Data-Driven Filtered Smith Predictor for SISO Dead-Time Processes

Mobile applications present new image quality challenges. Automotive vision requires reliable capture of scene detail. Photospace measurements have shown that the extremely wide intrascene dynamic range of traffic scenes necessitates wide-dynamic-range (WDR) technology. Multiple-slope complementary metal-oxide semiconductor (CMOS) technology adaptively extends dynamic range by partially resetting the pixel, resulting in a response curve with piecewise linear slopes of progressively increasing compression. As compression and thus dynamic range increase, a trade-off against detail loss is observed. Incremental signal-to-noise ratio (iSNR) has been proposed in ISO/TC42 standards for determining dynamic range, and this work describes how to adapt these to WDR. Measurements and computer simulations reveal that the observed trade-off between WDR extension and the loss of local detail can be explained by a drop in iSNR at each reset point. If a reset is not timed optimally, then iSNR may drop below the detection limit causing an iSNR hole to appear within the dynamic range. Thus iSNR has extended utility: it not only determines the dynamic range limits but also defines dynamic range as the luminance range where detail detection is reliable. It has become the critical criterion when maximizing dynamic range to maintain the minimum necessary level of detection reliability.

The combination of the automatic control theory courses, simulation verification and practical implementation of the designed controller algorithms in real-time conditions is very important for training of the control engineers.This contribution present structure and usage of Self-tuning Controllers Simulink Library (STCSL) for real time control.The STCSL was created for design, simulation verification and especially realtime implementation of single input -single output (SISO) digital self-tuning controllers.The proposed adaptive controllers, which are included in the library, can be divided into three groups (PID controllers, controllers based on the polynomial approach and the controllers derived on the other approaches (minimum variance etc.).This Library is very successfully used in Adaptive Control Course in education practice for design and verification of self-tuning control systems in simulation and real-time conditions.It is suitable also for design and verification of industrial digital controllers.The highly nonlinear laboratory model, the DR300 Speed Control with Variable Load, has been chosen as example for real-time control.

Controller design is performed to meet some performance criteria. Some of them are the gain and phase margins, control effort, settling time, overshoot, amongst other indexes. Obtaining a controller or compensator that fits all these criteria (or some of them) for a closed loop control is done in both empirical and analytical procedures. The most of these procedures assumes the plant to be controlled could be modelled as first or second-order system. This paper aims to show a way to find the controller parameters based on the multi-objective optimization with a evolutionary approach. The systems to be controlled must be the type SISO (Single Input Single Output) whose transfer functions may have order higher than second order.

This paper presents a Proportional Integral Derivative (PID) controller design with the presence of an uncertain internal gain and additional time delay in the forward path of a 300 kW Solid Oxide Fuel Cell-Gas Turbine (SOFC-GT). The outputs of the system are turbine speed and the fuel cell mass flow rate. A fixed set of proportional controller coefficients are determined to graphically develop an area of selection for the integral and derivative coefficients of the PID controller. The inputs to the power plant are the electric load and cold air valve. The decentralized controllers are applied to four sub-systems as a Single Input Single Output (SISO). The PID controller coefficients are selected from a singular matrix solution that stabilizes the system and satisfies the internal gain and time delay uncertainties. Two sub-systems are the transfer functions of the turbine speed over the electric load and the cold air valve. The other two sub-systems are the transfer functions of the fuel cell mass flow rate over the electric load and the cold air bypass valve. Multiple options for selecting PID controller coefficients are beneficial to the SOFC-GT plant due to the wide range of operations and internal uncertainty interactions. The specific internal time delay and gain margins increase the reliability and robustness of the SOFC-GT with multiple uncertain parameters.

A two-stage Active Disturbance Rejection Control (ADRC) design procedure is presented for the output trajectory tracking control problem in Single Input Single Output (SISO) nonlinear systems. Aside from the given scalar system output, the plant is assumed to exhibit a second, physically measurable, internal scalar output variable. The system output is controlled in an ADRC manner from an implicit static, or dynamic, nonlinear feedback controller using, in general, a nonlinear differential expression of the internal output variable. A desired internal output trajectory is thus generated. The internal output variable, in turn, is controlled from the original input and forced to track the desired trajectory synthesized in the previous step by the auxiliary controller. Each ADRC controller design is based on a simplified model of the corresponding subsystem, usually relegating interaction variables and additive nonlinearities to be part of a local (total) disturbance input term. The control scheme is reduced to a set of linear ADRC controllers with, possibly, cancellation of nonlinear input gains which are assumed to be known. Two illustrative aerospace examples are presented where the proposed procedure is illustrated via digital computer simulations.

In this paper, a decoupled voltage mode control (DVMC) is proposed for a single-input dual-output Cuk converter (SIDO-CC) to eliminate the cross-coupling (CC) effect and maintain the desired output voltage. The DVMC consists of a decoupled network and a PI-based voltage controller. The SIDO-CC is synthesized from the conventional single input single output (SISO) Cuk converter by inserting an additional switch and inductor. However, the coupled capacitor present in the converter topology leads to a CC problem, which affects the converter stability. Therefore, a decoupling network is used in DVMC to eliminate CC among the control loops to allow independent controller design. Furthermore, in DVMC, two PI-based voltage control loops are designed to maintain constant output voltage during all operating conditions of the converter. To understand the system dynamics, a small-signal analysis of SIDO-CC is carried out using the state-space averaging technique, which yields system transfer functions for controller design. The proposed controller effectively traces the output voltages to desired values in the presence of input and output disturbances, which is validated by MATLAB simulations results.

The last three decades have seen rapid development in modern control theory and microprocessors. Application of newly developed control algorithms in Industrial process control has gained popularity due to microprocessor based control systems. In this chapter all categories of control algorithms which have gained popularity amongst industrial users or which are industrially implementable are covered. We have first covered control algorithms for single-input single-output (SISO) systems and then multi-input multi-output (MIMO) systems. Three term controllers, time delay compensation techniques and fuzzy logic controllers, etc., have been discussed for SISO plants. Predictive, adaptive, optimal and state feedback controllers have been covered for both SISO and MIMO plants. We have discussed auto tuning techniques for SISO PID controllers and also briefly expert control systems. Algorithms have been described in their digital implementation form. Implementation of control algorithms in industrially available distributed digital control system has been discussed. A brief report has been given for actual implementation of some algorithms in industrial plants and benefits due to this implementation have been highlighted. In particular applications of optimal control and optimal filtering in power industry in UK and power, cement and steel industry in Japan and predictive control techniques in petroleum industries in North America have been mentioned while describing the particular algorithm. Recent research results to pool resources of linear quadratic gaussian design popular in power, cement and steel industry and predictive control (model algorithmic control and internal model control) popular in petroleum industries to evolve a better approach to controller design have been highlighted.

This paper proposes a new state observer for a class of nonlinear systems with non negligible time delays in the output and Lipschitz nonlinearity. The proposed observer is composed of a chain of observers each of which estimates the states in different time instants, while the last observer estimates the state in the present time. This observer,unlike the previously introduced chain-like observers, introduces similar structure for all of the observation algorithms, is applicable for both of the stable and unstable nonlinear systems and has no limit for the value of time delay. Conditions for stability of the observer are translated into linear matrix inequalities (LMIs) to obtain the observer gains. Simulation results demonstrate effectiveness of this observer for both of the stable ans unstable systems.

This paper proposes a burst-mode optical fiber amplifier (OFA) that consists of a combination of an automatic gain controlled praseodymium-doped fiber amplifier (AGC-PDFA), a fast automatic level controlled circuit (ALC), and a PDFA with just forward pumping. The second PDFA is used as a booster to achieve high gain, over 20 dB. The combination of AGC and ALC techniques suppresses optical surge generation against strong burst signal inputs and also prevents overloading of the burst-mode receivers; it provides OFA-based passive optical network (PON) repeaters with wide input dynamic range and solves the near–far problem in upstream transmission in long-reach PONs. We experimentally compare the operating range of the proposed burst-mode PDFA with that of a conventional burst-mode PDFA. Experiments show that the proposed PDFA achieves a much wider operating area than a conventional PDFA; a wide dynamic range in an access span of 17.5 dB, which is equivalent to the input dynamic range of the burst-mode receiver used in 10 gigabit Ethernet PON (10G-EPON), is obtained with an allowable loss margin of 14 dB in a trunk span. A maximum link budget of 55 dB is achievable.

Proteome analysis currently heavily relies on tandem mass spectrometry (MS/MS), which does not fully utilize MS1 features, as many precursors remain unselected for MS/MS fragmentation, especially in the cases of low abundance samples and wide abundance dynamic range samples. Therefore, leveraging MS1 features as a complement to MS/MS has become an attractive option to improve the coverage of feature identification. Herein, we propose MonoMS1, an approach combining deep learning-based retention time, ion mobility, detectability prediction, and logistic regression-based scoring for MS1 feature identification. The approach achieved a significant increase in MS1 feature identification based on an E. coli data set. Application of MonoMS1 to data sets with wide dynamic range, such as human serum proteome samples, and with low sample abundance, such as single-cell proteome samples, enabled substantial complementation of MS/MS-based peptide and protein identification. This method opens a new avenue for proteomic analysis and can boost proteomic research on complex samples.

A reversible optical membrane sensor for detection of Hg(II) was developed based on the colorimetric determination of tetrathia-12-crown-4-Hg(II), incorporating chromoionophore I (ETH5294) as a lipophilic H+-selective indicator, and sodium tetra phenyl borate (NaTPB) as a lipophilic anionic site. A decrease in absorption of the membrane at 664 nm and/or increase at 555 nm could be used as a suitable wavelength for quantitative determination of Hg(II). This membrane is capable of determining mercury(II) ions over a wide linear dynamic range 1.0 × 10−9 to 9.5 × 10−5 mol L−1 Hg(II) at pH 7.0 with detection limits of 8.1 × 10−10 mol L−1 Hg(II) and response time of 100 s. The optode reveals a very good selectivity toward Hg(II) ions over a wide variety of other metal ions in solution and the response to Hg(II) is fully reversible. Performance characteristics of the sensor evaluated as good reversibility, wide dynamic range, long life span, long-term response stability, and high reproducibility. The optode was applied to the determination of mercury(II) in water samples. The accuracy of the results was comparable to those obtained by cold vapor atomic absorption spectrometry.

Metal-oxide nano-porous microstructures have shown high electrocatalytic activity toward hydrogen peroxide oxidation. In this paper, we establish the copper oxide (CuO) porous hollow structures via the hydrothermal method using pluronic F-127 as a surfactant. The electrochemical performance involves the oxidation between Cu(I) and Cu(II) at room temperature. For verifying the formation of the desired morphology of CuO porous hollow structures, the scanning electron microscopy, Fourier-transform infrared spectroscopy (FTIR), Raman spectroscopy, X-ray diffraction spectroscopy and H2-temperature-programmed reduction (TPR) were applied. The synthesized samples are hollow microstructures which are formed by CuO nanoparticles. The achieved CuO hollow structures exhibit excellent H2O2 detection properties such as a very low detection limit of 141.1 nM, an extremely wide dynamic detection range of 50 nM–70 mM, an outstanding sensitivity of 13.7 µA µM−1 cm−2 and satisfactory stability in alkaline solution. The good tolerance toward interfering species, the satisfactory behaviour in repeatability and reproducibility and favourable stability verified the promising performance of the proposed sensor. The results of the study on sensing low levels of H2O2 concentrations by using a modified glassy carbon electrode as an optimized electrochemical sensor have been reported. The proposed synthesized nanostructures (CuO porous hollow structures) can be used as sensitive H2O2 biosensors. Essential characterizations and measurements have been performed. The constructed sensor shows acceptable electrocatalytic activity for detecting H2O2. High sensitivity, very low LOD, wide dynamic range, excellent tolerance toward interfering agents, favorable stability and satisfactory reproducibility and repeatability of the sensor have made it suitable for practical applications.

This article deals with the problem of optimal static output feedback control of linear periodic systems in continuous time, for which a continuous-time approach, which allows to deal with both stable and unstable open loop systems, is presented. The proposed approach is tested on the problem of designing attitude control laws for a Low-Earth Orbit (LEO) satellite on the basis of feedback from a triaxial magnetometer and a set of high-precision gyros. Simulation results are used to demonstrate the feasibility of the proposed strategy and to evaluate its performance.

Digital detectors in mammography have wide dynamic range in addition to the benefit of decoupled acquisition and display. How wide the dynamic range is and how it compares to film-screen systems in the clinical x-ray exposure domain are unclear. In this work, we compare the effective dynamic ranges of film-screen and flat panel mammography systems, along with the dynamic ranges of their component image receptors in the clinical x-ray exposure domain. An ACR mammography phantom was imaged using variable mAs (exposure) values for both systems. The dynamic range of the contrast-limited film-screen system was defined as that ratio of mAs (exposure) values for a 26 kVp Mo/Mo (HVL=0.34 mm Al) beam that yielded passing phantom scores. The same approach was done for the noise-limited digital system. Data from three independent observers delineated a useful phantom background optical density range of 1.27 to 2.63, which corresponded to a dynamic range of 2.3 +/- 0.53. The digital system had a dynamic range of 9.9 +/- 1.8, which was wider than the film-screen system (p<0.02). The dynamic range of the film-screen system was limited by the dynamic range of the film. The digital detector, on the other hand, had an estimated dynamic range of 42, which was wider than the dynamic range of the digital system in its entirety by a factor of 4. The generator/tube combination was the limiting factor in determining the digital system's dynamic range.

Adaptive MPC for Uncertain Discrete-Time LTI MIMO Systems with Incremental Input Constraints