A 16-bit 18-MSPS flash-assisted SAR ADC with hybrid synchronous and asynchronous control logic

This paper presents a 16-bit,18-MSPS(million samples per second)flash-assisted successive-approximation-register(SAR)analog-to-digital converter(ADC)utilizing hybrid synchronous and asynchronous(HYSAS)timing control logic based on an on-chip delay-locked loop(DLL).The HYSAS scheme can provide a longer settling time for the capacitive digital-to-analog converter(CDAC)than the synchronous and asynchronous SAR ADC.Therefore,the issue of incomplete settling or ringing in the DAC voltage for cases of either on-chip or off-chip reference voltage can be solved to a large extent.In addition,the fore-ground calibration of the CDAC’s mismatch is performed with a finite-impulse-response bandpass filter(FIR-BPF)based least-mean-square(LMS)algorithm in an off-chip FPGA(field programmable gate array).Fabricated in 40-nm CMOS process,the proto-type ADC achieves 94.02-dB spurious-free dynamic range(SFDR),and 75.98-dB signal-to-noise-and-distortion ratio(SNDR)for a 2.88-MHz input under 18-MSPS sampling rate.

Enhanced Fuzzy Logic Control Model and Sliding Mode Based on Field Oriented Control of Induction Motor

In the context of induction motor control, there are various control strategies used to separately control torque and flux. One common approach is known as Field-Oriented Control (FOC). This technique involves transforming the three-phase currents and voltages into a rotating reference frame, commonly referred to as the “dq” frame. In this frame, the torque/speed and flux components are decoupled, allowing for independent control, by doing so, the motor’s speed can be regulated accurately and maintain a constant flux which is crucial to ensure optimal motor performance and efficiency. The research focused on studying and simulating a field-oriented control system using fuzzy control techniques for an induction motor. The aim was to address the issue of parameter variations, particularly the change in rotor resistance during motor operation, which causes the control system to deviate from the desired direction. This deviation implies to an increase in the magnetic flux value, specifically the flux component on the q-axis. By employing fuzzy logic techniques to regulate flux vector’s components in the dq frame, this problem was successfully resolved, ensuring that the magnetic flux value remains within the nominal limits. To enhance the control system’s performance, response speed, and efficiency of the motor, sliding mode controllers were implemented to regulate the current in the inner loop. The simulation results demonstrated the proficiency of the proposed methodology.

Implementation of Fuzzy Logic Control into an Equivalent Minimization Strategy for Adaptive Energy Management of A Parallel Hybrid Electric Vehicle

As government agencies continue to tighten emissions regulations due to the continued increase in greenhouse gas production, automotive industries are seeking to produce increasingly efficient vehicle technology. Hybrid electric vehicles (HEVs) have been introduced to mitigate problems while improving fuel economy. HEVs have led to the demand of creating more advanced controls software to consider multiple components for propulsive power in a vehicle. A large section in the software development process is the implementation of an optimal energy management strategy meant to improve the overall fuel efficiency of the vehicle. Optimal strategies can be implemented when driving conditions are known a prior. The Equivalent Consumption Minimization Strategy (ECMS) is an optimal control strategy that uses an equivalence factor to equate electrical to mechanical power when performing torque split determination between the internal combustion engine and electric motor for propulsive and regenerative torque. This equivalence factor is determined from offline vehicle simulations using a sensitivity analysis to provide optimal fuel economy results while maintaining predetermined high voltage battery state of charge (SOC) constraints. When the control hierarchy is modified or different driving styles are applied, the analysis must be redone to update the equivalence factor. The goal of this work is to implement a fuzzy logic controller that dynamically updates the equivalence factor to improve fuel economy, maintain a strict charge sustaining window of operation for the high voltage battery, and reduce computational time required during algorithm development. The adaptive algorithm is validated against global optimum fuel economy and charge sustaining results from a sensitivity analysis performed for multiple drive cycles. Results show a maximum fuel economy improvement of 9.82% when using a mild driving style and a 95% success rate when maintaining an ending SOC within 5% of the desired SOC regardless of starting SOC.

Programmable Logic Controller Block Monitoring System for Memory Attack Defense in Industrial Control Systems

Cyberattacks targeting industrial control systems(ICS)are becoming more sophisticated and advanced than in the past.A programmable logic controller(PLC),a core component of ICS,controls and monitors sensors and actuators in the field.However,PLC has memory attack threats such as program injection and manipulation,which has long been a major target for attackers,and it is important to detect these attacks for ICS security.To detect PLC memory attacks,a security system is required to acquire and monitor PLC memory directly.In addition,the performance impact of the security system on the PLC makes it difficult to apply to the ICS.To address these challenges,this paper proposes a system to detect PLC memory attacks by continuously acquiring and monitoring PLC memory.The proposed system detects PLC memory attacks by acquiring the program blocks and block information directly from the same layer as the PLC and then comparing them in bytes with previous data.Experiments with Siemens S7-300 and S7-400 PLC were conducted to evaluate the PLC memory detection performance and performance impact on PLC.The experimental results demonstrate that the proposed system detects all malicious organization block(OB)injection and data block(DB)manipulation,and the increment of PLC cycle time,the impact on PLC performance,was less than 1 ms.The proposed system detects PLC memory attacks with a simpler detection method than earlier studies.Furthermore,the proposed system can be applied to ICS with a small performance impact on PLC.

Logical and Timing Control for Diagnostic Neutral Beam Injection on HT-7

The timing and master control logic （MCL） units are the most important function units of the diagnostic neutral beam （DNB） power supply control system. The units control the operation of nine power supply subsystems of the DNB system, and provide protection for the DNB system from faults such as beam source arc down. Based on the characteristics of the DNB power supply system, the timing and MCL units have been designed, fabricated and tested. Experiments prove that the timing unit is convenient, flexible and reliable, and the MCL is functional.

ARTIFICIAL NEURAL NETWORK AND FUZZY LOGIC CONTROLLER FOR GTAW MODELING AND CONTROL

An artificial neural network(ANN) and a self-adjusting fuzzy logiccontroller(FLC) for modeling and control of gas tungsten arc welding(GTAW) process are presented.The discussion is mainly focused on the modeling and control of the weld pool depth with ANN and theintelligent control for weld seam tracking with FLC. The proposed neural network can produce highlycomplex nonlinear multi-variable model of the GTAW process that offers the accurate prediction ofwelding penetration depth. A self-adjusting fuzzy controller used for seam tracking adjusts thecontrol parameters on-line automatically according to the tracking errors so that the torch positioncan be controlled accurately.

Controlling Torque Distribution for Parallel Hybrid Vehicle Based on Hierarchical Structure Fuzzy Logic

The Hierarchical Structure Fuzzy Logic Control (HSFLC) strategies of torque distribute for Parallel Hybrid Electric Vehicle (PHEV) in the mode of operation of the vehicle i. e. , acceleration, cruise, deceleration etc. have been studied. Using secondly developed the hybrid vehicle simulation tool ADVISOR, the dynamic model of PHEV has been set up by MATLAB/SIMULINK. The engine, motor as well as the battery characteristics have been studied. Simulation results show that the proposed hierarchical structured fuzzy logic control strategy is effective over the entire operating range of the vehicle in terms of fuel economy. Based on the analyses of the simulation results and driver’s experiences, a fuzzy controller is designed and developed to control the torque distribution. The controller is evaluated via hardware-in-the-loop simulator (HILS). The results show that controller verify its value.

Fuzzy logic control strategy for submerged arc automatic welding of digital controlling

A microcomputer control system based on 80C320 and a switching regulation of wire feeder were designed. A correction factor based double model fuzzy logic controller （FLC） was introduced to achieve welding digital and intellectualized control by means of wire feeding speed feedback. The controller has many functions such as keyboard input, light emitting diode （LED） display and real-time intellectualized control of welding process etc. The controlling performance influenced by the coefficient of correction function was discussed. It was concluded by the experiments the relation between the coefficient of correction function and welding quality, when the coefficient of correction function is great, the dynamic character of controller is better, when the coefficient of correction function is small, the sensitivity character of controller is better. Experimental results also show that digital and fuzzy logic control method enable the improvement of appearance of weld and stability of welding process to be achieved in submerged arc automatic welding.

SPECTRUM HANDOFF IN COGNITIVE RADIO WITH FUZZY LOGIC CONTROL

The secondary usage of spectrum has been investigated in Cognitive Radio(CR) network to resolving the spectrum scarcity issue in wireless communication.When Primary Users(PU) who own the spectrum appear,spectrum handoff is needed to maintain the communications of Secondary Users.But the decision making of spectrum handoff is a challenge issue for CR network,because the input of decision making,which obtain through spectrum sensing,is heterogeneous and inexact.In this paper we will use fuzzy logic control theory to solve this issue and make use of new information for handoff operation:the probability of PU's occupancy at a certain channel.Our new algorithm can make more intelligent decision compared to simple traditional spectrum handoff decision making and reduce the probability of spectrum handoff,also the performance of SU's communication can be enhanced.

Nonsingular Terminal Sliding Mode Control With Ultra-Local Model and Single Input Interval Type-2 Fuzzy Logic Control for Pitch Control of Wind Turbines

As wind energy is becoming one of the fastestgrowing renewable energy resources,controlling large-scale wind turbines remains a challenging task due to its system model nonlinearities and high external uncertainties.The main goal of the current work is to propose an intelligent control of the wind turbine system without the need for model identification.For this purpose,a novel model-independent nonsingular terminal slidingmode control(MINTSMC)using the basic principles of the ultralocal model(ULM)and combined with the single input interval type-2 fuzzy logic control(SIT2-FLC)is developed for non-linear wind turbine pitch angle control.In the suggested control framework,the MINTSMC scheme is designed to regulate the wind turbine speed rotor,and a sliding-mode(SM)observer is adopted to estimate the unknown phenomena of the ULM.The auxiliary SIT2-FLC is added in the model-independent control structure to improve the rotor speed regulation and compensate for the SM observation estimation error.Extensive examinations and comparative analyses were made using a real-time softwarein-the-loop(RT-SiL)based on the dSPACE 1202 board to appraise the efficiency and applicability of the suggested modelindependent scheme in a real-time testbed.

Adaptive Sliding Mode Control for MIMO Nonlinear Systems Based on Fuzzy Logic Scheme

In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.

Fuzzy logic for large mining bucket wheel reclaimer motion control—from an engineer's perspective

The bucket wheel reclaimer(BWR) is a key piece of equipment which has been widely used for stacking and reclaiming bulk materials(i.e.iron ore and coal) in places such as ports,iron-steel plants,coal storage areas,and power stations from stockpiles.BWRs are very large in size,heavy in weight,expensive in price,and slow in motion.There are many challenges in attempting to automatically control their motion to accurately follow the required trajectories involving uncertain parameters from factors such as friction,turbulent wind,its own dynamics,and encoder limitations.As BWRs are always heavily engaged in production and cannot be spared very long for motion control studies and associated developments,a BWR model and simulation environment closely resembling real life conditions would be beneficial.The following research focused mainly on the implementation of fuzzy logic to a BWR motion control from an engineer's perspective.First,the modeling of a BWR including partially known parameters such as friction force and turbulence to the system was presented.This was then followed by the design of a fuzzy logic-based control built on a model-based control loop.The investigation provides engineers with an example of applying fuzzy logic in a model based approach to properly control the motion of a large BWR following defined trajectories,as well as to show possible ways of further improving the controller performance.The result indicates that fuzzy logic can be applied easily by engineers to overcome most motion control issues involving a large BWR.

A FUZZY-LOGIC CONTROL ALGORITHM FOR ACTIVE QUEUE MANAGEMENT IN IP NETWORKS

Active Queue Management (AQM) is an active research area in the Internet community. Random Early Detection (RED) is a typical AQM algorithm, but it is known that it is difficult to configure its parameters and its average queue length is closely related to the load level. This paper proposes an effective fuzzy congestion control algorithm based on fuzzy logic which uses the pre- dominance of fuzzy logic to deal with uncertain events. The main advantage of this new congestion control algorithm is that it discards the packet dropping mechanism of RED, and calculates packet loss according to a preconfigured fuzzy logic by using the queue length and the buffer usage ratio. Theo- retical analysis and Network Simulator (NS) simulation results show that the proposed algorithm achieves more throughput and more stable queue length than traditional schemes. It really improves a router's ability in network congestion control in IP network.

Design of a Fuzzy Logic Based Controller for Fluid Level Application

In industrial process control, fluid level control is one of the most basic aspects. Many control methods such as on-off, linear and PID (Proportional Integral Derivative) were developed time by time and used for precise controlling of fluid level. Due to flaws of PID controller in non-linear type processes such as inertial lag, time delay and time varying etc., there is a need of alternative design methodology that can be applied in both linear and non-linear systems and it can be execute with fuzzy concept. By using fuzzy logic, designer can realize lower development cost, superior feature and better end product. In this paper, level of fluid in tank is control by using fuzzy logic concept. For this purpose, a simulation system of fuzzy logic controller for fluid level control is designed using simulation packages of MATLAB software such as Fuzzy Logic Toolbox and Simulink. The designed fuzzy logic controller first takes information about inflow and outflow of fluid in tank than maintain the level of fluid in tank by controlling its output valve. In this paper, a controller is designed on five rules using two-input and one-output parameters. At the end, simulation results of fuzzy logic based controller are compared with classical PID controller and it shows that fuzzy logic controller has better stability, fast response and small overshoot.

Voltage Control of a 12/8 Pole Switched Reluctance Generator Using Fuzzy Logic

This paper presents a voltage controller for a 12/8 switched reluctance generator (SRG). SR machines have a robust with simple structure because they have no windings or permanent magnets on the rotor, so they are capable of working at high speed application and at rough condition. However, due to nonlinear nature, doubly salient poles, time variant parameters, and non-ideal current waveform, The SRG output voltage inherently contains ripples. The proposed voltage controller is based on fuzzy logic that is very efficient over uncertainty and parameter variations. The effectiveness of the proposed control method is verified by comparing the obtained result with that of a PI-controller.

Maximum Power Point Tracker Controller Using Fuzzy Logic Control with Battery Load for Photovoltaics Systems

The target of this paper is to model a Maximum Power Point Tracker (MPPT) using a Fuzzy Logic Control (FLC) algorithm and to investigate its behavior with a battery load. The advantage of this study over other studies in this field is that it considers a battery load rather than the commonly used resistive load especially when we deal with the relationship between MPPT and system load. The system is about 60 kW which is simulated under various environmental conditions by Matlab/Simulink program. For this type of non-linear application, FLC naturally offers a superior controller for the real load case. The artificial intelligence approach also benefits from this method for overcoming the complexity of nonlinear system modelling. The results show that FLC provides high performance for MPPT of PV system with battery load due to its low settling time and limited oscillation around the steady state value. These are assistant factors for increasing battery life.

Fuzzy Logic Control for Suspension Systems of Tracked Vehicles

A scheme of fuzzy logic control for the suspension system of a tracked vehicle is presented. A mechanical model for the whole body of a tracked vehicle, which is totally a fifteen-degree-of-freedom system, is established. The model includes the vertical motion, the pitch motion as well as the roll motion of the tracked vehicle. In contrast to most previous studies, the coupling effect among the vertical, the pitch and the roll motions of the suspension system of a tracked vehicle is considered simultaneously. The simulation of fuzzy logic control under road surface with random excitation shows that the acceleration, pitch angle and roll angle of suspension system can be efficiently controlled.

Analyses and Simulation of Fuzzy Logic Control for Suspension System of a Track Vehicle

The vibration caused by terrible road excitation affects the ride quality and safety of track vehicles. The vibration control of suspension systems is a very important factor for modern track vehicles. A fuzzy logic control for suspension system of a track vehicle is presented. A mechanical model and a system of difft, rential equations of motion taking account of the mass of loading wheel are established. Then the fuzzy logic control is applied to control the vibration of suspension system of track vehicles for sine signal and random road surfaces. Numerical simulation shows that the maximum acceleration of suspension system can be reduced to 44 % of the original value for sine signal road surface, and the mean square root of acceleration of suspension system can be reduced to 21% for random road surface. Therefore, the proposed fuzzy logic control is an efficient method for the suspension systems of track vehicles.

Fuzzy Logic Control for Semi-Active Suspension System of Tracked Vehicle

The model of half a tracked vehicle semi-active suspension is established. The fuzzy logic controller of the semi-active suspension system is constructed. The acceleration of driver's seat and its time derivative are used as the inputs of the fuzzy logic controller, and the fuzzy logic controller output determines the semi-active suspension controllable damping force. The fuzzy logic controller is to minimize the mean square root of acceleration of the driver's seat. The control forces of controllable dampers behind the first road wheel are obtained by time delay, and the delay times are determined by the vehicle speed and axles distances. The simulation results show that this control method can decrease the acceleration of driver's seat and the suspension travel of the first road wheel, the ride quality is improved obviously.

Integrate Fuzzy Logic Stable Control System of Bank-to-Turn Missiles

The question of stable control system of bank-to-turn (BTT) missiles is a bottleneckin BTT technology. Integrate fuzzy logic stable control system of BTT missiles is designed in whichthree main problems are resolved. How to select input variables Of the fuzzy logic controller and howto guarantee completeness of the output control are two of them. The last one is how to coordinatethe fuzzy logic controllers in integrate fuzzy logic stable control system. Simulating results prov that integrate fuzzy logic stable coatrol system of BTT missiles is sueccessful, and it can be widelyused in future.