Generate Control Signals Research Articles

A VLSI Implementation of Four-Phase Lift Controller Using Verilog HDL

With the advent of an era of staggering range of new technologies to provide ease of mobility and transportation elevators have become an essential component of all high rise buildings. An elevator is a type of vertical transportation that moves people between the floors of a high rise building. A four-Phase lift controller modeled on Verilog HDL code using Finite State Machine (FSM) has been presented in this paper. Verilog HDL helps in automated analysis and simulation of lift controller circuit. This design is based on synchronous input that operates on a fixed frequency. The Lift motion is controlled by means of accepting the destination floor level as input and generate control signal as output. In the proposed design a Verilog RTL code is developed and verified. Project Navigator of XILINX has been used as a code writing platform and results were simulated using Modelsim 5.4a simulator. This paper discusses the overall evolution of design and also discusses simulated results.

Real-Time Charging Strategies for an Electric Vehicle Aggregator to Provide Ancillary Services

Real-time charging strategies, in the context of vehicle to grid technology, are needed to enable the use of electric vehicle fleets batteries to provide ancillary services. In this paper, we develop tools to manage charging and discharging in a fleet to track an automatic generation control signal when aggregated. We propose a real-time controller that considers bidirectional charging efficiency and extend it to study the effect of looking ahead when implementing model predictive control. Simulations show that the controller improves tracking error as compared with benchmark scheduling algorithms, as well as regulation capacity and battery cycling.

Control of Energy Storage

In the attempt to tackle the issue of climate change, governments across the world have agreed to set global carbon reduction targets. [...]

Switched Control Strategies of Aggregated Commercial HVAC Systems for Demand Response in Smart Grids

This work proposes three switched control strategies for aggregated heating, ventilation, and air conditioning (HVAC) systems in commercial buildings to track the automatic generation control (AGC) signal in smart grid. The existing control strategies include the direct load control strategy and the setpoint regulation strategy. The direct load control strategy cannot track the AGC signal when the state of charge (SOC) of the aggregated thermostatically controlled loads (TCLs) exceeds their regulation capacity, while the setpoint regulation strategy provides flexible regulation capacity, but causes larger tracking errors. To improve the tracking performance, we took the advantages of the two control modes and developed three switched control strategies. The control strategies switch between the direct load control mode and the setpoint regulation mode according to different switching indices. Specifically, we design a discrete-time controller and optimize the controller parameter for the setpoint regulation strategy using the Fibonacci optimization algorithm, enabling us to propose two switched control strategies across multiple time steps. Furthermore, we extend the switched control strategies by introducing a two-stage regulation in a single time step. Simulation results demonstrate that the proposed switched control strategies can reduce the tracking errors for frequency regulation.

Regulation of the Functional State of the Human Brain by Real-Time Frequency−Phase Synchronization of Sensory Stimuli with the EEG Rhythm

A method providing real-time digital EEG filtration in selected leads and assessment of the instantaneous amplitude and phase of the background rhythm to generate control signals for the presentation of sensory stimuli at specified phases of the dominant biorhythm is presented. Examples of phase-dependent rearrangements in EEG characteristics in humans detected using this method are given.

Rendimiento de Enfoques de Control Auto-Disparado


 
 
 El control auto-disparado produce secuencias de muestreo no periódico que varían dependiendo de factores de diseño relacionados con la estabilidad y el rendimiento del sistema a ser controlado. Dentro de este marco, recientemente han sido desarrollados dos enfoques dirigidos a minimizar un costo cuadrático, considerando un rendimiento óptimo y persiguiendo el mismo objetivo de control; cada una de ellos sigue una regla de muestreo diferente. Un enfoque se basa en mantener el valor de control actual tanto tiempo como sea posible, mientras que un umbral de rendimiento óptimo no se traspase. El otro enfoque se basa en la generación de una señal de control a trozos que se aproxima a una señal de control óptima continua, sujeta a determinadas limitaciones. Este artículo presenta un estudio comparativo entre los dos enfoques, proporcionando una percepción útil para la realización de futuras investigaciones. Como métricas de interés, el rendimiento de control y la utilización de recursos fueron considerados, y para evaluarlos, se hizo uso del intervalo de muestreo promedio y del costo normalizado. Se demostró que el diferente espacio de búsqueda de cada enfoque plantea un desafío para diseñar un marco de comparación equitativo, y que ambos enfoques superan al muestreo periódico. 
 
 

An Approach to Microcontroller-Based Realization of Boost Converter with Quasi-Sliding Mode Control

The paper considers a realization of quasi-sliding mode control for DC–DC boost-type converter on ATmega8 microcontroller. The proposed control law represents a combination of discrete-time sliding mode and generalized minimum variance control techniques. The control design is based on input–output converter model and only the sensed output voltage is used for generating control signal. This approach simplifies the practical realization of boost converter since there is no need for current sensors. By introducing an additional discrete-time integrator in control, the converter accuracy in steady-state under load and input voltage variations is enhanced. The experimental prototype is developed and several experiments are conducted to validate the functionalities of the proposed solution. The maximum load and line regulation errors of the proposed converter are 1.55% and 2.9%, respectively.

Development of control system for multi-converter High voltage Power supply using programmable SoC

Multi-converter based High Voltage Power Supplies (HVPSs) find application in multi-megawatt accelerators, RF systems. Control system for HVPS must be a combination of superior parallel processing, real time performance, fast computation and versatile connectivity. The hardware platform is expected to be robust, easily scalable for future developments with minimal overheads. This paper describes development of control system on Zynq All Programmable SoC (System on Chip) for HVPS. Typical HVPS control mechanism involves communication, generation of precise control signals/pulses for few hundred numbers of chopper and closed loop control in microsecond range for regulated output. Such kind of requirements can be met with Zynq All Programmable SoC, which is a combination of Dual core ARM Cortex A-9 Processing System (PS) and Xilinx 7 series FPGA based Programmable Logic (PL). Deterministic functions of power supply control system such as generation of control signals with precise inter-channel delay of nanosecond range and communication with individual chopper at 100kbps can be implemented on PL. PS should implement corrective tasks based on field feedback received from individual chopper, user interface and OS management that allows to take full advantage of system capabilities. PS and PL are connected with on-chip AXI-4 interface with low latency and higher bandwidth through 9 AXI ports. Typically PS boots first, this ensures secure booting and prevents external environment from tampering PL.

Brain–Machine Interface and Visual Compressive Sensing-Based Teleoperation Control of an Exoskeleton Robot

This paper presents a teleoperation control for an exoskeleton robotic system based on the brain-machine interface and vision feedback. Vision compressive sensing, brain-machine reference commands, and adaptive fuzzy controllers in joint-space have been effectively integrated to enable the robot performing manipulation tasks guided by human operator's mind. First, a visual-feedback link is implemented by a video captured by a camera, allowing him/her to visualize the manipulator's workspace and movements being executed. Then, the compressed images are used as feedback errors in a nonvector space for producing steady-state visual evoked potentials electroencephalography (EEG) signals, and it requires no prior information on features in contrast to the traditional visual servoing. The proposed EEG decoding algorithm generates control signals for the exoskeleton robot using features extracted from neural activity. Considering coupled dynamics and actuator input constraints during the robot manipulation, a local adaptive fuzzy controller has been designed to drive the exoskeleton tracking the intended trajectories in human operator's mind and to provide a convenient way of dynamics compensation with minimal knowledge of the dynamics parameters of the exoskeleton robot. Extensive experiment studies employing three subjects have been performed to verify the validity of the proposed method.

A self-tuning NeuroFuzzy feedback linearization-based damping control strategy for multiple HVDC links

This research work proposes a multi-input multi-output (MIMO) online adaptive feedback linearization NeuroFuzzy control (AFLNFC) scheme to improve the damping of low frequency oscillations (LFOs) in an AC/DC power system. Optimized NeuroFuzzy identification architecture online captures the oscillatory dynamics of the power system through wide area measurement system (WAMS)-based measured speed signals of machines. Based on the identified power system model, the appropriate control law is derived through feedback linearization control with a self-tuned coefficient vector. The generated control signal modulates the real power flow through a high voltage direct current (HVDC) link during perturbed operating conditions and enhances system stability. The effectiveness of the proposed control strategy is demonstrated through different contingency conditions of a multi-machine test power system with multiple HVDC links. The results validate the significance of the proposed control strategy to improve the capability of HVDC links to damp inter-area modes of LFOs. The proposed MIMO AFLNFC performance is bench-marked against conventional PID based supplementary control.

Experimental implementation of MIMO model predictive controller-based second order divided difference filter for nonlinear systems

In this paper, we propose an experimental implementation of a nonlinear predictive controller based on the second order divided difference filter (DDF2) which is a derivate-free estimator. The used state estimator avoids the determination of Jacobian matrices required with the extended Kalman filter (EKF) for an easy implementation with nonlinear systems. In addition, the second order Stirling's interpolation of the estimator allows a more accurate a priori state prediction. A constrained nonlinear predictive controller-based DDF2 is designed to control a multivariable three-tank system. In order to generate the control signals, the controller solves a nonlinear objective function. To overcome the offset output error that appeared due to the inaccuracy of the system model, an internal state model correction scheme is adopted at each iteration. Practical results show the reliability of the proposed method in state estimation, setpoint tracking, and smooth control signal generation. The proposed controller outperforms the model predictive control based on linear state space model derived from the linearisation of the system model around the same setpoint trajectory.

Water Hydraulic Servo Motor Velocity Control Using PID Funnel Control with Future Distance Estimation

Because of the environmental problems, water hydraulic system is introduced an alternative driving source for many applications. However, typical properties of water make the water hydraulic system difficult to be controlled; for example, the system contains parameters uncertainty and strong nonlinearity. This paper proposed the proportional-integral-derivative funnel control (PID-FC) with future distance estimation for the water hydraulic servo motor velocity control. The controller utilizes the evident merit of future distance estimation for control signal generation. This control strategy requires no system identification, and can ensure not only the transient response behavior but also the steady-state error of the system using predefined arbitrary funnel boundaries. The simulation results show that the proposed controller has high efficiency to control the velocity of the water hydraulic servo motor system. The proposed controller shows better control performance especially during the transient operation compared with the conventional PID-FC. Additionally, the controller is stable and robust for the case that dead-zone effects of servo valve are included.

Hybrid control of aggregated thermostatically controlled loads: step rule, parameter optimisation, parallel and cascade structures

This study proposes hybrid control strategies for aggregated thermostatically controlled loads (TCLs) in order to provide ancillary service. The on/off control strategy and the setpoint-regulation strategy are two typical control strategies. In order to reduce the tracking errors of the two control strategies, two improved methods were developed. The first method dispatches the aggregated loads to the automatic generation control signal following a step rule based on the state of charge. The second method optimises the controller parameters of the setpoint-regulation strategy by the Powell optimisation algorithm. Based on these two improved methods, the hybrid control strategies with parallel and cascade control structures were established by dividing the TCLs into two clusters, and the optimal allocations of the loads, the reference signal and the tracking error between the two clusters were obtained by the particle swarm optimisation algorithm. The simulation results demonstrate that the hybrid control strategies can reduce the errors in load following.

Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation

An energy storage system (ESS) in a power system facilitates tasks such as renewable integration, peak shaving, and the use of ancillary services. Among the various functions of an ESS, this study focused on frequency regulation (or secondary reserve). This paper presents an optimal scheduling algorithm for frequency regulation by an ESS. This algorithm determines the bidding capacity and base point of an ESS in each operational period to achieve the maximum profit within a stable state-of-charge (SOC) range. However, the charging/discharging efficiency of an ESS causes SOC errors whenever the ESS performs frequency regulation. With an increase in SOC errors, the ESS cannot respond to an automatic generation control (AGC) signal. This situation results in low ESS performance scores, and finally, the ESS is disqualified from performing frequency regulation. This paper also presents a real-time SOC management algorithm aimed at solving the SOC error problem in real-time operations. This algorithm compensates for SOC errors by changing the base point of the ESS. The optimal scheduling algorithm is implemented in MATLAB by using the particle swarm optimization (PSO) method. In addition, changes in the SOC when the ESS performs frequency regulation in a real-time operation are confirmed using the PSCAD/EMTDC tool. The simulation results show that the optimal scheduling algorithm manages the SOC more efficiently than a commonly employed planning method. In addition, the proposed real-time SOC management algorithm is confirmed to be capable of performing SOC recovery.

Model identification and vision-based H∞ position control of 6-DoF cable-driven parallel robots

ABSTRACTThis paper presents methodologies for the identification and control of 6-degrees of freedom (6-DoF) cable-driven parallel robots (CDPRs). First a two-step identification methodology is proposed to accurately estimate the kinematic parameters independently and prior to the dynamic parameters of a physics-based model of CDPRs. Second, an original control scheme is developed, including a vision-based position controller tuned with the H∞ methodology and a cable tension distribution algorithm. The position is controlled in the operational space, making use of the end-effector pose measured by a motion-tracking system. A four-block H∞ design scheme with adjusted weighting filters ensures good trajectory tracking and disturbance rejection properties for the CDPR system, which is a nonlinear-coupled MIMO system with constrained states. The tension management algorithm generates control signals that maintain the cables under feasible tensions. The paper makes an extensive review of the available methods and presents an extension of one of them. The presented methodologies are evaluated by simulations and experimentally on a redundant 6-DoF INCA 6D CDPR with eight cables, equipped with a motion-tracking system.

Automatic weight determination in nonlinear model predictive control of wind turbines using swarm optimization technique

This paper addresses the problem of automatic tuning of weighting coefficients for the nonlinear model predictive control (NMPC) of wind turbines. The choice of weighting coefficients in NMPC is critical due to their explicit impact on efficiency of the wind turbine control. Classically, these weights are selected based on intuitive understanding of the system dynamics and control objectives. The empirical methods, however, may not yield optimal solutions especially when the number of parameters to be tuned and the nonlinearity of the system increase. In this paper, the problem of determining weighting coefficients for the cost function of the NMPC controller is formulated as a two-level optimization process in which the upper- level PSO-based optimization computes the weighting coefficients for the lower-level NMPC controller which generates control signals for the wind turbine. The proposed method is implemented to tune the weighting coefficients of a NMPC controller which drives the NREL 5-MW wind turbine. The results are compared with similar simulations for a manually tuned NMPC controller. Comparison verify the improved performance of the controller for weights computed with the PSO-based technique.

NTM stabilization by alternating O-point EC current drive using a high-power diplexer

At the tokamak ASDEX Upgrade, experiments to stabilize neoclassical tearing modes (NTMs) by electron cyclotron (EC) heating and current drive in the O-points of the magnetic islands were performed. For the first time, injection into the O-points of the revolving islands was performed via a fast directional switch, which toggled the EC power between two launchers synchronously to the island rotation. The switching was performed by a resonant diplexer employing a sharp resonance in the transfer function, and a small frequency modulation of the feeding gyrotron around the slope of the resonance. Thus, toggling of the power between the two outputs of the diplexer connected to two articulating launchers was possible. Phasing and control of the modulation were performed via a set of Mirnov coils and appropriate signal processing. In the paper, technological issues, the design of the diplexer, the tracking of the diplexer resonance to the gyrotron frequency, the generation and processing of control signals for the gyrotron, and the typical performance concerning switching contrast and efficiency are discussed. The plasma scenario is described, and plasma experiments are presented, where the launchers scanned the region of the resonant surface continuously and also where the launchers were at a fixed position near to the q = 1.5-surface. In the second case, complete stabilization of a 3/2 NTM could be reached. These experiments are also seen as a technical demonstration for the applicability of diplexers in large-scale ECRH systems.

Compression-Friendly Low Power Test Application Based on Scan Slices Reusing

This paper presents a compression-friendly low power test scheme in EDT environment. The proposed approach exploits scan slices reusing to reduce the switching activity during shifting for test scheme based on linear decompressor. To avoid the impact on encoding efficiency from resulting control data, a counter is utilized to generate control signals. Experimental results obtained for some larger ISCAS’89 and ITC’99 benchmark circuits illustrate that the proposed test application scheme can improve significantly the encoding efficiency of linear decompressor.

Mono-pulse tracking system for active free space optical communication

Pilot survey experimental non-linear input-output mapping data are used for the design of neuro-controller. This controller process the beam location information from a static linear map of a 2D plane: Optoelectronic Position Detector (OPD), as observer, and generate the necessary control outputs to steer the beam using piezo-electronic actuators: Fast Steering Mirror (FSM). The beam centroid position is computed using the mono-pulse algorithm. The performance of the mono-pulse beam tracking system designed to aim the modulated laser beam to be at the center of the detector plane under atmospheric (medium) disturbances is experimentally investigated. The improvements attained in control signal generation, beam centroid stability, received power, outage probability and Bit Error Rate (BER) are comprehensively assessed using the experimental results obtained from the FSO communication test-beds constructed for the horizontal range of 0.5km at an altitude of 15.25m.

FPGA Design for Multiline Acquisition and Ethernet Interface in High-Frame-Rate Ultrasound Machines

ABSTRACTThe study presents the design of a 32-channel field-programmable gate arrays (FPGA) for ultrasound instruments working at high frame rates of the order of 1000 fps. The FPGA does multiline acquisition and Ethernet framing of the received data stream from the analog-to-digital converters (ADCs). The study also presents implementation of innovative methods of moving window algorithm, critical window capture, and envelope detection in the FPGA, for data rate reduction to aid video processing in laptops. The FPGA has serial peripheral interfacing bus interface towards microcontroller. FPGA also has data interface towards ADCs and Gigabit Ethernet MAC device. The microcontroller has in-line management interface with Gigabit Ethernet MAC through the FPGA. The FPGA dataflow consists of received signal processing of captured ultrasound data from ADCs, temporary storage in FPGA, and forwarding to external Ethernet devices after Ethernet framing. All the functional blocks are integrated and synchronized with an external clock. Internal clock and control signal generation modules generate the requisite timing clocks. The FPGA design has been realized in prototype hardware. The prototype hardware has microcontroller-based control from a MATLAB-based graphical user interface for device configurations and image processing. The captured packets as well as the acquired image results are shown. The design is modular, flexible, have large-scale integration, cost-effective, and can be easily replicated.