This paper presents a robust adaptive control scheme for a class of continuous-time linear systems with unknown non-smooth asymmetrical deadzone nonlinearity at the input of the plant. The methodology is applied to handle input deadzone as well as unmeasurable disturbances simultaneously in strictly matched systems. The proposed controller robustly cancels any residual distortion caused by the inaccurate deadzone cancellation scheme. The scheme is shown to successfully cancel the deadzone’s deleterious effect as well as eliminate other unmeasurable disturbances within the span of the input. The new controller ensures the global stability of all states and adaptations, and achieves asymptotic tracking. The asymptotic stability of the closed-loop system is proven by Lyapunov arguments, and simulation results confirm the efficacy of the control methodology.

Loss of Control (LOC) is the primary factor responsible for the majority of fatal air accidents during past decade. LOC is characterized by the pilot’s inability to control the aircraft and is typically associated with unpredictable behavior, potentially leading to loss of the aircraft and life. In this work, the minimum time dynamic optimization problem to LOC is treated using Pontryagin’s Maximum Principle (PMP). The resulting two point boundary value problem is solved using stochastic shooting point methods via a differential evolution scheme (DE). The minimum time until LOC metric is computed for corresponding spatial control limits. Simulations are performed using a linearized longitudinal aircraft model to illustrate the concept.

As a result of sudden failure in the Programmable Logic Control (PLC) controlled process, the need of diagnosis arises. Diagnosis problem plays an important role to monitor failures in PLC, used to control the whole process. Nowadays and due to the lack of the needed tools availability to perform this action automatically, it is accomplished manually. Usually, the time consuming method is used by back-tracking the failure on an actuator due to the corresponding sensors. This paper analyzes the software quality metrics and their application on the PLC programs. Aiming to implement metrics that gives predictive information about diagnosability of an Instruction List (IL) PLC programs, this could minimize the needed effort to check the program in case of mistakes. Furthermore, to get a better prediction about diagnosability, new metrics are introduced which are able to give more information about the semantics of a program. But they are not yet fully developed and have to be analyzed.

SCADA (Supervisory Control and Data Acquisition) is concerned with gathering process information from industrial control processes found in utilities such as power grids, water networks, transportation, manufacturing, etc., to provide the human operators with the required real-time access to industrial processes to be monitored and controlled either locally (on-site)or remotely (i.e., through Internet). Conventional solutions such as custom SCADA packages, custom communication protocols, and centralized architectures are no longer appropriate for engineering this type of systems because of their highly distribution and their uncertain continuously changing working environments. Multi-agent systems (MAS) appeared as a new architectural style for engineering complex and highly dynamic applications such as SCADA systems. In this paper, we propose an approach for simply developing flexible and interoperable SCADA systems based on the integration of MAS and OPC process protocol. The proposed SCADA system has the following advantages: 1) simple (easier to be implemented); 2) flexible (able to adapt to its environment dynamic changes); and 3) interoperable (relative to the underlying control systems, which belongs to diverse of vendors). The applicability of the proposed approach is demonstrated by a real case study example carried out in a paper mill.

Machines have served the humanity starting from a simple ceiling fan to higher industrial applications such as lathe drives and conveyor belts. This research work aims at providing an appropriate software based control system because it provides computer featured applications, prevents rapid signal loss, reduces noise while also significantly improves the steady state and dynamic response of the motor. In this research paper, we have worked on DC motors due to its significant advantages over other types of machine drives. We have first individually studied Fuzzy and ANFIS (Adaptive Neuro-Fuzzy Interference System) controller in controlling speed for a separately excited DC motor. Afterwards, we have analyzed both results to conclude that which technique is better to be adopted for precisely controlling the speed of DC motor. Outcomes from MATLAB fuzzy logic toolbox for simulation of our schematic has been provided in this research work. Our study parameters include input voltage of DC motor, its speed, percentage overshoot and rising time of the output signal. Our proposed research has interpreted the outcomes that ANFIS controller is better than Fuzzy controller because it produces less percentage overshoot and causes less distortion of the output signal as the overshoot percentage of ANFIS controller is 8.2% while that of Fuzzy controller is 14.4%.

Motors are normally used for industrial control, automation and home electrical appliance. It spans everything from residential washing machines, fans, hand-held power tools, automotive window lift, traction control system, industrial drives and many more. Motor application is not completed without a control system. The inventions of microprocessor and microcontroller make the control system become easier. This control system is basically controlling the switch, speed, and direction of motor. Control signal is generated by a switch that is connected directly to the control circuit. In order to control and monitor the motor, user need to be at the place where the switch is located. In this system, mobile phone is used as a control switch. By sending text message using short message service (SMS) which is a part of the Global System for Mobile Communications (GSM), control signal is sent wirelessly to the control circuit. By implementing GSM module on the control circuit of motor, it can enable the user to send text message that contain command from any mobile phone to that GSM module. The GSM module will receive the text command and send it to the microcontroller to be processed and converted into desired control signal. Controlling motor using SMS is really convenient and give mobility as the user is able to control and monitor the motor from anywhere as long as the places have coverage. Moreover, sending text message is considered very low cost and most of people have their own mobile phones and it already becomes one of the basic needs in life.

In this paper, we consider cooperative hyperbolic systems involving Schr?dinger operator defined on Rn. First we prove the existence and uniqueness of the state for these systems. Then we find the necessary and sufficient conditions of optimal control for such systems of the boundary type. We also find the necessary and sufficient conditions of optimal control for same systems when the observation is on the boundary.

A feasibility assay is conducted for electromyography measure in sternocleidomastoid and platysma, tenting to use it on Brain-Computer Interface (BCI) feedback. It is proposed a case of study for four healthy subjects with an average of 35 years old, two females and two males. Methodology proposed includes signal acquisition and processing with feature extraction of RMS, Mean and Variance. The data are acquired with the AD board NI USB-6009, interfaced with LabView and processed in MatLab. An uncertainty analysis was made obtaining a system uncertainty of ±2.31 mV. ANOVA analysis was done, with a Randomized Complete Block Design (RCBD) experiment and interaction of factors and residues obtained with the software Minitab.

This paper presents an application of the simulation of discrete events (SED) using ARENATM in the management of large-scale breeding farms. The main objective of the simulation model is to find a policy of replacement, to ensure the best economic performance of a farm. The only variant analyzed of replacement policy was the number of cycles set in permanency for a sow in the herd. Considered incomes come from the sale of piglets and unproductive sows, and costs are due to the feeding of animals, replacement sows purchases, and the operation expenses of the farm. For this analysis, the production process was divided into three major stages called: mating, pregnancy or gestation and lactation. The sow’s movement from one stage to other was modeled by cycle-dependent transition probabilities. Considering the daily utility, as response variable, the model shows the best number of cycles to maintain the sows.

A feedforward controller for the automatic regulation of chemical composition of molten steel in the tundish of a continuous casting machine is proposed in this work. The flow of molten steel inside the tundish is modeled as a distributed parameter system, and the resulting partial differential equation is transformed into a set of ordinary differential equations by means of the finite differences technique. From the above set and using a proper boundary condition, a feedforward control law is synthesized. No experimental tests are reported, however, the dynamic performance of the controller is illustrated by means of numerical simulations.