Self-tuning fuzzy logic control of a non-linear structural system with ATMD against earthquake

Self-tuning fuzzy logic controllers (STFLC) for the active control of Marmara Kocaeli earthquake excited building structures are studied in this paper. Vibration control using intelligent controllers, such as fuzzy logic has attracted the attention of structural control engineers during the last few years, because fuzzy logic can handle nonlinearities, uncertainties, and heuristic knowledge effectively and easily. The improved seismic control performance can be achieved by converting a simply designed static gain into a real time variable dynamic gain through a self-tuning mechanism. Self-tuning fuzzy logic controller is designed to reduce the story-drift of each floor. The simulated system has a nine-degree-of-freedom, which is modeled using nonlinear behavior of the base-structure interaction. Modeled system was simulated against the ground motion of the Marmara Kocaeli earthquake (M _w=7.4) in Turkey on 17 August, 1999. At the end of the study, the time history of the story displacements, accelerations, ATMD displacements, control voltage, and frequency responses of the both uncontrolled and controlled cases are presented. The robustness of the controller has been checked through the uncertainty in stiffness of the structure. Performance of the designed STFLC has been demonstrated for the different disturbance using ground motion of the Kobe earthquake. Simulations of an earthquake excited nine story structure are performed to prove the validity of proposed control strategy.     

Self-tuning fuzzy logic control of crane structures against earthquake induced vibration

Self-tuning fuzzy logic controllers (STFLC) for the active control of Marmara Kocaeli Earthquake excited crane structures are studied in this paper. Vibration control using intelligent controllers, such as fuzzy logic has attracted the attention of structural control engineers during the last few years, because fuzzy logic can handle, uncertainties and heuristic knowledge and even non-linearities effectively and easily. The improved seismic control performance can be achieved by converting a simply designed static gain into a real time variable dynamic gain through a self-tuning mechanism. A self-tuning fuzzy logic controller is designed to reduce the vibrations of the crane structure. The simulated system has a five degrees-of-freedom and modeled system was simulated against the ground motion of the Marmara Kocaeli Earthquake (M _w =7.4) in Turkey on August 17, 1999. At the end of the study, the time history of the crane bridge and portal legs displacements, accelerations, and frequency responses of the both uncontrolled and controlled cases are presented. Additionally, the performance of the designed STFLC is also compared with a PD controller. Simulations of an earthquake excited bridge and portal legs are performed to prove the validity of proposed control strategy.     

Modeling and control of a nonlinear half-vehicle suspension system: a hybrid fuzzy logic approach

Modeling and control of vehicle suspension system are high noteworthy from safety to comfort. In this paper, an analytical nonlinear half-vehicle model which is included quadratic tire stiffness, cubic suspension stiffness, and coulomb friction is derived based on fundamental physics. A hybrid fuzzy logic approach which combines fuzzy logic and PID controllers is designed for reducing the vibration levels of passenger seat and vehicle body. Performances of designed controllers have been evaluated by numerical simulations. Comparisons with classical PID control, Fuzzy Logic Control (FLC) and Hybrid Fuzzy-PID control (HFPID) have also been provided. Results of numerical simulations are evaluated in terms of time histories of displacement and acceleration responses and ride index comparison. A good performance for the Hybrid Fuzzy-PID controller with coupled rules (HFPIDCR) is achieved in simulation studies despite the nonlinearities.     

Sensor less fuzzy control of DC motor

This paper is concerned with the design of the sensorless controller for the position control of DC motor. The DC motor can be modeled as a linear time invariant single input single output system. In this paper synthesis and analysis of position control of a DC motor using sensor less fuzzy control and conventional PID controllers are carried out and their performance is evaluated and compared. The performance of sensor less fuzzy controller is found superior to conventional PID controllers even in the presence of disturbances.     

Output Feedback Modular Adaptive Control of a Nonlinear Prototypical Wing Section

The paper presents nonlinear adaptive control systems for the control of limit cycle oscillations of a prototypical wing section with structural nonlinearities using only output feedback. The chosen model describes the plunge and pitch motion of a wing. The model includes plunge and pitch nonlinearities, and has a single control surface for the purpose of control. Using a canonical representation of the aeroelastic system, a modular output feedback adaptive control system consisting of an input-to-state stabilizing controller and a passive identifier (an observer and adaptation law) is derived. In the closed-loop system, asymptotic stabilization of the pitch and plunge motion is accomplished. Simulation results show that the control system is effective in regulating the state vector to the origin in spite of large parameter uncertainties.     

Fuzzy-approximation-based adaptive control of the chaotic permanent magnet synchronous motor

This paper focus on the problem of position tracking control for the chaotic permanent magnet synchronous motor drive system with parameter uncertainties. Fuzzy logic systems are used to approximate the nonlinearities and the adaptive backstepping technique is employed to construct controllers. The proposed adaptive fuzzy controllers guarantee that the tracking error converges to a small neighborhood of the origin. Compared with the conventional backstepping, the designed fuzzy controllers?? structure is very simple. Simulation results show that the proposed control scheme can suppress chaos of PMSM and guarantee the perfect tracking performance even under the unknown parameters.     

Discrete adaptive fuzzy control for asymptotic tracking of robotic manipulators

This paper presents a novel discrete adaptive fuzzy controller for electrically driven robot manipulators. It addresses how to overcome the nonlinearity, uncertainties, discretizing error and approximation error of the fuzzy system for asymptotic tracking control of robotic manipulators. The proposed controller is model-free in the form of discrete Mamdani fuzzy controller. The parameters of fuzzy controller are adaptively tuned using an adaptive mechanism derived by stability analysis. A robust control term is used to compensate the approximation error of the fuzzy system for asymptotic tracking of a desired trajectory. The controller is robust against all uncertainties associated with the robot manipulator and actuators. It is easy to implement since it requires only the joint position feedback. Compared with fuzzy controllers which employ all states to guarantee stability, the proposed controller is very simpler. Stability analysis and simulation results show its efficiency in the tracking control.     

Passivity-based control for a flexible spacecraft in the presence of disturbances

The attitude regulation control problem for flexible spacecraft is investigated in this paper. Two extended PD+variable structure controllers are proposed using passivity-based control technique instead of sliding mode control approach. The first controller is a basic one, while the second one is an extension of the first one which relaxes the bound requirement for the external disturbances. In the presence of model uncertainties and external disturbances, both controllers presented in this research can make the flexible spacecraft UGAS (uniformly globally asymptotically stable). By virtue of related analysis tools, stability of the proposed controllers is proven theoretically. Numerical simulations are also included to demonstrate the performance of the developed controllers.     

Adaptive neural network-based saturated control of robotic exoskeletons

In this paper, novel adaptive neural network (NN) controllers with input saturation are presented for n-link robotic exoskeletons. The controllers consist of a state feedback controller and an output feedback controller. Through utilizing auxiliary dynamics, the controllers provide a new framework for input saturated control of these robotic systems which can feature the global stability for state feedback control. To compensate for the unknown dynamics of the system, adaptive schemes based on NNs are exploited. Furthermore, adaptive robust terms are utilized to deal with unknown external disturbances. Stability studies show that the closed-loop system is globally uniformly ultimately bounded (UUB) with the state feedback controller, where the global property of the NN-based controller is achieved exploiting a smooth switching function and a robust control term. Also, the system is semi-globally UUB with the output feedback controller. Effectiveness of the controllers is validated by simulations and experimental tests.     

Simulation and hybrid fuzzy-PID control for positioning of a hydraulic system

Accuracy and precision of position control of hydraulic systems are key parameters for engineering applications in order to set more economical and quality systems. In this context, this paper presents modeling and position control of a hydraulic actuation system consisting of an asymmetric hydraulic cylinder driven by a four way, three position proportional valve. In this system model, the bulk modulus is considered as a variable. In addition, the Hybrid Fuzzy-PID Controller with Coupled Rules (HFPIDCR) is proposed for position control of the hydraulic system and its performance is tested by simulation studies. The novel aspect of this controller is to combine fuzzy logic and PID controllers in terms of a switching condition. Simulation results of the HFPIDCR based controller are compared with the results of classical PID, Fuzzy Logic Controller (FLC), and Hybrid Fuzzy-PID controller (HFPID). As a result, it is demonstrated that Hybrid Fuzzy PID Controller with Coupled Rules is more effective than other controllers.     

Active disturbance rejection adaptive control of uncertain nonlinear systems: theory and application

This paper proposes an active disturbance rejection adaptive controller for tracking control of a class of uncertain nonlinear systems with consideration of both parametric uncertainties and uncertain nonlinearities by effectively integrating adaptive control with extended state observer via backstepping method. Parametric uncertainties are handled by the synthesized adaptive law and the remaining uncertainties are estimated by extended state observer and then compensated in a feedforward way. Moreover, both matched uncertainties and unmatched uncertainties can be estimated by constructing an extended state observer for each channel of the considered nonlinear plant. Since parametric uncertainties can be reduced by parameter adaptation, the learning burden of extended state observer is much reduced. Consequently, high-gain feedback is avoided and improved tracking performance can be expected. The proposed controller theoretically guarantees a prescribed transient tracking performance and final tracking accuracy in general while achieving asymptotic tracking when the uncertain nonlinearities are not time-variant. The motion control of a motor-driven robot manipulator is investigated as an application example with some suitable modifications and improvements, and comparative simulation results are obtained to verify the high tracking performance nature of the proposed control strategy.     

海洋平台地震响应的H∞控制

提出了将H_∞控制及平衡降阶法应用于结构主动控制的新方法.该方法首先利用平衡降阶法对结构进行降阶,然后利用降阶模型构造出H_∞控制器和H_∞观测器对结构进行控制;同时结合复模态理论和虚拟激励法,给出了系统分析的有效途径.本文最后以海洋平台地震响应的ATMD主动控制为例,验证了本文方法的有效性.     

Stochastic seismic response of long-span structures

In this paper, dynamic responses of long-span structures subjected to the action of earthquake with realistic wave speed are analysed. The horizontal or vertical ground motion due to earthquakes is assumed to be a stationary stochastic process, and the seismic waves travel along a horizontal straight line. Expressions for calculating the psd(power spectral density) matrices of structural displacements and internal forces are derived based on three dimensional FEM structural models with the ground motion phase-lags taken into account. A numerical example is given which shows that it is of great importance to consider the effect of the ground motion phase-lags for long-span structures.This work was supported by the National Natural Science Foundation of China.     

Evolutionary algorithm-based PID controller tuning for nonlinear quarter-car electrohydraulic vehicle suspensions

The basic challenge associated with the design of vehicle suspension system is the attainment of an optimal trade-off between the various design objectives. This study presents the design of proportional-integral-derivative (PID) controller for a quarter-car active vehicle suspension system (AVSS) using evolutionary algorithms (EA) such as the particle swarm optimization (PSO), genetic algorithm (GA) and differential evolution (DE). Each of the EA-based PID controllers showed overall improvement in suspension travel, ride comfort, settling time and road holding from the manually tuned controller and the passive vehicle suspension system. These improvements were, however, achieved at the cost of increased actuator force, power consumption and spool-valve displacement. DE-optimized PID control resulted in the best minimized suspension performance, followed by the GA and PSO, respectively. Frequency-domain analysis showed that all the signals were attenuated within the whole body vibration frequency range and the EA-optimized controllers had RMS frequency weighted body acceleration of the vehicle within allowable limits for vibration exposure. Robustness analysis of the DE-optimized PID-controlled AVSS to model uncertainties is carried out in the form of variation in vehicle sprung mass loading, tyre stiffness and speed.     

Active vortex-induced vibration control of a circular cylinder at low Reynolds numbers using an adaptive fuzzy sliding mode controller

An adaptive fuzzy sliding mode control (AFSMC) scheme is applied to actively suppress the two-dimensional vortex-induced vibrations (VIV) of an elastically mounted circular cylinder, free to move in in-line and cross-flow directions. Laminar flow regime at Re=90, low non-dimensional mass with equal natural frequencies in both directions, and zero structural damping coefficients, are considered. The natural oscillator frequency is matched with the vortex shedding frequency of a stationary cylinder at Re=100. The strongly coupled unsteady fluid/cylinder interactions are captured by implementing the moving mesh technology through integration of an in-house developed User Define Function (UDF) into the main code of the commercial CFD solver Fluent. The AFSMC approach comprises of a fuzzy system designed to mimic an ideal sliding-mode controller, and a robust controller intended to compensate for the difference between the fuzzy controller and the ideal one. The fuzzy system parameters as well as the uncertainty bound of the robust controller are adaptively tuned online. A collaborative simulation scheme is realized by coupling the control model implemented in Matlab/Simulink to the plant model constructed in Fluent, aiming at determination of the transverse control force required for complete suppression of the cylinder streamwise and cross-flow oscillations. The simulation results demonstrate the high performance and effectiveness of the adopted control algorithm in attenuating the 2D-VIV of the elastic cylinder over a certain flow velocity range. Also, the enhanced transient performance of the AFSM control strategy in comparison with a conventional PID control law is demonstrated. Furthermore, the effect of control action on the time evolution of vortex shedding from the cylinder is discussed. In particular, it is observed that the coalesced vortices in the far wake region of the uncontrolled cylinder, featuring the C(2S)-type vortex shedding characteristic mode, are ultimately forced to switch to the classical von Kármán vortex street of 2S-type mode, displaying wake vortices of moderately weaker strengths very similar to those of the stationary cylinder. Lastly, robustness of AFSMC is verified against relatively large structural uncertainties as well as with respect to a moderate deviation in the uniform inlet flow velocity.     

Modeling and active control of chatter vibrations of piezoelectric stacked machining arm in micro-turning process

Self-excited vibrations known as chatter are considered as the most detrimental issue in micro-turning processes. Occurring unpredictably, they adversely affect the tool life, productivity rate and surface quality of the machining processes. In this paper, a novel machining arm is modeled as a piezoelectric stacked rod which is subjected to a chatter force in the orthogonal micro-turning process. Due to the fact that machining processes are affected by various sources of uncertainties, H_∞ robust control approach is used to suppress the chatter vibrations of the machining arm in the presence of tool wear and dynamic model parameter variations. Also, input control force of the system is provided by exciting the input voltage of piezoelectric layers of the rod. In order to be certain that the designed controller succeeds in suppressing vibrations of the effective structural modes, behavior of the first three modes of vibrations are considered in the final response of the machining arm. In the following, performance of the robust H_∞ controller is compared with a modified PID controller. Simulation results show that the H_∞ controller improves the robustness and performance of the system against uncertainties. The PID controller extends the stability region of the sharp tool and fails to achieve this purpose for the worn tool although its performance is acceptable in suppressing chatter vibrations.

     

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在仿真研究1/4车体二自由度液压半主动悬架的基础上,设计了一种 用于1/2车体的液压半主动悬架的参数自整定模糊PID控制器,并利用模糊控制规则对 PID参数进行在线修改. 以正弦信号路面、脉冲信号路面和C级路面3种典型路面作为输入 信号,应用MATLAB/Simulink控制系统仿真软件对该半主动悬架模型进行的计算机仿真表明, 具有模糊PID控制器的半主动悬架在提高车辆乘坐的舒适性方面要明显优于一般的模糊控制 悬架,具有更好的自适应能力.     

On Fractional PI λ Controllers: Some Tuning Rules for Robustness to Plant Uncertainties

The objective of this work is to find out optimum settings for a fractional PI ^λ controller in order to fulfill three different robustness specifications of design for the compensated system, taking advantage of the fractional order, λ. Since this fractional controller has one parameter more than the conventional PI controller, one more specification can be fulfilled, improving the performance of the system and making it more robust to plant uncertainties, such as gain and time constant changes. For the tuning of the controller an iterative optimization method has been used, based on a nonlinear function minimization. Two real examples of application are presented and simulation results are shown to illustrate the effectiveness of this kind of unconventional controllers.     

High performance fuzzy-Padé controllers: Introduction and comparison to fuzzy controllers

In this paper, a new highly convergent, efficient, and fast response control technique entitled as fuzzy-Padé control method is introduced. It provides a simple methodology to exploit the heuristic knowledge in controlling a system. Fuzzy–Padé controllers originate from a unification of heuristic knowledge expressed as the rule base, and Padé approximants. In this method, fuzzy singleton rules are used to generate the rule base. Accordingly, unknown parameters in the Padé approximant are determined using these rules. The fuzzy-Padé controllers possess certain advantages over fuzzy controllers, and they can be applied in situations where fuzzy controllers previously failed. To demonstrate the effectiveness and robustness of the method, the simulation results for three case studies, the single inverted pendulum, ball and beam, and parallel double inverted pendulum systems are presented. In the case studies, it is shown that the fuzzy-Padé controller has greater convergence region, is quite faster, and its energy consumption is much lower than the fuzzy controller.     

Synchronization of inferior olive neurons via {\mathcal {L}}_1 adaptive feedback

This paper considers the synchronization of inferior olive neurons based on the \({\mathcal {L}}_1\) adaptive control theory. The ION model treated here is the cascade connection of two nonlinear subsystems, termed ZW and UV subsystems. It is assumed that the structure of the nonlinear functions and certain parameters of the IONs are not known, and disturbance inputs are present in the system. First, an \({\mathcal {L}}_1\) adaptive control system is designed to achieve global synchrony of the ZW subsystems using a single control input. This controller can accomplish local synchrony of the UV subsystems if the linearized UV subsystem is exponentially stable. For global synchrony of the UV subsystems, an \({\mathcal {L}}_1\) adaptive control law is designed. Each of these controllers includes a state predictor, an update law, and a control law. In the closed-loop system, global synchrony of the complete models of the IONs (the interconnected ZW and UV subsystems) is accomplished using these two adaptive controllers. Simulations results show that in the closed-loop system, the IONs are synchronized, despite unmodeled nonlinearities, disturbance inputs, and parameter uncertainties in the system.