adjusted by that amount. The tuning algorithms are tested by examining their performance in tuning an active RC‐filter.

The purpose of this paper is to solve the problem of tuning of EKF parameters (process and measurement noise co-variance matrices) designed for attitude estimation using Global Positioning System (GPS) aided inertial sensors by employing a Human Opinion Dynamics (HOD)-based optimization technique and modifying the technique using maximum likelihood estimators and study its performance as compared to Particle Swarm Optimization (PSO) and manual tuning.

A model for the determination of attitude of flight vehicles using inertial sensors and GPS measurement is designed and experiments are carried out to collect raw sensor and reference data. An HOD-based model is utilized to estimate the optimized process and measurement noise co-variance matrix. Added to it, few modifications are proposed in the HOD model by utilizing maximum likelihood estimator and finally the results obtained by the proposed schemes analysed.

Analysis of the results shows that utilization of evolutionary algorithms for tuning is a significant improvement over manual tuning and both HOD and PSO-based methods are able to achieve the same level of accuracy. However, the HOD methods show better convergence and is easier to implement in terms of tuning parameters. Also, utilization of maximum likelihood estimator shows better search during initial iterations which increases the robustness of the algorithm.

The paper is unique in its sense that it utilizes a HOD-based model to solve tuning problem of EKF for attitude estimation.

The purpose of this paper is to introduce an artificial bee colony-based Kalman filter algorithm along with an extended objective function to ensure the optimality of the estimator of the quadrotor in the presence of unknown measurement noise statistics.

Six degree-of-freedom mathematical model of the quadrotor is derived. Position controller for the quadrotor is designed. Kalman filter-based estimation algorithm is implemented in the sensor feedback loop. Artificial bee colony-based hybrid algorithm is used as an optimization method to handle the unknown noise statistics. Existing objective function is extended with a penalty term. Mathematical proof of the extended objective function is derived. Results of the proposed algorithm is compared with de facto genetic algorithm-based Kalman filter.

Artificial bee colony algorithm-based Kalman filter and extended objective function duo are able to optimize the measurement noise covariance matrix with an absolute error as low as 0.001 [m²]. Proposed method and function is capable of reducing the noise from 2 to 0.09 [m] for x-axis, 3.4 to 0.14 [m] for y-axis and 3.7 to 0.2 [m] for z-axis, respectively.

The motivation behind this paper is to bring a novel optimization-based solution for the estimation problem of the quadrotor when the measurement noise statistics are unknown along with an extended objective function to prevent the infeasible solutions with mathematical convergence analysis.

The purpose of this paper is to improve the performance of control loop suffering from control valve stiction. Control valve stiction is considered as of one of the main causes of oscillation in process variables, which require performing costly unplanned maintenance and process shutdown. An adaptive solution to handle valve stiction while maintaining safety and quality until next planned maintenance is highly desirable to save considerable cost and effort.

This paper implements a new stiction compensation method built using adaptive inverse model techniques and intelligent control theories. Finite impulse response (FIR) model, which is known to be robust, as a compensator for stiction. The parameters of FIR model are tuned in an adaptive way using differential evolution (DE) technique. The performance of proposed method is compared with other two compensation techniques.

The new method showed excellent performance of the DE–FIR compensator compared to other dynamic inversion methods in terms of minimizing process variability, energy saving and valve stem aggressiveness.

The compensation ability for all compensators reduces with the increase of stiction severity, thus the over shoot case always shows the worst result. In future works, other optimization techniques will be explored to find the appropriate technique that can extend the FIR model size with smallest computation time that can improve the performance of the compensator in over shoot case. In addition, the estimation of the valve residual life based on the level of stiction and effort required by the controller should be considered.

The presented approach represents an original contribution to the literature. It performs stiction compensation without a need for a prior knowledge on the process or the valve models and guarantees a smooth control of the stem movement with a low control effort. The proposed approach differs from previous adaptive methods as it uses stable FIR models and DE to find the appropriate parameters of the inverse model and handle nonlinear behavior of stiction.

The purpose of this paper is to provide an analysis on using two non‐conventional nonlinear estimating filters compared to the traditional linearized extended Kalman filter (EKF). This analysis will look at two state‐of‐the‐art applications and will provide insight to the problems associated with these applications.

The approach taken was to simulate both applications with three different filter designs: EKF, unscented Kalman filter, and particle filter. After results and explanations are given for both applications, then there is a comparison of results between the two applications to compare and contrast their findings.

This research shows how critical it is when selecting a filter for different applications. Not only is tuning the filter properly a necessity, but choosing a filter that is optimum for the application also greatly affects the accuracy and precision of the results.

As these filter methods are proven feasible for these applications, testing can move beyond simulation. Further research could compare other nonlinear filters to these results to determine if a better estimation technique exists.

This paper shows a lot of the issues one must face when choosing an estimation technique for their application as well as the impact the technique can have on the outcome.

This paper clearly describes the decision‐making criteria in regards to these two specific applications. These two applications are current technological problems that many are trying to solve. This paper shows where and why errors in calculations occur. It also offers insight into different ways to solve these problems when the specific application is taken into account.

On October 31st 1985, 48 members of the ISHM‐Benelux Chapter met at the Delft University of Technology for the Autumn 1985 meeting.

The purpose of this paper is to design and construct an amplitude shift keying (ASK) modulator, which, using the digital binary modulating signal, controls a floating memristor emulator (MR) internally without the need for additional control circuits to achieve the ASK modulated wave.

A binary digital unipolar signal to be modulated is converted by a pre-processor circuit into a suitable bipolar modulating direct current (DC) signal for the control of the MR state, using current conveyors the carrier signal’s amplitude is varied with the change in the memristance of the floating MR. A high pass filter is then used to remove the DC control signal (modulating signal) leaving only the modulated carrier signal.

The results from the experiment and simulation are in agreement showed that the MR can be switched between two states and that a change in the carrier signals amplitude can be achieved by using an MR. Thus, showing that the circuit behavior is in line with the proposed theory and validating the said theory.

In this paper, the binary signal to be modulated is modified into a suitable control signal for the MR, thus the MR relies on the internal operation of the modulator circuit for the control of its memristance. An ASK modulation can then be achieved using a floating memristor without the need for additional circuits or signals to control its memristance.

This paper aims to present the prototype of a 140 kVA shunt active power filter (APF) for current harmonics and fundamental reactive power compensation of a 200 kW induction heating system.

Design issues of the power components, of the switching ripple filter and of the digital control are addressed and discussed. The APF control algorithm has been implemented on the 16‐bit, fixed‐point, TMS320LF2407 A DSP controller. The current control is based on proportional‐sinusoidal signal integrators with good performance in current harmonic elimination and power factor compensation.

The experimental tests, performed in real industrial environment for a 200 kW induction heating plant, show that the performance goals are fulfilled.

The sinusoidal signal integrators (for consistency with the other plural forms of acronyms) of the current controller are implemented in the rotating reference frame aligned with the voltage vector at the point of common connection. This allows the compensation of two harmonics with a single SSI, thus halving the computational effort of the DSP.

In industrial induction heating, the need for harmonic and reactive power compensation lasts a few seconds per minute, making passive solutions not suitable. The presented APF is a valid solution for this application, where only a few tailored implementations are available on the market.

A novel Ka-band compact parallel-coupled microstrip bandpass filter with harmonic suppression performance has been designed, implemented and tested on GaAs MMIC.

This proposed filter consists of modified coupled-line units with T-shaped open-stubs.

The proposed filter with T-shaped open-stubs is valuable in performance with low loss at fundamental frequency, suppression at harmonic frequencies and small size. The simulation is based on full-wave electromagnetic analysis and the measurement is based on chip test. It shows an insertion loss below 1.2 dB, return loss better than 20 dB in the pass band and high than 28 dB suppression at harmonic frequencies.

This Ka-band MMIC filter with harmonic suppression is attractive for the millimeter-wave system.

The purpose of this paper is to report the results of an industry-funded qualitative interdisciplinary research project that has produced a new approach to motorway noise management called “noise transformation”.

Four iterative design tests guided by listening as methodology. These included field recordings, laboratory tests and two field tests. Field tests were conducted in combination with ethnographers, who verified community responses to field-based transformations.

Transformation requires an audible perception of both background and introduced sounds in all instances. Transformation creates a 1–2 dB increase in background sound levels, making it counterintuitive to traditional noise attenuation approaches. Noise transformation is an electroacoustic soundscape design method that treats noise as a “design material”. When listening to motorway noise transformations, participants were actually experiencing another rendering of a sound that they had already acquired a degree of attunement to. Thus, they experienced transformations as somehow familiar or normal and easy to feel comfortable with.

Noise transformation is a new approach to noise management. Typically, noise management focusses on reduction in dB levels. Noise transformation focusses on changing the perceptual impact of noise to make it less annoying. It brings together urban design, composition and ethnography as a means to think about the future design of outdoor environments affected by motorway traffic noise, and should be of interests to planners, designers and artists. The authors have structured the paper around listening as methodology, through which both design and ethnography outcomes were achieved.