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Evaluating the results of image denoising algorithms in Computed Tomography (CT) scans typically involves several key metrics to assess noise reduction while preserving essential details. Full Reference (FR) quality evaluators are popular for evaluating image quality in denoising CT scans. There is limited information about using Blind/No Reference (NR) quality evaluators in the medical image area. This paper shows the previously utilized Natural Image Quality Evaluator (NIQE) in CT scans; this NIQE is commonly used as a photolike image evaluator and provides an extensive assessment of the optimum NIQE setting. The result was obtained using the library of good images. Most are also part of the Convolutional Neural Network (CNN) training dataset against the testing dataset, and a new dataset shows an optimum patch size and contrast levels suitable for the task. This evidence indicates a possibility of using the NIQE as a new option in evaluating denoised quality to find improvement or compare the quality between CNN models. [ABSTRACT FROM AUTHOR]

The trajectory tracking control performance of the wheeled mobile robot (WMR) is subject to position constraints, system uncertainties, and external disturbances. This paper explores the mechanism of the position constraints (equality and inequality) and considers the system uncertainties to be time-varying but bounded with fuzzy prescribed bounds. To solve the position constraints and uncertainties problems, a cooperative game-oriented optimal robust control method is proposed to provide high-precision, fast-response performance and robustness for WMR. First, a creative diffeomorphism transformation is proposed to convert the bounded state variables (subject to inequality constraints) into unbounded state variables. Accordingly, a restructured WMR system with the new state variables is established, which is free from inequality constraints. The uncertainties' bound is described as a fuzzy number by employing fuzzy set theory, which builds the fuzzy dynamic system of the WMR. Second, the control goal for this study is to drive the WMR to follow the position constraints despite uncertainties. An optimal robust control is developed to guarantee that the tracking errors of the WMR converge to a predefined neighborhood of origin. Using Lyapunov stability analysis, a fuzzy performance index is constructed, including steady-state performance, time performance, and control effort. The fuzzy performance index is employed as the cost function based on the cooperative game theory. The optimal control design is formulated to seek the Pareto-optimal solution of control parameters. Finally, the stability analysis and comparative experiments demonstrate that the proposed control algorithm can ensure the WMR's superior trajectory tracking convergence performance and strong robustness against uncertainties/disturbances. [ABSTRACT FROM AUTHOR]

Lightweight SiC-particle-reinforced aluminum composites have the potential to replace cast iron in brake discs, especially for electric vehicles. This study investigates the effect of SiC particle size and matrix alloy composition on the resulting transfer efficiency and particle distribution. The performance of a specially designed stirring head was studied using a water model, and the stirring head conditions were assessed to understand the particle transfer and dispersion mechanisms in the molten aluminum. The standard practice of thermal pre-treatment promotes the wetting of the reinforcing particles and commonly causes clustering before the addition to the melt. This early clustering affects the transfer efficiency and particle dispersion, where their interaction with the melt top-surface oxide skin plays an important role. In addition, the transfer efficiency was linked to the particle size and the chemical composition of the matrix alloy. Smaller particles aggravated the degree of clustering, and the addition of rare earth elements as alloying elements in the matrix alloy affected the particle dispersion. The stirring parameters should be selected to ensure cluster disruption when the carbides are added to the melt. [ABSTRACT FROM AUTHOR]

Computed Tomography (CT) is commonly used for cancer screening as it utilizes low radiation for the scan. One problem with low-dose scans is the noise artifacts associated with low photon count that can lead to a reduced success rate of cancer detection during radiologist assessment. The noise had to be removed to restore detail clarity. We propose a noise removal method using a new model Convolutional Neural Network (CNN). Even though the network training time is long, the result is better than other CNN models in quality score and visual observation. The proposed CNN model uses a stacked modified U-Net with a specific number of feature maps per layer to improve the image quality, observable on an average PSNR quality score improvement out of 174 images. The next best model has 0.54 points lower in the average score. The score difference is less than 1 point, but the image result is closer to the full-dose scan image. We used separate testing data to clarify that the model can handle different noise densities. Besides comparing the CNN configuration, we discuss the denoising quality of CNN compared to classical denoising in which the noise characteristics affect quality. [ABSTRACT FROM AUTHOR]

This article proposes a sliding mode control scheme with exact convergence time for uncertain nonlinear systems. Terminal time regulator is defined for designing the global exact‐time time‐varying sliding mode. The proposed method has the following advantages: first, the reaching phase is absolutely eliminated from the initial time such that the sliding mode invariance is identically guaranteed on an entire dynamics; second, on the sliding mode, the system state converges to the origin exactly at the predefined settling time instant, rather than at an uncertain time instant with boundedness as obtained by existing methods; third, the control signal of the proposed controller is bounded even when the time approaches to the predefined settling time; and fourth, low‐pass filtering is utilized to suppress the signal chattering in the discontinuous control while maintaining the system transient behaviors by selecting a proper time constant. Lyapunov analysis verifies that for any initial condition the closed‐loop system can terminally converge to zero exactly at the predefined time instant. The proposed control is finally generalized for Euler–Lagrange (EL) systems. [ABSTRACT FROM AUTHOR]

This article proposes a novel Stackelberg-game-oriented optimal control approach to address the bounded constraint-following control problem for uncertain mechanical systems. First, the uncertainties (possibly fast time-varying) in the system are assumed to be bounded with an unknown boundary, which lies in a specified fuzzy evidence number. In practical engineering, bounded system performance is always demanded, such as the inequality constraint. A diffeomorphism transformation approach is proposed to transform the constrained system into a restructured one satisfying the bounded constraint. Second, we propose an adaptive robust control oriented by the constraint-following control to render the restructured system to follow the specified constraints accurately with deterministic performance (guaranteeing uniform boundedness and uniform ultimate boundedness). The self-adjusting adaptive law (leakage-type) can compensate for the uncertainties and avoid overcompensation. Third, a Stackelberg-game-oriented optimization approach is proposed to obtain the optimal control parameters based on the fuzzy evidence theory. In the optimization approach, the two control parameters $\sigma$ and $\varepsilon$ are considered as two players with respective cost functions related to system performance and control cost. Furthermore, the optimization problem is solved by obtaining the Stackelberg strategy, which is proved to exist in analytic form. Ultimately, the permanent magnet synchronous linear motor system simulation is presented to show the design process and the excellent performance of the proposed optimal control scheme. [ABSTRACT FROM AUTHOR]

This article proposes a novel control design method for high-precision positioning systems. The method aims to eliminate the tracking error caused by measurement quantization present in positioning systems with incremental encoders. By employing a combined internal model based feedback and quantized feedforward design, we are able to make the output of the positioning system asymptotically track any input signal with one or more sinusoidal components of known frequencies and a possible constant component. When combined with a micro-actuator, the resulting dual-stage positioning system is able to track any continuous periodic signal with a known period. Besides theoretical guarantees, the proposed design is validated experimentally and proved able to achieve asymptotic tracking error below $\pm \text{1}\ \mu$ m when subject to a sensor quantization level of 5 $\mu$ m. [ABSTRACT FROM AUTHOR]

Narrow-band position error at midfrequencies around the open-loop crossover frequency cannot be effectively reduced by using a conventional peak filter, because the attenuation of sensitivity gains has to be traded off with the associated decrease of phase margin. This paper presents a general second-order filter that can reject narrow-band disturbances at any frequency range. The filter zero is designed to minimally degrade the closed-loop system stability and obtain a smooth sensitivity curve around the disturbance frequency. The paper presents a nonlinear optimization procedure for selecting the filter parameters so that the statistical position error is minimized. Experimental results of a piezoelectrically actuated head positioning control system on a spinstand demonstrate that the add-on filter can further reduce the midfrequency nonrepeatable runout of the position error signal by 8% and preserve the stability margin of the original feedback control system. Index Terms--Hard disk drive, narrow-band disturbance filter, PZT actuator, servo control, spinstand.

The dual-actuator hard disk drive with two voice coil motor actuators mounted in the diagonal corners of the baseplate allows faster data access with relatively slow spindle speed. However, the mechanical interaction between the actuators tends to affect the head positioning accuracy. In this paper, we use the circle-fit modal testing method to identify the dual-input dual-output frequency response model of the dual-actuator plant. We discuss the decentralized control scheme for the dual-actuator tracking servo. The servo loop decomposition reveals that the interaction induces narrow-band vibrations near the crossover frequency. We propose a phase-lead interaction filter with a slight change to the loop stability to suppress the vibrations. Experimental results on a dual-actuator prototype show that the position error signal 6[sigma] value due to interaction vibrations is reduced by 61% with the interaction filter in combination with the decentralized control scheme. Index Terms--Decentralized control, dual-actuator system, hard disk drive, identification, interaction.

Road transport and the associated fuel consumption plays a primary role in emissions. Weight reduction is critical to reaching the targeted reduction of 34% in 2025. Weight reduction in moving parts, such as pistons and brake disc rotors, provide a high-impact route to achieve this goal. The current study aims to investigate the formability of Al–Si alloys reinforced with different fractions and different sizes of SiCp to create an efficient and lightweight Al-MMC brake disk. Lanthanum (La) and cerium (Ce) were added to strengthen the aluminium matrix alloy and to improve the capability of the Al-MMC brake discs to withstand elevated temperature conditions, such as more extended braking periods. La and Ce formed intermetallic phases that further strengthened the composite. The analysis showed the processability and thermal stability of the different material's combinations: increased particle sizes and broader size range mixture supported the formation of the SiCp particle interactions, acting as an internal scaffolding. In conclusion, the additions of Ce and La strengthened the softer matrix regions and resulted in a doubled compression peak strength of the material without affecting the formability, as demonstrated by the processing maps. [ABSTRACT FROM AUTHOR]

In this paper, a novel methodology for estimating the parameters of robotic manipulator systems is proposed. It can be seen that, for the purpose of parameter estimation, the input torque to each joint motor is designed as a linear combination of sinusoids. After the transient responses of joint angles exponentially converge to zero, the steady states of joint angle outputs can be extracted. Since the steady states of joint angles are the equivalent finite Fourier series, the coefficients of the steady state components of joint angles can be further extracted in a fundamental period. With the amazing finding that the steady states contain all dynamic information of manipulator systems, all unknown parameters of the system model can be accurately estimated with the extracted coefficients in finite frequency bands. The simulation results for a two-link manipulator are carried out to illustrate the effectiveness and robustness against measurement noise of the proposed method. [ABSTRACT FROM AUTHOR]

As one type of unmanned aerial vehicles, the quadrotor typically suffers from payload variations, system uncertainties, and environmental wind disturbances, which significantly deteriorate its attitude control performance. To provide high-speed, accurate, and robust attitude tracking performance for the quadrotor, an adaptive fast nonsingular terminal sliding mode (AFNTSM) controller is proposed in this article. The proposed AFNTSM controller combines the advantages of fast nonsingular terminal sliding mode (FNTSM), integral sliding mode, and adaptive estimation techniques, which are effective to achieve the desired tracking performance and suppress control signal chattering. Furthermore, unlike conventional methods, the adaptive estimation removes the requirements for the upper bound information of the disturbances. It is proved that the proposed AFNTSM can guarantee finite-time convergence and zero tracking error for the quadrotor attitude control. Finally, comparative study with the FNTSM control only and conventional sliding mode control is conducted through experiments and the results demonstrate that the proposed AFNTSM can achieve faster convergence and stronger robustness in line with theoretical analysis. [ABSTRACT FROM AUTHOR]

The tracking performance of linear motor (LM) positioners is subject to payload uncertainty and external time-varying disturbances. Conventional robust controllers typically employ a high control gain that is substantially greater than the known a priori upper bound of the disturbance to ensure tracking error convergence. The main disadvantage of those controllers lies in that when the disturbance decreases, the control input is often overly generated, which then results in undesired control chattering effect or even actuator saturation. To overcome this problem, this article develops a robust tracking controller based on barrier function adaptive sliding mode (BFASM) for the LM positioners. The main benefits of BFASM are twofold: first, the controller is designed without the need for any disturbance information; second, its control gain is adaptively adjusted in terms of the amplitude of disturbance and, thus, leads to decreased control input when the disturbance becomes small. Furthermore, a modified barrier function (MBF) is proposed for applications with actuator saturation. It is proved that both the BFASM and MBF-based controllers can ensure the convergence of the tracking error into a prespecified neighborhood of zero in finite time. Experimental results on a real LM positioner demonstrate the superior properties of the developed controllers in comparison with two existing robust control schemes. [ABSTRACT FROM AUTHOR]