Fuzzy logic congestion control for broadband wireless IPTV

All-IP broadband networks are being created with multimedia bandwidth requirements in mind. A unicast IPTV service forming a pipe or sub-channel on the converged network may need to negotiate a broadband wireless link. Where there is a need for multiple variable bit rate video streams to share the same pipe a problem of link utilisation arises [1], requiring congestion control at the server bank. Conventional controllers such as TCP-friendly rate control (TFRC) [2] and TCP emulation at receivers (TEAR) [3], originating in a TCP-dominated internet, will stream video up to the capacity of the pipe, but reacting to feedback may overestimate the capacity, resulting in packet loss, which leads to reduced video quality. In this Letter, fuzzy logic control (FLC) is shown to outperform conventional control in such a network by changing the quantisation parameter for live video or through a bit rate transcoder for pre-encoded video. Moreover, compared to prior use of traditional (type-1) fuzzy logic for similar purposes [4], interval type-2 (IT2) FLC has been employed, as this is robust to feedback measurement uncertainties.     

Fuzzy logic for constant force control of end milling

The machining condition usually has significant variation resulting from the change of cutting depth and the intrinsic property of the workpiece. In order to maintain the performance of a classical proportional integral derivative control system, the tool life and machining quality, conservative feedrate, and cutting depth change are prespecified as the limitations of computer numerically controlled operators. Therefore, constant cutting force control is proposed as a useful approach for increasing the metal removal rate and the tool life. However, the model-based controller cannot handle the nonlinearity of a force control system due to cutting condition variations. Here, a fuzzy controller with learning ability was employed to improve both the system performance and the adaptability. This control approach vias implemented on a retrofit old-fashioned milling machine for the end milling process. The experimental results show that this control strategy has smooth feedrate and good cutting force dynamic responses     

Fuzzy logic control of an active power line conditioner

Fuzzy logic and active power line conditioners (APLC) are two tools that are being increasingly applied to power quality problems. In this paper, a switch-mode APLC that uses fuzzy logic to control the semiconductor switches is described. Frequency-domain analysis is used to determine the desired compensation current, and a rule-based piecewise-linear fuzzy proportional-integral controller (FPIC) provides the appropriate switching pattern of the APLC to generate the actual compensation current. MATLAB simulations and experimental measurements on a low-power (700 VA), digital signal processor-based, hardware prototype show that the APLC produces excellent results despite the use of a relatively low switching frequency, which is necessary to minimize semiconductor switching losses. The simulations and measurements are in good agreement and show that the APLC/FPIC system can significantly improve line current total harmonic distortion and power factor during both steady-state and transient operating conditions.     

Fuzzy logic enhanced speed control of an indirect field-orientedinduction machine drive

Field orientation control (FOC) of induction machines has permitted fast transient response by decoupled torque and flux control. However, field orientation detuning caused by parameter variations is a major difficulty for indirect FOC methods. Traditional probability density function (PID) controllers have trouble meeting a wide range of speed tracking performance even when proper field orientation is achieved. PID controller performance is severely degraded when detuning occurs. This paper presents a fuzzy logic design approach that can meet the speed tracking requirements even when detuning occurs. Computer simulations and experimental results obtained via a general-purpose digital signal processor (DSP) system are presented     

Fuzzy logic applied to speed control of a stepping motor drive

Nowadays, thanks to the development of microprocessors, stepping motors are widely used in robotics and in the numerical control of machine tools where they have to perform high-precision positioning operations. Nevertheless, the variations of the mechanical configuration of the drive, which are common to these two applications, can lead to a loss of synchronism for high stepping rates. Moreover, the classical open-loop speed control is weak and a closed-loop control becomes necessary. In this paper, the fuzzy logic principle is applied to control the speed of a stepping motor drive with feedback. An advanced test bed is used in order to evaluate the tracking properties and the robustness capacities of the fuzzy logic controller when variations of the mechanical configuration occur. The experiment has been performed using a low-cost 16 bit microcontroller in order to verify the design performance     

Fuzzy logic flowers in Japan

Fuzzy logic is briefly explained, and its use in controllers is described. Further theoretical development and commercial implementation of these ideas in Japan is surveyed. Work progress in domains other than control is indicated     

埋弧自动焊弧长模糊控制器

为满足埋弧焊过程弧长实时稳定控制要求,研制了以高速微处理为核心的微机控制系统和一套开关式的送丝调速系统.引入通过模糊目标隶属函数调节修正函数来调整模糊控制规则的模糊控制算法,设计了以模糊控制为核心的埋弧焊过程电弧智能控制系统.在实验的基础上讨论了模糊控制的修正函数对系统性能的影响,合理的控制参数直接影响焊接质量.实验表明,该系统采用模糊控制在焊缝成型以及过程稳定等方面都有较大提高.     

Fuzzy logic control of a space-vector PWM current regulator forthree-phase power converters

This paper presents a fuzzy logic implementation of space-vector pulse-width modulation (PWM) for three-phase power converters. The conventional space-vector PWM current regulator implementation is generally computationally complex. The fuzzy logic controller implementation relieves the processor of a number of computations, thereby accommodating a less expensive microprocessor. The AC-side rectifier voltages are used as fuzzy-state variables. The fuzzy logic control has two outputs: magnitude and angle of reference voltage. Both conventional space-vector PWM and the fuzzy logic controller are implemented to evaluate performance using a 16-b microcontroller (68HC16). Experimental results are provided for both controllers at the same operating point, where the power drawn by the load is about 3 kW. The fuzzy logic controller reduces the computational burden on the processor by about 30%     

埋弧自动焊弧长模糊控制器

为满足埋弧焊过程弧长实时稳定控制要求,研制了以高速微处理为核心的微机控制系统和一套开关式的送丝调速系统。引入通过模糊目标隶属函数调节修正函数来调整模糊控制规则的模糊控制算法,设计了以模糊控制为核心的埋弧焊过程电弧智能控制系统。在实验的基础上讨论了模糊控制的修正函数对系统性能的影响,合理的控制参数直接影响焊接质量。实验表明,该系统采用模糊控制在焊缝成型以及过程稳定等方面都有较大提高。     

Fuzzy logic based on-line efficiency optimization control of anindirect vector-controlled induction motor drive

Improvement of adjustable speed drive system efficiency is important not only from the viewpoints of energy saving and cooling system operation, but also from the broad perspective of environmental pollution. The paper describes a fuzzy logic based on-line efficiency optimization control of a drive that uses an indirect vector controlled induction motor speed control system in the inner loop. At steady-state light-load condition, a fuzzy controller adaptively decrements the excitation current on the basis of measured input power such that, for a given load torque and speed, the drive settles down to the minimum input power, i.e., operates at maximum efficiency. The low-frequency pulsating torque due to decrementation of rotor flux is compensated in a feedforward manner. If the load torque or speed command changes, the efficiency search algorithm is abandoned and the rated flux is established to get the best transient response. The drive system with the proposed efficiency optimization controller has been simulated with lossy models of the converter and machine, and its performance has been thoroughly investigated. An experimental drive system with the proposed controller implemented on a TMS320C25 digital signal processor, has been tested in the laboratory to validate the theoretical development     

Fuzzy logic based intelligent control of a variable speed cagemachine wind generation system

The paper describes a variable speed wind generation system where fuzzy logic principles are used for efficiency optimization and performance enhancement control. A squirrel cage induction generator feeds the power to a double-sided pulse width modulated converter system which pumps power to a utility grid or can supply to an autonomous system. The generation system has fuzzy logic control with vector control in the inner loops. A fuzzy controller tracks the generator speed with the wind velocity to extract the maximum power. A second fuzzy controller programs the machine flux for light load efficiency improvement, and a third fuzzy controller gives robust speed control against wind gust and turbine oscillatory torque. The complete control system has been developed, analyzed, and validated by simulation study. Performances have then been evaluated in detail     

Artificial neural network control of FES in paraplegics for patientresponsive ambulation

Describes a binary adaptive resonance theory (ART-1)-based artificial neural network (ANN) adapted for controlling functional electrical stimulation (FES) to facilitate patient-responsive ambulation by paralyzed patients with spinal cord injures. This network is to serve as a controller in an FES system developed by the first author which is presently in use by 300 patients worldwide (still without ANN control) and which was the first and the only FES system approved by the FDA. The proposed neural network discriminates above-lesion upper-trunk electromyographic (EMG) time series to activate standing and walking functions under FES and controls FES stimuli levels using response-EMG signals. For this particular application, the authors introduce several modifications of the ART-1 for pattern recognition and classification. First, a modified on-line learning rule is proposed. The new rule assures bidirectorial modification of the stored patterns and prevents noise interference. Second, a new reset rule is proposed which prevents “exact matching” when the input is a subset of the chosen pattern. The authors show the applicability of a single ART-1-based structure to solving two problems, namely, 1) signal pattern recognition and classification, and 2) control. This also facilitates ambulation of paraplegics under FES, with adequate patient interaction in initial system training, retraining the network when needed, and in allowing patient's manual override in the ease of error, where any manual override serves as a retraining input to the neural network. Thus, the practical control problems (arising in actual independent patient ambulation via FES) were all satisfied by a relatively simple ANN design     

Fuzzy logic based network reliability evaluation

A method for evaluation of the reliability of a network and its nodes is suggested reflecting the customers' requirements and needs stated in linguistic form. The method uses the fuzzy logic to formulate criteria for reliability evaluation and grading on a percentage scale. An illustrative example is included.     

Tuning of a nonanalytical hierarchical control system for reachingwith FES

Point-to-point functional movements involve simultaneous shoulder and elbow joint rotations. In able-bodied subjects these movements are fully automatic, and feed-forward control ensures the synergistic activity of many muscles. Synergy between joint rotations was defined and described as a scaling between joint angular velocities (M. Popovic and D. Popovic, J. Electromyog. Kinesiol., vol. 4, p. 242-53, 1994). Similarly, subjects who can control their shoulder movements may be assisted in reaching tasks by functional electrical stimulation (FES) of elbow extensor muscles. The synergistic control paradigm can be implemented in real-time by employing a hierarchically structured production-rules method. The use of production-rules necessitates the acquisition of knowledge and the assembly of a rule-base. A nonparametric technique was designed for the identification of the rules. The identification process was divided into two phases: determination of the scaling parameters, and determination of the stimulation parameters. The scaling parameters, needed for the coordination of movements, were determined in able-bodied subjects. Those depend exclusively on the initial and target positions of the hand. The number of scalings could be reduced by dividing the workspace into 12 zones. The stimulation parameters, needed for the execution of movements, were determined in subjects with paralyzed elbow extensor muscles by identifying triplets: elbow angular velocity, elbow angular acceleration (velocity increments), and the corresponding pulse durations for various classes of movements and loads attached to the hand     

Fuzzy logic approach to VLSI placement

A contemporary definition of VLSI placement problem is characterized by multiple objectives. These objectives are: timing, chip area, interconnection length and possibly others. In this paper, fuzzy logic has been used to facilitate multiobjective decision-making in placement for standard cell design style. A placement process has been defined in terms of linguistic variables, linguistic values and membership functions. Various objectives have been related by hierarchical fuzzy logic rules implemented as object-oriented programming objects. It is demonstrated that a designed fuzzy logic system is flexible in selecting goals and considering tradeoffs. Details of implementation, experimental results and comparisons with other systems are provided     

Fuzzy logic control-a taxonomy of demonstrated benefits

The motivations for fuzzy logic control (FLC) are illuminated by exploring the benefits obtained by application designers through its use. A context for this exploration is set with a discussion of the characteristics of control policies and of the general attributes of FLC. Each benefit is described by reference to reported FLC implementations in which the benefit is demonstrated. Based on common features of the example applications, application preconditions for obtaining each benefit are stated     

模糊逻辑及其在数据融合中的应用

自从１９６５年Ｚａｄｅｈ发表关于模糊集理论的文章以来,模糊集理论已在工业控制、医疗诊断、经济决策、模式识别等领域得到广泛应用,随着模糊逻辑和可能性理论的提出和深入研究,它们在不确定推理模型的设计和多传感器信息融合中显示出越来越强大的优势,文中探讨它们在多传感器数据融合中的应用。     

Sliding mode closed-loop control of FES: controlling the shank movement

Functional electrical stimulation (FES) enables restoration of movement in individuals with spinal cord injury. FES-based devices use electric current pulses to stimulate and excite the intact peripheral nerves. They produce muscle contractions, generate joint torques, and thus, joint movements. Since the underlying neuromuscular-skeletal system is highly nonlinear and time-varying, feedback control is necessary for accurate control of the generated movement. However, classical feedback/closed-loop control algorithms have so far failed to provide satisfactory performance and were not able to guarantee stability of the closed-loop system. Because of this, only open-loop controlled FES devices are in clinical use in spite of their limitations. The purpose of the reported research was to design a novel closed-loop FES controller that achieves good tracking performance and guarantees closed-loop stability. Such a controller was designed based on a mathematical neuromuscular-skeletal model and is founded on a sliding mode control theory. The controller was used to control shank movement and was tested in computer simulations as well as in actual experiments on healthy and spinal cord injured subjects. It demonstrated good robustness, stability, and tracking performance properties.     

Newton-method based iterative learning control for robot-assisted rehabilitation using FES

Precise control of useful movement is critical in providing effective upper limb stroke rehabilitation using functional electrical stimulation (FES). To address the lack of accuracy currently available in clinical practice, this paper develops a general framework based on iterative learning control (ILC), an approach that has been successfully employed in three clinical treatment trials. An upper limb model is first developed to encompass unconstrained movements of the upper arm. In line with clinical need, additional assistance is then incorporated via a general class of robotic support mechanism. An iterative learning scheme is then developed to enable a subset of joint angles to be controlled via stimulation of an arbitrary set of muscles. This scheme is the first ILC approach which explicitly addresses coupled multivariable nonlinear dynamics in upper-limb rehabilitation, enforcing convergence over multiple executions of a reaching task. Experiments with six participants confirm practical utility and performance.     

Stability and a control strategy of a multilink musculoskeletalmodel with applications in FES

Introduces a relegated control strategy for point-to-point movement of musculoskeletal systems driven by redundant actuators. The actuator system is partitioned to two functional groupings referred to as gravity compensators and movement generators. Unlike dynamic optimization methods, relegation of control enables real-time computation of control signals to the muscle actuators. It is shown that this strategy significantly reduces the degree of coactivation needed to stabilize the movement. The real-time nature of this strategy coupled with reduced coactivation makes the proposed strategy amenable for multichannel control of paraplegics through functional electrical stimulation. Simulations of a three-link sagittal system are conducted to test the algorithm for a bowing movement