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In this paper the issue of constraining the control input and the state variables in continuous-time systems via sliding mode control was considered. The sliding mode controller was designed using the reaching law technique. Further, the time-varying convergence rate was selected so that the fastest, finite-time, monotonic convergence of the state to the predefined sliding hyperplane simultaneously satisfying both control input and state limitations is ensured. Sufficient condition that guarantees these properties was presented and proved.

Pseudo random sequences are used in testing a logical circuit which can be generated from Linear Feedback Shift Register (LFSR). The proposed pattern generator can work both as an external and internal LFSR depending on the control signal. A number of patterns can be generated by using the proposed design which can be used in logical circuit testing. Primitive polynomials with degrees ranging from 3 to 11 are implemented using the proposed design. The implemented design is synthesized in Vivado on Zynq-7000 and the analysis is done on parameters timing, power and utilization. The proposed design is compared with the previously implemented design which uses XNOR gate and without reseeding. The proposed design improves the quality of patterns generated as well as the structure of pattern generator which was previously implemented [11].

Flexibility, more specially, in terms of modelling of components, is a priority for new-structured power systems with renewable energy resources (RESs). To fill the research gap in modelling of flexible loads (FLs), a new approach for modeling and identification of FLs based on the state-space paradigm is discussed in this paper. A power system integrated with wind units, as the most prevalent RES, is considered. The load is represented as a dynamic model which adopts an external control signal to change its consumption. The parameters of the proposed FL model are approximated using the optimal least-squares algorithm (OLSA). The fastness of the algorithm and its performance in an approximation of FL parameters are adorable. Simulations indicate the appropriateness of the proposed FL modeling approach in power systems with RESs.

In this article is proposed a direct torque control of induction motor with additional control signal from adaptive controller. It‘s signal is summed with the those from the conventional PI regulator and the result is the reference torque signal. Using the created mathematical model, the modes of operation of an induction electric drive with adaptive control under various disturbing influences are investigated.

A Linear Feedback Shift Register (LFSR) is used to generate Pseudo random sequences of bits which can be used in testing a logical circuit. In this work a Test Pattern Generator is implemented which can work as internal LFSR and external LFSR based on the control signal. This module is implemented for different Primitive polynomials from 3bits to 11 bits in Vivado using Zynq-7000 and parameters like utilization, power, and timing are analyzed. The main objective of this work is to increase the length of the Pseudorandom sequences generated by a Test Pattern generator by combining internal and external LFSR using a control signal in a single module. So that, the long test patterns can be generated by using lower bit LFSR.

The article discusses a method for dealing with concentrated acoustic interference in telecommunication audio exchange systems. The study and development of algorithms for processing speech signals that increase the efficiency of information-control telecommunication systems of audio exchange under the influence of external concentrated acoustic noise of high intensity are carried out in the work. A telecommunications system for transmitting speech information is considered, an algorithm for calculating the signal-to-interference ratio is proposed, the influence of noise interference on the perception of signals received at the output of a telecommunication system is estimated. An adaptive algorithm for generating a control signal is proposed, which makes it possible to turn off channels affected by concentrated interference, the efficiency of the proposed algorithm and the dependence of possible losses of a useful signal on the choice of a rejection band are estimated.

This paper proposes a robust Fuzzy PI to detect the changing of load and provide an appropriate control signal to stabilize the motor speed. First, the mathematical model of Permanent magnet synchronous motor (PMSM) and the structure of the Mamdani fuzzy controller were proved. Secondly, this controller will be combined with PI controller to adjust K p , K i when the load changing. Finally, the speed response and overshoot will be discussed and compared with the PI method.

We analyze the wavelength drifting of a Mach-Zehnder Interferometer coupler assisted reflective-type microring resonator (RT-MRR) based on the transmission matrix formalism. An experiment is carried out to validate our analysis. The results show that the resonant wavelength of the RT-MRR periodically drifts as a function of the control signal, which helps us to understand the wavelength drifting mechanism and to find solutions to avoid the wavelength drifting effect.

When a quadrotor UAV is interfered so much that it may deviate from the equilibrium state greatly. Due to the limitation of the output rate of the actuator, its output control signal is always less than the control signal needed to adjust the attitude of the aircraft, which may cause the quadrotor UAV to lose control. This paper focuses on the characteristics of yaw dynamics of the six DOF underactuated quadrotor UAV, studies the quantitative matching relationship between the design of the control loop, the motor rate limiter and the maximum angular velocity interference of the quadrotor UAV, through the analysis of without the actuator and with the actuator respectively. The maximum angular velocity disturbance and the maximum attitude angular acceleration disturbance are obtained. Finally, the great anti-interference capability of the quadrotor UAV controlled by the classical PD control method is verified by simulation. The simulation results show that the conclusion of this paper is correct. It provides a reference for engineering application.

The main goal of existing scan chain diagnosis approaches is to identify a point (or range of points) in the scan chain(s) at which values are directly corrupted due to a defect. A common assumption made in these techniques is the defect causing failure is in the scan chain/path itself. Based on the real silicon failure analysis over years, this assumption is often found to be correct, but not always. Specifically, in cases where a single defect is expected (stress fails and field returns), yet multiple chains fail, this assumption is more often incorrect. In these cases, the defect was found to be in the clock and control signal logic. This paper proposes an improved approach to diagnose defects on clock and control signal lines to enhance accuracy of scan chain diagnosis. Experimental results on injected clock and control signal defects demonstrate the effectiveness of the proposed technique. Physical Failure Analysis (PFA) on selected silicon devices confirmed the results of proposed technique.

A novel radio tracking system is proposed by a two-element time modulated array (TMA). By estimating the spectrum of incident signal after time modulation, the system produces control signal and rotates the platform to tracking the source. The signal processing of the proposed method relies on two-point discrete Fourier transform (DFT). Its system complexity is low since only one RF channel is required. Simulation is conducted to verify its effectiveness.

Conveyor is one of the important mining equipment in the coal mine and the belt is the key component of the conveyor. Once the belt is torn longitudinally, if the measures are not taken in time, the entire conveyor belt will be torn completely, which will cause serious economic losses. To solve this problem, this paper studies a method to detect longitudinal rip of coal conveyor belt by applying MATLAB and knowledge of image processing. By extracting the longitudinal rip part of the image, combining with edge detection, then calculating the area of the longitudinal rip part with a new algorithm, at last comparing this area with the minimum area of the longitudinal rip set by system, it can be judged whether the belt has been longitudinally torn. So control signal can be provided to the control equipment to prevent the conveyor belt from continuing to be torn.

This paper studies distributed adaptive architectures for controlling uncertain multiagent systems with unmeasurable coupled dynamics. Specifically, we first analyze a standard distributed adaptive control method with system uncertainties and coupled dynamics in a leader-follower setting, where we present local stability conditions. We second propose an additional feedback term within the control signal of each agent in order to relax the aforementioned local stability conditions. An illustrative numerical example is then given in order to demonstrate our contributions.

Brushless DC Motor (BLDCM) is broadly utilized for some mechanical applications, given their high efficiency, high torque, and low volume. It is very hard to tune the parameters and accomplish full force highlights utilizing a basic custom PID controller. An adaptive PID controls can meet the highlights and are anything but difficult to enrol. The list items test that any adaptive PID controller has favoured both the PI controller and the customary Tahitian PID controller. This paper applies an Adaptive PID controller dependent on the extra blunder of a turn around control sign to comprehend non-linearity, parameter varieties, and burden travel issues that happen in the BLDC motor drive framework. The test results are exhibited to demonstrate that Adaptive PID controllers dependent on the extra mistake of the reverse control signal are fit for the following movement, just as diminishing the impact of parameter changes. The proposed adaptive PID controller model has done by MATLAB/SIMULINK.

Guarding buildings and residents against calamities caused by vibrations is very crucial. Active vibration control devices combined with control systems have shown fruitful results. The study was an effort to tackle the issue of complexity and improving robustness in previous control methods proposed by scholars. The modified PID controller combined active force control method was able to reduce the vibration of both levels of the building structure investigated by 99.99% and also the amount of control signal required was reduced to the minimum. The method maintains the advantages of the PID controller most especially simplicity as well as robustness of the active force control scheme. Hence, it might make a breakthrough in active vibration control in buildings as well as other similar structures, although further investigations may be required. The study is novel in the sense currently no such technique was proposed for eradication of vibration disturbances in buildings.

This study focuses on an analysis of circuit solutions for biological signals recording unit in prostheses. Creation of prostheses using the biological signal as the control signal is an important problem in the field of medical technologies. Electromyographic signal is the popular biological signal in prosthesis control. In this study three options for the electromyographic signal recording unit were considered: the unit based on an instrumentation amplifier, the circuit with the addition of an “active ground” and the circuit with the addition of filtration of polarization voltage of the electrodes. Based on these options, three installations were invented. Using these installations electromyographic signals from triceps of test subjects were recorded and processed. Signal-to-noise ratios of signals were calculated and compared using the statistical methods. Quality of recorded biological signals depends on many factors including circuit solution of recording unit. Based on the results obtained, the optimal circuit solution was chosen for recording the electromyographic signals for prostheses control. The optimal was called circuit with the highest signal-to-noise ratio and acceptable dimensions. It was discovered that circuit with the addition of active ground” part is the most appropriate for recording of biological signals which are used as prostheses control signals. The results of the study can be used in the development of prosthesis control unit and other medical applications which are used to record biological signals.

The article deals with the problem of modeling and calculating processes in a linear system with a delay based on dynamic graphs. A graph model of a continuous lagging signal (initial function) is constructed. A graph model of a linear stationary system with a delay in the feedback chain is constructed as a union of graph models of its elements. The graph model makes it obvious that a system with a delay in the feedback circuit is open relative to the signals flowing in it, which makes it possible to significantly simplify computational procedures. A linear system with a delayed control signal is also considered. Based on graph models the authors obtain the recurrent relations and an algorithm for calculating processes in a linear system with a delay in state and a delay in control. The paper presents an example of using the obtained algorithm. The proposed method allows for a clear and strict formalization of the description and analysis of complex systems, including nonlinear discrete systems with different types of modulation

Drones or unmanned aerial vehicles are having an increased popularity in all fields of applications such as transportation, traffic monitoring, military surveillance etc. However, this technology can be used for destruction when it fall in the hands of criminal, who are using it for terrorist or unauthorized activities. There is a rising demand for anti-drone systems, which can detect and block their activities in order to make full use of the great advantages provided by this technology. The project aims to provide a systematic design of a drone detection mechanism using the RF control signal exchanged between the drone and its remote controller. The system generates a high-power jamming signal transmitted over the same carrier frequency and band of the detected drone and directed towards the drone location in order to disconnect it from its controller causing it to land safely or trigger a mechanism to return it to home. This system is designed to work only at 2.4 GHz band.

International audience; In this paper, we study the problem of stabilizing a linear ordinary differential equation through a system of an n + m (hetero-directional) coupled hyperbolic equations in the actuating path. The method relies on the use of a backstepping transform to construct a first feedback to tackle in-domain couplings present in the PDE system and then on a predictive tracking controller used to stabilize the ODE. The proposed control law is robust with respect to small delays in the control signal.

An acrobot is a nonlinear and underactuated system with two degrees of freedom. The control of its swing-up motion using only the actuated joint at the elbow of the system is a challenging problem that has been tackled using different optimal control approaches. This paper uses the Discrete Mechanics and Optimal Control (DMOC) method to solve the problem, allowing the system to start from its position pointing down and end at the unstable upward position. The formulation of the trajectory optimization problem for the acrobot is presented, followed by the full solution, including all the mathematical details. The results compare the obtained solution with a more classical one, showing the effectiveness of the DMOC approach on the control signal.

Fractional- $N$ frequency synthesizers are notorious for exhibiting spurious tones (spurs). Spurs can be introduced inadvertently by the divider controller or may result from interaction between a spur-free divider control signal and nonlinearities in the loop. This paper discusses the underlying problem, a variety of deterministic mechanisms that produce spurs, and techniques for mitigating and/or eliminating them.

In this paper a high efficiency power amplifier is presented with quasi VSWR immunity. It is based on a new, high efficiency architecture, the Load Modulated Balanced Amplifier. By using a balanced amplifier to generate the control signal, the overall circuit showed very high VSWR tolerance compared to classic designs. The circuit is currently under development in a single chip RFIC in CMOS and IPD technology.

In this paper an adaptive neural network controller is used to solve the problem of tracking trajectories of a delta parallel robot (DPR) with three degrees of freedom. This controller used an adaptive artificial B-Spline neural network (BSNN) for online training. The BSNN improves the performance of DPR on a closed loop and update the parameters of control scheme online. This algorithm sets the control signal without using a detailed mathematical model nor exact values of the parameters of the DPR. The proposed adaptive controller was compared with a traditional control based a PD +G contoller. Analytical and numerical results prove the robust and efficient performance of the adaptive neural network controller.

In this paper, optimal fractional and integer order PID controllers are compared on a stabilized Ball Balancing Table system. The real-time system is restricted on Y-axis and stabilized by using PV controller. Firstly, fractional and integer order system models are obtained from stabilized real-time system. Then, Big Bang-Big Crunch optimization algorithm is used to design optimal fractional and integer order PID controller with ISE performance index as a cost function. In order to avoid from system aggressiveness and high control signal values, maximum sensitivity constraint is utilized. Finally, the performance of the control systems are analyzed via simulations and real-time system applications.

This paper presents a fault-tolerant ship roll motion control using the control allocation approach (CA) in the presence of actuator faults. An control allocation method is applied based on the optimized l ∞ norm of the control signal. The practical actuator constraints are also considered. An active fin is used that is commanded by a PID controller. The active fin actuator is most effective at high speed. Simulation results are used to show the effectiveness of the proposed method.

This paper describes the research results of development of noise-immunity memory cell containing a trigger, a delay element, a coincidence element, a gamma sensor, and an electronic key. In the case of upset initiated by gamma radiation, a control signal is generated to transfers the trigger to its initial state. The transition process simulation made it possible to refine the parameters of elements and their connection diagram. The prototype of the upgraded trigger memory cell (TMC) was developed and experimentally confirmed the restoration of the initial state of the trigger cell in case of upset under the radiation.

Paper discusses a problem of the CMOS self-timed circuits' indication. Large number of indicating signals in the multi-bit computational devices and registers requires an additional hardware and time for their combining and forming a single control signal that provides a request-acknowledge interaction between interconnected self-timed functional blocks. Indication subcircuit performs this. Multi-input hysteretic triggers allows for accelerating indication subcircuit by factor of 1.1 − 1.6 and reducing its complexity in several times in comparison to standard implementation basis on static and semi-static Muller's elements. A penalty for this is some short-circuit current in the worst case.

One way to realize zero-speed sensorless control of ac machines is to establish voltage step excitations, whose current responses deliver information about machine saliencies, finally leading to the flux position required for the control. The use of only one active inverter state for saliency-offset vector calculation results in low current ripple. However, signal offsets appear in the vector, whose magnitude can be significantly bigger than the saliency information, especially in induction machines, where the slotting signal is often used as control signal. Besides, offsets are dependent on saturation level and in addition vary in angle and magnitude, depending on the active inverter state used. Consequently, offset estimation must be performed online and as frequent and accurate as possible to precisely extract saliency information. This paper proposes a novel identification method that estimates offset magnitudes and angles under one active inverter state excitations that modulate the fundamental wave voltage. Measurements performed on a traction induction machine prove the method accuracy.

Freeway congestion has become a serious problem for city manager due to the continuous growth of traffic demand. Different kinds of traffic control management measures, such as variable speed limits and ramp metering, have been proposed and partly implemented to handle this problem. Mobility, safety and emission are used as the control objectives. This paper investigates multi-objective optimization with the coordinated control of variable speed limits and ramp metering. Moreover, model predictive control is used as the control framework in a rolling horizon system. Furthermore, multi-objective particle swarm optimal algorithm is adopted to acquire the best control signal for mobility, safety and emission performance. The proposed method is evaluated through simulation and calibrated using the real-world data at a freeway stretch. The experiment result indicates that the mobility of the study network was improved, and the collision risk and carbon emission are reduced by the integration of variable speed limits and ramp metering.

Facing the unmanned vehicle steering system with nonlinearity and uncertainties, model-based control methods could not acquire satisfied performance. In this paper, a novel adaptive high-order sliding mode (HOSM) control algorithm is proposed for the steer-by-wire (SBW) system of unmanned vehicle. There are three original contributions. Firstly, without the priori knowledge of the unmodeled dynamics and external disturbances bounds, the proposed adaptive HOSM controller ensures a real sliding mode established in finite time and a continuous control input signal to the steering motor. Secondly, the developed adaption schemes of switching effectively avoids overestimation, which significantly suppresses the formidable chattering caused by high frequency switching of the control signal. Finally, the effectiveness and superiority of the adaptive HOSM controller are indicated by numerical simulations.

This paper considers the application of Particle Swarm Optimization (PSO) to decentralized control of a Control Moment Gyroscope (CMG). The PSO is used to obtain optimized gains for a decentralized PID controller. A cost function with ITAE index combined with the control signal variance is proposed for the system. A simple velocity feedback is proposed for damping resonant poles prior to the decentralized control. Simulation and practical results are presented in order to validate the methodology.

The article considers a single-loop MIMO system with a linear T-periodic continuous process and a digital controller with a sampling time T in the presence of a control signal delay. The necessary and sufficient conditions for the modal controllability are given. The problem of stabilization in the absence of controllability is taken into account.

This paper proposes a hybrid aperiodic sampled-data control strategy for the stability of interconnected nonlinear systems. These interconnected nonlinear systems are modelled using Takagi-Sugeno fuzzy modelling technique. In the proposed methodology, first a self-triggering strategy is developed for computing the next sampling instant for each node in a distributed networked control system. Further, an event-triggering condition is checked at these sampling instants and the control signal for each system is updated only if the event-triggering condition is satisfied. This reduces the number of sampling instants and number of times the control law is computed as compared to time-triggered mechanism and the aperiodic sampled-data strategy when applied alone. The results presented in this paper are validated through simulations and a comparison with other triggering mechanisms is also shown.

Cross coupling between multiple receivers can lead to significant impacts on the characteristics of multi-receiver wireless power transfer (WPT) systems. To improve the power transfer capability, performance and reliability of such systems, mathematical models needs to be derived and employed for parameters design. This paper builds a small-signal model that describes how a typical multi-receiver WPT system reacts on a perturbation in its reference control signal using the methods of generalized state space averaging (GSSA) and extended description function (EDF). The small-signal model is verified by simulation results of PSIM software and proves to be accurate. Using the derived model, the dynamics of the system is analyzed and then its parameters are designed and optimized.

This paper introduces the application of predictor-based control with constraints of human response to a dynamic virtual 3D face. We are using changing distance-between-eyes in a woman 3D face as a stimulus - control signal. Human response to the stimulus is observed using EEG-based excitement signal - output signal. The technique of dynamic systems identification which ensures stability and possible higher gain of the model for building a predictive input-output model of control plant is applied. Two predictor-based control schemes with a minimum variance or a generalized minimum variance control quality and constrained control signal magnitude and change rate are developed. High prediction accuracy and control quality are demonstrated by modelling results.

The rapid uptake of renewable energy sources (RES) and displacement of synchronous generators is introducing a number of security challenges, particularly in terms of frequency and voltage stability, whose interactions in RES-dominated systems are to be fully understood yet. This paper models and discusses the application of utility-connected battery energy storage system (BESS) for provision of integrated dynamic services, i.e., simultaneous provision of primary frequency/active power and voltage/reactive power control. To investigate how BESS should respond to system contingencies, a detailed BESS dynamic model is presented along with comprehensive discussions on interaction of frequency and voltage responses and proposing suitable control signal generation algorithms. Simulation results illustrate the BESS capability to provide integrated dynamic services as proposed, highlighting the significance of response prioritization.

In this paper, we proposed a new single-electron (SE) circuit that can learn after being fabricated. We designed it whose result changes with the number of signals arriving at the output. To design it, we designed an SE flip flop circuit and an SE switch circuit to control signal propagation. The circuit can be used as a learning circuit. We performed character recognition as operation test of the proposed circuit. The results show that our SE neural network using a learning circuit can simultaneously learn multiple types of input patterns.

This paper deals with the decentralized force control problem of compliant robots driven by Series Elastic Actuators (SEAs). The decentralized force control problem of a compliant robot manipulator is transformed into the robust position control problem of a servo system by using Hooke's law and lumping the nonlinear dynamics and unknown disturbances of the robot manipulator into a fictitious disturbance variable. In order to precisely follow the reference force trajectories at joint space, i.e., the position trajectories of the servo systems, the robust controller is synthesized by using Disturbance Observer (DOb) and Sliding Mode Control (SMC). Although the robust force controller can be synthesized by using only SMC, the force control signal may suffer from high control signal chattering as the force reference input is increased. In addition to improving the robustness of force control, DOb significantly suppresses the discontinuous control signal chattering by allowing to decrease the SMC gain. When the proposed decentralized robust force controller is implemented, the compliant robot can precisely track desired force trajectories and safely contact to different environments. The validity of the proposed force controller is verified by giving the simulation results of a redundant robot manipulator.

This paper presents a control technique for reverse parking car-like vehicles based on deep reinforcement learning and preview control. The deep deterministic policy gradient (DDPG) algorithm is used for training a neurocontroller using a reward function defined in terms of the desired final state of the system. A preview control approach is employed to leverage knowledge of a known a priori reference input to generate a predictive control signal coupled into the neurocontroller output. Simulation results are presented to validate the proposed method. Moreover, these results show that incorporating a preview control signal improves the parking time.

In classical boundary layer (First-order) SMC strategy, the tracking performance and robustness affected when this controller is designed to reduce chattering phenomenon. To improve this tracking performance higher order SMC strategies are preferred. In this paper, higher order smc algorithms are applied to regulate the armature control dc motor. These higher order sliding modes reduces the chattering without affecting tracking accuracy and robustness and also insensitive to disturbance. This higher-order SMC controller smoothens the control signal. This paper examine two different control algorithms related to second-order SMC, these are twisting and super twisting. The effectiveness of these control algorithms in regulating the speed and angular position of the DC motor is verified in simulation in MATLAB environment. The speed characteristics of DC motor under different initial conditions are shown in simulation using twisting and super twisting higher order SMC strategy.

In order to reduce the adverse effects of the arterial intersections signal control strategy dynamic changes during arterial coordination control signal transition. This paper analyzes the fluctuation characteristics during the transition of control signals. The phase offset variation volatility model, signal cycle fluctuation volatility model, green ratio volatility model are constructed, and the volatility model analysis is conducted on the two aspects of the multi-period transition and multi-intersection coordination cycle transitions. The particle swarm optimization algorithm was used to solve the multi-objective optimization problem in the arterial coordination transition, and the best transition control strategy was finally obtained. The simulation results show that the proposed algorithm is optimized compared with the traditional Add algorithm and the Subtract algorithm in terms of vehicle average delay, vehicle average stop times, and average queue length, which can make the signal control effect better.

In response to bird damage, this paper uses dynamic video target detection technology to develop a set of intelligent detection devices for high-voltage transmission lines. Firstly, the optimized motion history map (MHI) is used to extract the foreground information of the moving target, and then the detection algorithm is transplanted into the embedded chip Hi3531, and the control signal is sent to the windows working platform while the display screen detects the bird. Through the analysis of the experimental results of different acquisition videos, it is concluded that the bird damage can be detected and the monitoring results can be displayed in time while the bird occurs.

Improving the velocity control of servodrives is an important topic in industrial applications, especially in the presence of internal and external disturbances. To address this problem, in this work the feedback loop of a perturbed servodrive is augmented with a Disturbance Observer (DOB). The DOB uses the control signal, velocity measurements and a nominal model of the plant to estimate the disturbance. The disturbance estimate is then used to compensate for the effects of the real disturbance. Then an equivalence between the P+dob and a set point weighted Proportional-Integral controller is established. Experiments with a laboratory prototype show the effectiveness of the proposed scheme.

Increased penetration of electric vehicles (EVs) can lead to uncoordinated charging which can result in electrical distribution network overloads and possibly outages as well as increased peak demands. This can particularly occur in power systems with minimal and insufficient demand side management schemes where there is no time of use (TOU) tariffs. Such is usually characteristic of small Caribbean island power systems and their numerous distinctive policy, technical and infrastructural challenges. This manuscript documents a unique approach for EV charging (AC level 1 and 2) in Trinidad and Tobago with application to other developing countries. A prototype device is designed and developed for connection to the EV that allows remote (IEEE 802.11 Standard) modification by the electrical utility of the pilot control signal of the J1772 charger.