Constant Sampling Time Research Articles

A Review on stability and passivity analysis of haptic devices

Haptic devices are robots that are used for simulating virtual objects for their operators. Since most real objects can be modelled by spring and dampers, the virtual object is also a (discrete) spring and damper. The discretization is done with a constant sampling time, while a time delay may exist in the control loop, due to do different sources. Simulating stiff objects is a challenging problem since severe vibrations occur in the body of the haptic device and may damage itself or even its operator. The stable operation of a haptic device is a key problem in all haptic applications. It is shown that using smaller values of sampling time and time delay, can make an increase in the stability domain; while increasing effective mass and friction has the same result. In this paper, a review of the stability and passivity of haptic devices is presented and helps the readers to know better recent activities in this field.

Research of controller of Permanent magnet linear synchronous motors via model predictive direct thrust control

How to achieve high-precision control is the core issues of the linear motor research. To solve this problem, this paper proposes a new control algorithm. on the one hand, through the sliding mode control for the unknown torque observations, in the process of observation, select a specific based function to approximate the sign function in order to eliminate the jitter of the vicinity of the switching surface; On the other hand, the use of model predictive control method (Model Predictive Control) to achieve the torque compensator track to achieve the velocity and displacement tracking. The constant sampling time of the model predictive control in the new method can effectively avoid the problems that the number of switching per unit time of the inverter can’t be expected.

A Linear Recursive State of Power Estimation for Fusion Model Component Analysis with Constant Sampling Time

The state of power of lithium-ion batteries, as the main product of choice for electric and hybrid electric vehicle energy storage systems, is one of the precise feedback control parameters for the battery management system. The proposed research establishes a method for the analysis of charging and discharging constitutive factors under the sampling time, realizes the online identification of parameters by building an adaptive forgetting factor recursive least-squares method based on the Thevenin model, and uses the online parameters to achieve an effective characterization of the power state under voltage and current limitations. The results demonstrate that the accuracy error of online parameter identification is less than 0.03 V. Combining the analysis of charging and discharging constitutive factors under-sampling time with the fusion model of voltage and current limitation makes the power state estimation more reliable and accurate. The results demonstrate that the power state estimation error in the discharging state is less than 8%.

An Improved Model Predictive Control Method to Drive an Induction Motor Fed by Three-Level Diode-Clamped Indirect Matrix Converter

In this paper, an improved model predictive control method is proposed to drive an induction motor fed by a three-level matrix converter. The main objective of this paper is to present a novel method to increase the switching frequency at a constant sampling time. Also, it is analytically discussed that increasing the switching frequency not only can decrease the motor current ripples, but it can also significantly reduce its torque ripples. Finally, this study demonstrates that reducing the motor current ripple will improve the quality of the supply current. To be the accurate model and validate the motor drive system, a co-simulation method, which is a combination of FLUX and MATLAB software packages, is employed to find the simulation results. The findings indicate that the proposed method diminishes the THD of the supply current up to 26% approximately. Furthermore, increasing the switching frequency results in the torque ripple reduction by up to 10% almost.

Active Collision Avoidance System Design Based on Model Predictive Control with Varying Sampling Time

In active collision avoidance, the trajectory tracking controller determines the deviation from the reference path and the vehicle stability. The main objective of this study was to reduce the tracking error and improve the tracking performance in collision avoidance. Unlike the previously proposed model predictive control (MPC) strategies with constant sampling time, an improved MPC controller with varying sampling time based on the hierarchical control framework was proposed in this paper. Compared with the original MPC tracking controller, the improved MPC controller demonstrated better adaptive capability for the varying road adhesion coefficients and vehicle speed on a curved road. The simulation results revealed that the hierarchical control framework generated an optimal trajectory for collision avoidance in real-time by minimizing the potential field energy.

A Simple Self-Tuning Resonant Control Approach for Power Converters Connected to Micro-Grids With Distorted Voltage Conditions

Over the last few decades, the consolidated goal of reducing greenhouse gasses has increased the relevance of renewable energy research, electromobility, energy storage, and distributed generation, micro-grids, among others. Micro-grids, systems working in islanding mode, are particular cases where some disadvantages are present due to the wide variations which may appear across their electrical quantities. Variations on the voltage amplitude and the frequency are intrinsic in the operation of weak grids, because they have low inertia and therefore the load must be able to cope with these variations, otherwise loads may trip electrical system protection. Particularly, on power electronic drives, these frequency deviations will lead to increased system nonlinearities, entailing a more critical controller design. To overcome these issues, this paper presents an implementation of a resonant controller with self-tuned gains. The strategy imposes a constant sampling time which allows these controllers to be used in variable frequency environments. In addition, the computational capacity required for the digital board is also considered. The simulated and experimental results provided demonstrate the good performance of this proposal.

TS-based sampled-data model predictive controller for continuous-time nonlinear systems

This paper proposes a new fuzzy model predictive control approach for continuous-time nonlinear systems in terms of linear matrix inequalities (LMIs). The proposed approach is based on the Takagi–Sugeno fuzzy modeling, a quadratic Lyapunov function, and a sampled-data parallel distributed compensation controller with constant sampling time. The goal is designing the sampled-data controller such that at each sampling time, the stability of the closed-loop system is guaranteed and an infinite horizon cost function is minimised. The main advantage of the proposed approach is to eliminate the approximations induced from discretizing the original system and cost function upper bound minimisation. Consequently, a lower bound of the cost function is obtained and the performance of the proposed model predictive controller is improved compared to the recently published papers in the same field of interest. In addition, the Euclidean norm constraint of the control input vector is derived in terms of LMIs. To illustrate the merits of the proposed approach, the proposed technique is applied to a continuous stirred tank reactor system.

A control-oriented thermal model for a moving dual-layer substrate

This paper describes an early lumping approach for generating a mathematical model of the heating process of a moving dual-layer substrate. The heat is supplied by convection and nonlinearly distributed over the whole considered spatial extend of the substrate. Using CFD simulations as a reference, two different modelling approaches have been investigated in order to achieve the most suitable model type. It is shown that due to the possibility of using the transition matrix for time discretization, an equivalent circuit model achieves superior results when compared to the Crank-Nicolson method. In order to maintain a constant sampling time for the in-visioned-control strategies, the effect of variable speed is transformed into a system description, where the state vector has constant length but a variable number of non-zero entries. The handling of the variable transport speed during the heating process is considered as the main contribution of this work. The result is a model, suitable for being used in future control strategies.

Quality Prediction of Refined Bleached Deodorized Palm Oil (RBDPO) Using Partial Least Square Regression Technique

Out of specification in the production of Refined Bleached Deodorized Palm Oil (RBDPO) will cause recycling in palm oil refining process as well as zero production during that period. Hence, the ability to predict the output quality variables so that appropriate adjustment can be made in the process beforehand is very useful in minimizing the production cost and time consumption. In this study, Multivariate Statistical Process Control (MSPC) is used to develop a prediction tool in order to predict the output quality variables before the process even began and eventually reduce the utility cost as compare to traditional method of using tacit knowledge which is not very practical. Knowing product quality in advance, adjustment can be made at the specific unit operation and also to identify in which standard the quality variables belongs to, be it Palm Oil Refiners Association Malaysia (PORAM) standard, China or Vietnam. The MSPC method used in this study is Partial Least Squares Regression (PLS) which capable in finding the relationships between the process and quality variables of the palm oil refining process assuming that the data are linear. In simulation, data used are obtained from Lahad Datu Edible Oil Sdn. Bhd. (LDEO) with percentage of fatty acid (FFA), moisture content, and iodine value as both the process and quality variable which undergone pre-screening and pre-processing of data. This study also considers a constant sampling time to ensure the randomness of the data as well as the residence time in determining the relationships of the quality variables corresponded to the actual process variables. Simulation results obtained from developed correlation coefficient are evaluated and compared using Mean Squared Error (MSE). MSE results shows that PLS method is capable in predicting the output quality variables.

Adaptive Energy Management System Based on a Real-Time Model Predictive Control With Nonuniform Sampling Time for Multiple Energy Storage Electric Vehicle

The performance of a dual energy storage electric vehicle system mainly depends on the quality of its power and energy managements. A real-time management strategy supported by a model predictive control (MPC) using the nonuniform sampling time concept is developed and fully addressed in this paper. First, the overall multiple energy storage powertrain model including its inner control layer is represented with the energetic macroscopic representation and used to introduce the energy strategy level. The model of the system with its inner control layer is translated into the state-space domain in order to develop an MPC approach. The management algorithm based on mixed short- and long-term predictions is compared to rule-based and constant sampling time MPC strategies in order to assess its performance and its ability to be used in a real vehicle. The real-time simulation results indicate that, compared to other strategies, the proposed MPC strategy can balance the power and the energy of the dual energy storage system more effectively, and reduce the stress on batteries. Moreover, battery and supercapacitor key variables are kept within safety limits, increasing the lifetime of the overall system.

Consistent Estimation of Randomly Sampled Ornstein–Uhlenbeck Process Long-Run Mean for Long-Term Target State Prediction

In this letter, we study the problem of estimating the long-run mean of the Ornstein–Uhlenbeck (OU) stochastic process and its effect on the long-term prediction of future vessel states, which is a crucial problem for Maritime Situational Awareness (MSA). We employ a sample mean estimator (SME) to estimate the key OU parameter from the observations, computing the closed-form SME covariance error in both the random and constant sampling time regimes, providing a fundamental building block of the overall long-term state prediction covariance. We show also that the SME is: $\sqrt{n}$ -consistent when the sampling time is random; asymptotically efficient when the sampling time is constant; and very close to the Cramer–Rao lower bound in the cases of practical interest for MSA.

Generalized Predictive Control With Actuator Deadband for Event-Based Approaches

This work presents an event-based control structure using the generalized predictive control (GPC) algorithm with actuator deadband. The main objective of this work is to limit the number of controlled system updates. In this approach, the controlled process is sampled with a constant sampling time and is updated in an asynchronous way that depends on the obtained control signal value. To achieve the desired control properties, a hybrid system framework is used to model the virtual actuator deadband. The deadband is modeled as system input constraints in the GPC's optimization procedure, exploring mixed integer quadratic programming (MIQP) techniques. The presented control structure considers adjustable actuator deadband as an additional tuning parameter and allows a tradeoff between control performance and the number of events/updates. This fact is very important for the lifetime of the actuators and minimizes their wear, especially for mechanical and electromechanical systems. The minimization of actuator usage can be also understood as an economical saving. Other benefits can be found in distributed control systems, where various control system agents are connected through computer networks, and where a reduction in communication is always welcome.

A New Method to Enhance Performance of Digital Frequency Measurement and Minimize the Clock Skew

There are different ways to measure frequency. But in most of the methods the systems are failed to provide good sensitivity or to maintain constant relative errors. This paper presents a new wide-range speed measurement method, using the direct memory access (DMA) terminal count register. The measure ends are interfaced with DMA channels through pipelines to improve hit ratio. Here hit ratio indicates the exact identification of encoder pulses without any fail or miss. The DMA method is based on pulses counting in the constant sampling time at terminal count stop pin of a DMA controller. A pipe line technology is built in the system to reduce the data losses during not ready sequence of DMA operations. But the conventional pipeline system is facing problems due to improper synchronization of clock pulses. This is a universal problem in all the digital systems mostly called jitter or skew. In most of the digital systems the propagation of information mainly controlled on the basis of clock pulses. In most of the digital systems the clock skew decreases the performance of the digital systems. Here a new system is implemented in the path of the clock to remove or reduce the clock skew.

Evaluation of the number of sampling step angles in SPECT Images: comparison between FBP and OS-EM reconstruction algorithms

We compared filtered back projection (FBP) and ordered subset expectation maximization (OS-EM) reconstruction algorithms to examine the effects of sampling step angle on SPECT image reconstruction. Image sampling was compared between conditions of constant total sampling time (16 min) and constant sampling time (40 sec) for each step with angles of 3, 5, 7.5, and 10 degrees. Generally, OS-EM was superior to FBP in terms of image reconstruction. Changes in the sampling step angles did not significantly affect the quality of the reconstructed images with OS-EM insofar as acquisition counts were sufficient for evaluation. On the other hand, the quality of FBP images deteriorated with larger angles such as 7.5 and 10 degrees, and it was difficult to obtain stable results. In conclusion, OS-EM improves the quality of images required for examination.

A Simulation Method for High-Speed and High-Accuracy Calculation

This paper deals with a computer simulation method, which can realize high-speed and high-accuracy. The proposed method is characterized by both introducing the so-called discrete-time system with variable-sampling time and treating the digital control system as the discrete-time system with constant-sampling time. The proposed method is applied to a position-sensorless IPM motor drive system, which has been proposed by the authors. Simulated results show that the proposed method achieves more accurate and efficient simulation than conventional methods do.

A Monitoring Tape for Chlorine Gas with N,N-Diethyl-p-Phenylenediamine Sulfate.

A porous cellulose tape impregnated with a processing solution that includes N, N-Diethyl-p-phenylenediamine (DPD) sulfate, glycerin and methanol was developed for the detection of chlorine gas in air. When the sample is passed through the tape, chlorine reacts with DPD to form a red stain. The intensity of the red stain is proportional to the concentration of chlorine at a constant sampling time and flow rate, and was recorded by measuring the intensity of reflected light (555 nm) . The detection limit was 0.03 ppm of chlorine with a sampling time of 60 s and a flow rate of 200 ml min-1. The sensitivity of the tape could be maintained for at least 1 month when stored in dark clean box.Reproducibility tests showed that the relative standard deviations of the response (n=10) was 2.5 % for 0.1ppm of chlorine gas. No interference was observed from ethanol (1 vol.%), acetone (1 vol.%), trichloroethylene (1 vol.%), carbon monoxide (100 ppm), hydrogen sulfide (30 ppm), sulfur dioxide (51 ppm) or ozone (2 ppm) .The relative intensities of nitrogen dioxide and fluorine gas were 25 and 13 % of that of chlorine, respectively.

Applying the uniform resampling (URS) algorithm to a lissajous trajectory: fast image reconstruction with optimal gridding.

Various kinds of nonrectilinear Cartesian k-space trajectories have been studied, such as spiral, circular, and rosette trajectories. Although the nonrectilinear Cartesian sampling techniques generally have the advantage of fast data acquisition, the gridding process prior to 2D-FFT image reconstruction usually requires a number of additional calculations, thus necessitating an increase in the computation time. Further, the reconstructed image often exhibits artifacts resulting from both the k-space sampling pattern and the gridding procedure. To date, it has been demonstrated in only a few studies that the special geometric sampling patterns of certain specific trajectories facilitate fast image reconstruction. In other words, the inherent link among the trajectory, the sampling scheme, and the associated complexity of the regridding/reconstruction process has been investigated to only a limited extent. In this study, it is demonstrated that a Lissajous trajectory has the special geometric characteristics necessary for rapid reconstruction of nonrectilinear Cartesian k-space trajectories with constant sampling time intervals. Because of the applicability of a uniform resampling (URS) algorithm, a high-quality reconstructed image is obtained in a short reconstruction time when compared to other gridding algorithms.

An automatic measurement of hydrogen cyanide in air by a monitoring tape method

An automatic monitor has been developed for hydrogen cyanide gas in air using a sensitive tape for hydrogen cyanide. It is based on color change of the tape by reaction with hydrogen cyanide. The tape containing silica gel as an absorbent and impregnated with a processing solution that includes 4,4′-bis(dimethylamino)diphenylmethane(tetrabase), copper(II) acetate, butylhydroxytoluene, glycerin and methanol was found to be a highly sensitive means of detecting hydrogen cyanide gas and it maintained stable sensitivity for at least a month in the air of a desiccator. When an air sample including hydrogen cyanide gas was passed through the tape, hydrogen cyanide was absorbed on the surface of the tape, and it reacted with copper(I) ion producing CuCN; then the tetrabase was oxidized by Cu(II) ion to form a stain. The intensity of the stain was proportional to the concentration of hydrogen cyanide at a constant sampling time and flow rate, and it could be recorded by measuring the intensity of reflecting light (555 nm). The detection limit ( S/ N = 3) was 0.2 ppm for hydrogen cyanide gas with a sampling time of 60 s and a flow rate of 400 ml/min. Reproducibility tests showed that the relative standard deviation of response ( n = 6) was 2.2% for 5 ppm hydrogen cyanide. No response was observed from methanol (1 vol.%), acetone (1 vol.%), carbon dioxide (4.9 vol.%), carbon monoxide (100 ppm), sulfur dioxide (50 ppm), hydrogen chloride gas (8 ppm), nitrogen monoxide (50 ppm), nitrogen dioxide (4 ppm), or ammonia (40 ppm).

Development of a monitoring system for vinyl chloride gas in air by using an HCl monitoring tape and pyrolyzer

A continuous monitoring system for vinyl chloride gas in air has been developed using an HCl monitoring tape and pyrolyzer consisting of a heater around a quartz tube. It is based on the color change of the tape by reaction with HCl gas produced by decomposition of vinyl chloride gas in the heated quartz tube. The conversion efficiency of vinyl chloride into HCl depends on the temperature of the pyrolyzer. The tape impregnated with a coloring solution that includes Metanil Yellow (pH indicator; pH 1.2–2.3, red-yellow), glycerin and methanol is a highly sensitive means of detecting HCl gas. When vinyl chloride gas was passed through the heated quartz tube (910°C) and the HCl gas produced was passed through the tape, the color of the tape changed from yellow to red. The degree of color change was proportional to the concentration of vinyl chloride gas with a constant sampling time and flow rate. The degree of color change could be recorded by measuring the intensity of reflecting light (555 nm). This method is scarcely affected by other gases with the exception of chlorinated hydrocarbons such as trichloroethylene and chloroform or strong acids such as HCl gas. Reproducibility tests showed that the relative standard deviation of the relative intensity ( n = 10) was 4.5 for 5 ppm vinyl chloride. The detection limit was 0.4 ppm for vinyl chloride with a sampling time of 40 s and a flow rate of 300 ml min −1.

Development of a monitoring tape for nitrogen dioxide in air

A porous cellulose tape containing a silica gel impregnated with a processing solution that includes p-toluenesulfonic acid, sulfanilic acid, N-(1-naphthyl)ethylenediamine dihydrochloride, glycerin and methanol has been developed to provide a highly sensitive means of detecting nitrogen dioxide in air. When the sample including nitrogen dioxide was passed through the tape, the color of tape changed to red. The degree of color change was proportional to the concentration of nitrogen dioxide at a constant sampling time of flow rate. The degree of color change could be recorded by measuring the intensity of reflecting light (555 nm). The detection limit was 1 ppb for nitrogen dioxide with a sampling time of 10 min and a flow rate of 30 ml/min. Reproducibility tests showed that the relative standard deviation of response ( n = 10) was 3.5% for 0.1 ppm nitrogen dioxide. No interference was observed from methanol (0.5 vol.%), ammonia (40 ppm), ethylene (99.9 vol.%), hydrogen (99.9%), carbon monoxide (306 ppm), sulfur dioxide (50.6 ppm), carbon dioxide (20.5 vol.%), chlorine (2.5 ppm), hydrogen sulfide (27.1 ppm) or nitrogen monoxide (99.1 ppm).