Fractional-order optimal fuzzy control for network delay

Fuzzy logic control has been used frequently in tuning network control system (NCS) due to its on-line dynamic static non-linear match and several remarkable fractional-order controllers have achieved satisfactory control performance when applied to NCS in present years, therefore, in this paper, a novel fractional fuzzy logic controller which combined the fractional algorithm and fuzzy logic control together has been proposed to deal with fixed and random network induced delays in closed-loop feedback systems. The comparisons of set-point tracking performances of fractional fuzzy logic PID controller (FFuzzyPID), conventional fuzzy logic PID controller(FuzzyPID), fractional optimal PID controller (FOPID), and optimal PID controller(OPID) on a representative plant with fixed and random network delays have been shown with simulations. The simulation results indicate that fractional fuzzy logic controller has higher capability to handle network delays compared with other controllers in most cases.     

Genetic algorithm based active vibration control for a moving flexible smart beam driven by a pneumatic rod cylinder

A rod cylinder based pneumatic driving scheme is proposed to suppress the vibration of a flexible smart beam. Pulse code modulation (PCM) method is employed to control the motion of the cylinder's piston rod for simultaneous positioning and vibration suppression. Firstly, the system dynamics model is derived using Hamilton principle. Its standard state-space representation is obtained for characteristic analysis, controller design, and simulation. Secondly, a genetic algorithm (GA) is applied to optimize and tune the control gain parameters adaptively based on the specific performance index. Numerical simulations are performed on the pneumatic driving elastic beam system, using the established model and controller with tuned gains by GA optimization process. Finally, an experimental setup for the flexible beam driven by a pneumatic rod cylinder is constructed. Experiments for suppressing vibrations of the flexible beam are conducted. Theoretical analysis, numerical simulation and experimental results demonstrate that the proposed pneumatic drive scheme and the adopted control algorithms are feasible. The large amplitude vibration of the first bending mode can be suppressed effectively.     

Fuzzy coordinator compensation for balancing control of cart-seesaw system

In contrast with fully controllable systems, a super articulated mechanical system (SAMS) is a controlled underactuated mechanical system in which the dimensions of the configuration space exceed the dimensions of the control input space. The control of the cart-seesaw system is especially difficult since it is an underactuated mechanism (three degrees of freedom and only two inputs). This research develops a balancing approach for a novel SAMS model, called the cart-seesaw system, using fuzzy logic and fuzzy coordinator compensation to drive the sliding carts and keep the seesaw angle close to zero in the equilibrium state. Experimental results indicate that utilizing the proposed control methodology significantly enhances the performance. Moreover, the presentation of the fuzzy balancing controller is not considerably affected by changes in the environmental parameters, which demonstrates the effectiveness of the fuzzy controller in minimizing the seesaw tilt angle in the time domain, although the system is caused by unpredicted loading variation. Moreover, the experimental results indicate the usefulness and robustness of the proposed fuzzy control methodology. Furthermore, the proposed software/hardware platform can be beneficial for standardizing laboratory equipment and developing amusement apparatus.     

Free vibration control of smart composite beams using particle swarm optimized self-tuning fuzzy logic controller

This paper deals with active free vibrations control of smart composite beams using particle-swarm optimized self-tuning fuzzy logic controller. In order to improve the performance and robustness of the fuzzy logic controller, this paper proposes integration of self-tuning method, where scaling factors of the input variables in the fuzzy logic controller are adjusted via peak observer, with optimization of membership functions using the particle swarm optimization algorithm. The Mamdani and zero-order Takagi–Sugeno–Kang fuzzy inference methods are employed. In order to overcome stability problem, at the same time keeping advantages of the proposed self-tuning fuzzy logic controller, this controller is combined with the LQR making composite controller. Several numerical studies are provided for the cantilever composite beam for both single mode and multimodal cases. In the multimodal case, a large-scale system is decomposed into smaller subsystems in a parallel structure. In order to represent the efficiency of the proposed controller, obtained results are compared with the corresponding results in the cases of the optimized fuzzy logic controllers with constant scaling factors and linear quadratic regulator.     

Fuzzy logic membership implementation using optical hardware components

Intelligent control techniques consist of knowledge-based expert or fuzzy logic control. One obvious drawback in many such applications is that fuzzy logic memberships are implemented at the lowest level. In high-bandwidth processes, this form of fuzzy logic membership implementation would require high speed and accuracy in the presence of strong nonlinearities and dynamic coupling. This paper presents a novel methodology called the Opto-fuzzy method to design a fuzzy logic membership using an optical hardware component. The proposed scheme is applied to triangular-shaped and half trapezoidal-shaped membership functions.     

Vibration suppression control of smart piezoelectric rotating truss structure by parallel neuro-fuzzy control with genetic algorithm tuning

The main goal of this paper is to develop a novel approach for vibration control on a piezoelectric rotating truss structure. This study will analyze the dynamics and control of a flexible structure system with multiple degrees of freedom, represented in this research as a clamped–free–free–free truss type plate rotated by motors. The controller has two separate feedback loops for tracking and damping, and the vibration suppression controller is independent of position tracking control. In addition to stabilizing the actual system, the proposed proportional–derivative (PD) control, based on genetic algorithm (GA) to seek the primary optimal control gain, must supplement a fuzzy control law to ensure a stable nonlinear system. This is done by using an intelligent fuzzy controller based on adaptive neuro-fuzzy inference system (ANFIS) with GA tuning to increase the efficiency of fuzzy control. The PD controller, in its assisting role, easily stabilized the linear system. The fuzzy controller rule base was then constructed based on PD performance-related knowledge. Experimental validation for such a structure demonstrates the effectiveness of the proposed controller. The broad range of problems discussed in this research will be found useful in civil, mechanical, and aerospace engineering, for flexible structures with multiple degree-of-freedom motion.     

Fuzzy auto-tuning PID control of multiple joint robot driven by ultrasonic motors

A three-joint robot is directly driven by ultrasonic motors with advantage of high torque at low speed. The speed of the ultrasonic motors is actually controlled by regulating their operating frequencies. The kinematic and kinetic analyses of the robot have been carried out using Adams. Due to the lack of accurate control model of ultrasonic motors and the time-varying motor parameters, a fuzzy auto-tuning proportional integral derivative (PID) controller for the robot is experimented, in which a simple method to tune parameters of the PID type fuzzy controller on-line is developed and a new position–speed feedback strategy is proposed and implemented. The effectiveness of the proposed control strategy and fuzzy logic controller is verified by experimental investigation.     

Active pneumatic vibration isolation system using negative stiffness structures for a vehicle seat

In this paper, an active pneumatic vibration isolation system using negative stiffness structures (NSS) for a vehicle seat in low excitation frequencies is proposed, which is named as an active system with NSS. Here, the negative stiffness structures (NSS) are used to minimize the vibratory attraction of a vehicle seat. Owing to the time-varying and nonlinear behavior of the proposed system, it is not easy to build an accurate dynamic for model-based controller design. Thus, an adaptive intelligent backstepping controller (AIBC) is designed to manage the system operation for high-isolation effectiveness. In addition, an auxiliary control effort is also introduced to eliminate the effect of the unpredictable perturbations. Moreover, a radial basis function neural network (RBFNN) model is utilized to estimate the optimal gain of the auxiliary control effort. Final control input and the adaptive law for updating coefficients of the approximate series can be obtained step by step using a suitable Lyapunov function. Afterward, the isolation performance of the proposed system is assessed experimentally. In addition, the effectiveness of the designed controller for the proposed system is also compared with that of the traditional backstepping controller (BC). The experimental results show that the isolation effectiveness of the proposed system is better than that of the active system without NSS. Furthermore, the undesirable chattering phenomenon in control effort is quite reduced by the estimation mechanism. Finally, some concluding remarks are given at the end of the paper.     

Motion planning and actuator specialization in the control of active-flexible link robots

Trajectory planning is a well-known open-loop control strategy to minimize residual vibrations in point-to-point tasks of systems featuring mechanical flexibility. However, the major drawback of open-loop control is its limitation in coping with modeling uncertainty. In this paper a novel approach to trajectory planning based on LQR theory is proposed and applied to a single flexible link robot. To improve performance under parameter uncertainty the strategy is combined with collocated vibration control through piezoelectric actuation of the link. This combination raises the issue of the roles and the contribution of each actuator type to the overall performance of the maneuver. An actuator specialization is proposed where the joint controller is responsible for the gross vibrationless motion of the link, while the link actuators are expected to deal only with residual vibrations that may arise from modeling errors. Simulation and experimental results validate the trajectory planning methodology and the combination of the open-loop strategy with collocated vibration control.     

Control of a unique active vibration isolator with a phase compensation technique and automatic on/off switching

This work examines the characteristics of a unique active vibration isolator and develops a control strategy for it. The proposed active vibration isolator is introduced and its dynamic model is presented. A characterization study is conducted to identify system parameters. It is shown that with a simple proportional feedback the closed-loop system has a very narrow stability margin due to the inherent dynamics of the actuator. To improve the stability of the closed-loop system and enhance the performance of vibration isolation, a phase compensator is incorporated in the control scheme. An optimization problem is formulated to determine the optimum controller parameters by minimizing the 2nd norm of the displacement transmissibility. Both absolute position feedback and relative position feedback are considered. In real time implementation, an automatic on/off switching strategy is devised to take full advantage of both the active isolator and passive isolator. The experimental results show that with the proposed control scheme, the isolator is capable of suppressing base excitations effectively.     

Parametric control of an axially moving string via fuzzy sliding-mode and fuzzy neural network methods

This study is dedicated to design effective control schemes to suppress transverse vibration of an axially moving string system by adjusting the axial tension of the string. To this end, a continuous model in the form of partial differential equations is first established to describe the system dynamics. Using an energy-like system functional as a Lyapunov function, a sliding-mode controller (SMC) is designed to be applied when the level of vibration is not small. Due to non-analyticity of the SMC control effort generated as vibration level becoming small, two intelligent control schemes are proposed to complete the task — fuzzy sliding-mode control (FSMC) and fuzzy neural network control (FNNC). Both control approaches are based on a common structure of fuzzy control, taking switching function and its derivative as inputs and tension variation as output to reduce the transverse vibration of the string. In the framework of FSMC, genetic algorithm (GA) is utilized to search for the optimal scalings for the inputs; in addition, the technique of regionwise linear fuzzy logic control (RLFLC) is employed to simplify the computation procedure of the fuzzy reasoning. On the other hand, FNNC is proposed for conducting on-line tuning of control parameters to overcome model uncertainty. Numerical simulations are conducted to verify the effectiveness of controllers. Satisfactory stability and vibration suppression are attained for all controllers with the findings that the FSMC assisted by GA holds the advantage of fast convergence with a precise model while the FNNC is robust to model uncertainty and environmental disturbance although a relatively slower convergence could be present.     

Active control of friction-induced self-excited vibration using adaptive fuzzy systems

Vibration caused by friction is harmful to engineering systems. Understanding the mechanism of such a physical phenomenon and developing some strategies to effectively control the vibration have both theoretical and practical significance. Based on our previous work, this paper deals with a problem of active compensation control of friction-induced self-excited vibration using adaptive fuzzy systems. Comparative studies on control performance are carried out, where a class of adaptive compensation control schemes with various friction models are applied to control a motion dynamics with friction. It is observed that our proposed modeling and control techniques are powerful to eliminate the limit cycle and the steady-state error. Furthermore, robustness of the proposed controller with respect to external disturbances is discussed. Simulation results show that the active controller with adaptive fuzzy friction compensation outperforms other active controllers with compensation terms characterized by three well-known friction models.     

永磁直线同步电机位置系统的模糊IP控制研究

针对具有电磁推力大、响应快、易于矢量解耦控制的永磁直线同步电机PMLSM,研究高精度位置伺服控制系统的设计,以满足高速加工与高精度微进给加工的需求。考虑被控对象的变化和外界扰动,控制器的参数难于在线修订,设计了一种模糊/积分-比例IP位置控制器。它将具有并联反馈环节的IP控制器与模糊控制器有效结合,根据位置偏差的变化率进行切换,即存在较大输入指令与系统输出偏差较大时采用模糊控制,而系统输出接近于输入指令时则采用IP控制器,从而发挥模糊控制器对变参数系统的自适应性和IP控制器的快速和准确性优势。仿真实验结果表明模糊/IP控制器在稳态精度和动态性能方面优于单纯的IP控制器和模糊控制器,能够满足变参数控制系统的性能指标。     

基于自适应模糊控制的分数阶混沌系统同步

本文主要研究了带有未知外界扰动的分数阶混沌系统的同步问题.基于分数阶Lyapunov稳定性理论,构造了分数阶的参数自适应规则以及模糊自适应同步控制器.在稳定性分析中主要使用了平方Lyapunov函数.该控制方法可以实现两分数阶混沌系统的同步,使得同步误差渐近趋于0.最后,数值仿真结果验证了本文方法的有效性.     

Hybrid fuzzy logic control of laser surface heat treatments

This paper presents an advanced hybrid fuzzy logic control system for laser surface heat treatments, which allows to increase significantly the uniformity and final quality of the obtained product, reducing the rejection rate and increasing the productivity and efficiency of the treatment. Basically, the proposed hybrid control structure combines a fuzzy logic controller, with a pure integral action, both fully decoupled, improving the performances of the process with a reasonable design cost, since the system nonlinearities are fully compensated by the fuzzy component of the controller, while the integral action contributes to eliminate the steady-state error.     

Adaptive fuzzy sliding mode control of smart structures

Smart structures are usually designed with a stimulus-response mechanism to mimic the autoregulatory process of living systems. In this work, in order to simulate this natural and self-adjustable behavior, an adaptive fuzzy sliding mode controller is applied to a shape memory two-bar truss. This structural system exhibits both constitutive and geometrical nonlinearities presenting the snap-through behavior and chaotic dynamics. On this basis, a variable structure controller is employed for vibration suppression in the chaotic smart truss. The control scheme is primarily based on sliding mode methodology and enhanced by an adaptive fuzzy inference system to cope with modeling inaccuracies and external disturbances. The robustness of this approach against both structured and unstructured uncertainties enables the adoption of simple constitutive models for control purposes. The overall control system performance is evaluated by means of numerical simulations, promoting vibration reduction and avoiding snap-through behavior.     

Control of a rotating cantilever beam using a torque actuator and a distributed piezoelectric polymer actuator

A torque actuator and a distributed piezoelectric polymer (PVDF) actuator are utilized for control of a rotating cantilever flexible beam. The torque control contains proportional and derivative (PD) feedback for rigid motion control and a PVDF actuator control for vibration damping. Unlike previous approaches in the literature in which the angular velocity feedback was utilized, in this study we propose to use the linear velocity feedback (L-type) in our controller design for feasible implementation and avoiding modal truncation. The stability of the system with the L-type control has been analyzed, using the concept of a virtual joint model. The advantage of the proposed scheme lies in easy implementation, avoidance of modal truncation, efficient suppression of the dominant mode of vibration, and allowing high-speed motions. Numerical examples demonstrate the effectiveness of the proposed approach.     

Pinning impulsive synchronization of stochastic delayed coupled networks

In this paper,the pinning synchronization problem of stochastic delayed complex network (SDCN) is investigated by using a novel hybrid pinning controller. The proposed hybrid pinning controller is composed of adaptive controller and impulsive controller,where the two controllers are both added to a fraction of nodes in the network. Using the Lyapunov stability theory and the novel hybrid pinning controller,some sufficient conditions are derived for the exponential synchronization of such dynamical networks in mean square. Two numerical simulation examples are provided to verify the effectiveness of the proposed approach. The simulation results show that the proposed control scheme has a fast convergence rate compared with the conventional adaptive pinning method.     

基于模糊控制的 VSVPWM 中点电位平衡策略

针对中点钳位型(NPC)三电平逆变器存在的直流侧中点电位不平衡问题,提出了一种基于模糊控制 的中点电位平衡策略。该策略重新定义了虚拟空间矢量,使虚拟小矢量不引起中点电位波动,并在虚拟中矢量中 引入了对中点电位不平衡有抑制作用的控制因子 Q。同时,设计了由模糊控制器 A 和 B 构成的组合模糊控制器, 该控制器能够依据中点电位偏移情况调整控制因子 Q,实现对中点电位的闭环控制。仿真和实验结果表明,采用 该策略的 NPC 型三电平逆变器中点电位不平衡问题能得到有效改善。     

带有未知非对称控制增益的不确定分数阶混沌系统自适应模糊同步控制

针对带有非对称控制增益的不确定分数阶混沌系统的同步问题设计了模糊自适应控制器. 模糊逻辑系统用来逼近未知的非线性函数, 非对称的控制增益矩阵被分解为一个未知的正定矩阵、一个对角线上元素为+1或-1的已知对角矩阵和 一个未知的上三角矩阵的乘积. 基于分数阶Lyapunov稳定性理论构造了模糊控制器以及分数阶的参数自适应律, 在保证所有变量有界的情况下实现驱动系统和响应系统的同步. 在分数阶系统稳定性分析中给出了一种平方Lyapunov函数的使用方法, 根据此方法很多针对整数阶系统的控制方法可以推广到分数阶系统中. 最后数值仿真结果验证了所提控制方法的可行性.