Practical Tracking Control Under Actuator Saturation for a Class of Flexible-Joint Robotic Manipulators Driven by DC Motors

This paper is devoted to the practical tracking control for a class of flexible-joint robotic manipulators driven by DC motors. Different from the related literature where control constraint is neglected and the disturbances are excluded or only exist in one subsystem, actuator saturation is considered in this paper while the disturbances are present in all the three subsystems. This leads to the incapability of the traditional schemes on this topic. For this, a novel control design scheme is proposed by skillfully incorporating adaptive dynamic compensation technique, constructive methods of command filters and an auxiliary system for the actuator saturation into the backstepping framework, and in turn to design a practical tracking controller which ensures that all the states of the resulting closed-loop system are bounded and the system output practically tracks the reference signal. It is worthwhile strengthening that a more wider class of reference signals can be tracked since they are only first order continuously differentiable but twice or more in the related literature. Finally, a numerical example is provided to validate the effectiveness of the proposed theoretical results.

DESIGN IMPLEMENTATION ANDON FOR PRODUCTION MONITORING SYSTEM BASED ON INTERNET OF THINGS

Each production requires a system monitoring, so efficiency that the desired and productivity can be achieved and monitored in real time. This system is needed in the type of press machine production which is mainly influenced by based production lead time. The monitoring process is one of the factors that influences the time of production and manufacturing. Conventionally, the system is monitoring carried out manually by the operator on a piece of paper. This method tends to create errors and quite a long time. This paper aims to overcome the problems that occur by creating a system that is able to record and monitor the machine automatically. The solution is made by utilizing a sensor limit switch, infrared, pressure transmitter and Wi-Fi network based on Web Interface that is connected to the Firebase real time database. Equipped with PID control using the Ziegler Nichols 1 method to stabilize wind pressure on the system. Monitoring devices can be accessed on PCs, laptops, smartphones, connected to the internet, equipped with user-level operators, management, or engineers so that they can be used easily. All production data for each press is collected in a database. The data will be processed by the system to produce a value OEE machine. All data will be displayed on the Web Interface in real-time. The system output is the actual production, value OEE and wind pressure control. The test results show the system is running well, with 2s delay time and data accuracy of ± 0.2%.

Pemilihan Daerah Penerima Bantuan Logistik Menggunakan Metode Simple Additive Weighting (SAW)

Deputy for Logistics and Equipment is a unit that handles requests for logistical assistance along with equipment in areas that need assistance related to disasters that occur. Provision of Logistics Assistance so far there are still some obstacles including the process of calculating each region that proposes logistics assistance is done with a simple calculation and using microsoft excell and aspects calculated only based on disaster-prone categories without taking into account other aspects. So that areas that really deserve logistical assistance become unable to get help. The solution to the problem is to use Simple Additive Weighting (SAW) algorithm that is applied to a decision support system. The results of the study in the form of a decision support system and the results of the system output showed that the recipient area was Aceh which was chosen with a score of 81.17.

Variance and Entropy Assignment for Continuous-Time Stochastic Nonlinear Systems

This paper investigates the randomness assignment problem for a class of continuous-time stochastic nonlinear systems, where variance and entropy are employed to describe the investigated systems. In particular, the system model is formulated by a stochastic differential equation. Due to the nonlinearities of the systems, the probability density functions of the system state and system output cannot be characterised as Gaussian even if the system is subjected to Brownian motion. To deal with the non-Gaussian randomness, we present a novel backstepping-based design approach to convert the stochastic nonlinear system to a linear stochastic process, thus the variance and entropy of the system variables can be formulated analytically by the solving Fokker–Planck–Kolmogorov equation. In this way, the design parameter of the backstepping procedure can be then obtained to achieve the variance and entropy assignment. In addition, the stability of the proposed design scheme can be guaranteed and the multi-variate case is also discussed. In order to validate the design approach, the simulation results are provided to show the effectiveness of the proposed algorithm.

Sensor fault detection and reconstruction system for commercial aircrafts

The aim morphing of this study is to detect and reconstruct a fault in angle-of-attack sensor and pitot probes that are components in commercial aircrafts, without false alarm and no need for additional measurements. Real flight data collected from a local airline was used to design the relevant system. Correlation analysis was performed to select the data related to the angle-of-attack and airspeed. Fault detection and reconstruction were carried out by using Adaptive Neural Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANN), which are machine-learning methods. No false alarm was detected when the fault test following the fault modeling was carried out at 0–1 s range by filtering the residual signal. When the fault was detected, fault reconstruction process was initiated so that system output could be achieved according to estimated sensor data. Instead of using the methods based on hardware redundancy, we designed a new system within the scope of this study.

Prototype Automation of Air Conditioning Treatment in the Grinding Area Aneka Cocoa Based on IoT

A good work environment will affect the level of productivity of workers in a company. The operation of the refrigeration machine in the cocoa powder grinding area is very important in production. The indicators for the operation of the cooling machine are dust density, ambient temperature and wind speed. With control on the indicator will increase efficiency. In this study, the indicator is controlled with a GP2Y1010AUF0F dust sensor, a DHT22 temperature sensor, a DS18B20 sensor, and a wind speed sensor as sensor inputs. Furthermore, the sensor will be processed by the Node M CU ESP826 module. System output will be displayed on LED and android. The results of this study indicate the accuracy of the dust sensor is 96.12%, the DHT22 temperature sensor is 99.80%, the DS18B20 temperature sensor is 99.57% and the speed sensor is 95.89%. In this prototype, we can monitor the temperature of the air velocity of dust particles in the engine and the temperature of the engine cooler together and closely monitored.

Development and Parametric Analysis of Vibration System Controlled by Hydraulic Shock Rotary Vibrator

The improvement of the energy utilization rate of a hydraulic vibration-excitation system is critical to the research and development of hydraulic vibration equipment. In this paper, a hydraulic vibration-excitation system controlled by a new type of shock rotary vibrator is proposed. A system model considering the pipeline effect was established for the hydraulic shock phenomenon. In addition, the model was compared with the one that does not consider the pipeline effect. The effectiveness of the proposed model was verified experimentally. Finally, the shock phenomenon during the process of switching the working state of the vibrator and the influence of certain important parameters of the system on the vibration output were investigated based on the proposed model. The results showed that (1) the hydraulic shock phenomenon occurred when the working state of the hydraulic vibrator was switched and (2) the hydraulic shock wave could effectively improve the excitation force of the system. The excitation force increased with an increase in the oil supply pressure, spindle speed, and load. However, it was negatively correlated with the spring stiffness. The amplitude of the vibration waveform output was positively correlated with the oil supply pressure and negatively correlated with the spindle speed and load. The amplitude first increased and then decreased as the stiffness of the vibration spring increased. The only influence of the precompressed length of the spring on the system output was its alteration of the vibration center of the system output vibration.

A Two-Filter Approach for State Estimation Utilizing Quantized Output Data

Filtering and smoothing algorithms are key tools to develop decision-making strategies and parameter identification techniques in different areas of research, such as economics, financial data analysis, communications, and control systems. These algorithms are used to obtain an estimation of the system state based on the sequentially available noisy measurements of the system output. In a real-world system, the noisy measurements can suffer a significant loss of information due to (among others): (i) a reduced resolution of cost-effective sensors typically used in practice or (ii) a digitalization process for storing or transmitting the measurements through a communication channel using a minimum amount of resources. Thus, obtaining suitable state estimates in this context is essential. In this paper, Gaussian sum filtering and smoothing algorithms are developed in order to deal with noisy measurements that are also subject to quantization. In this approach, the probability mass function of the quantized output given the state is characterized by an integral equation. This integral was approximated by using a Gauss–Legendre quadrature; hence, a model with a Gaussian mixture structure was obtained. This model was used to develop filtering and smoothing algorithms. The benefits of this proposal, in terms of accuracy of the estimation and computational cost, are illustrated via numerical simulations.

IMPLEMENTATION OF LEBESGUE SAMPLING METHOD AND DIGITAL SENSORS FOR CONTROLLING THE LEVEL VARIABLE IN A CONTINUOUS SYSTEM

This study aims to show that the continuous control from a level system can be efficiently measured and controlled using capacitive digital binary sensors, which in this case, replace the measurement signal from an analog differential pressure transmitter in a level control system. The binary sensors low cost and the digital output they process allow the reproduction of a correct signal and the estimation of a variable for controlling the water level inside the process tank through a proportional pneumatic level control valve, which receives the control signal from the Lebesgue sampling estimation algorithm applied herein for processing digital measurements. In this particular case, the Lebesgue algorithm is applied to reproduce the estimation of values obtained from the continuous signal in the real level process for the measurement and control. Also, are compared both, simulated and real outputs obtained using the Lebesgue algorithm and digital sensors, which were applied to a state observer controller that relates digital signals for controlling the real level system output. The application of the Lebesgue algorithm in the real level process concludes that the analog level signal can be efficiently reproduced using this method. In addition, the controller enables the system to smoothly conduct digital output processing using digital sensors to control the system output correctly, validating that not only analog sensors should be applied for controlling the output of proportional actuators, because it is shown that digital binary signals can be used for controlling and emulating continuous signals, which were processed and applied to the pneumatic valve. Keywords: Lebesgue sampling, estimation, binary sensor, observer controller, finite state machine, continuous system, control, LTI systems, identification, state variable, estimated output, proportional actuator