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.     

Seismic-vibration mitigation of a nonlinear structural system with an ATMD through a fuzzy PID controller

This paper discusses the design of fuzzy PID type controllers (FPIDC) to improve seismic control performance of a nonlinear structural system with an active tuned mass damper (ATMD) against earthquakes. Since structural systems have nonlinearities and uncertainties, fuzzy-based controllers are adequate because of their robust character and satisfactory performance in active structural control. The main advantages of this controller are the ability to handle nonlinearities and uncertainties effectively. In the literature, various structures for fuzzy PID (including PI and PD) controllers have been proposed. In order to obtain proportional, integral and derivative control actions altogether, it is intuitive and convenient to combine PI and PD actions to form a fuzzy PID controller. The simulated system has fifteen degrees of freedom and is modeled using nonlinear behavior of the base–structure interaction. The system is then simulated against the ground motion of the Northridge earthquake (M _w =6.7) in USA on 17 January, 1994. Finally, the time history of the storey displacements, accelerations, ATMD displacements, control voltage and frequency responses of both the uncontrolled and controlled cases are presented. The ground motion recorded of the El-Centro and Kocaeli earthquakes has been used to evaluate the effectiveness of the proposed control algorithm. The robustness of the controller has been checked through the uncertainty in stiffness of the structure. Simulation results exhibit that superior vibration suppression is achieved by the use of designed fuzzy PID type controllers.     

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.     

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.     

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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.     

Load distribution control system design for a semi-track air-cushion vehicle

This paper describes the design principle for a semi-track air-cushion vehicle working on soft terrain. A novel structure, i.e., a flexible joint mechanism is designed for the semi-track air-cushion vehicle suspension system. Focusing on optimizing the total power consumption of the vehicle, three main issues were studied in this paper. First, a theoretical model for minimizing the total power demand of the vehicle is developed. The effects of load distribution on total rolling resistance and total power requirement are calculated which are compared with the prototype experiment data. Second, the optimization procedure is presented. Third, a control scheme is proposed to minimize the power consumption by using a self-tuning PID fuzzy controller and the feasibility was examined by the simulations performed in Matlab/Simulink software environment.     

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.     

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.     

陀螺Fuzzy-PID温度控制系统研究

对于具有大时间延迟环节并难以建立精确数学模型的陀螺温度控制系统,提出采用模糊自整定PID控制参数的Fuzzy-PID陀螺温度控制方法。该方法可以集模糊控制与PID控制之所长,有较好的抗干扰能力。温控及高低温实验证明,该系统可以达到所要求的快速启动、输出稳定并能较好适应工作环境变化等精度要求。     

Suppression of the wing-rock phenomenon using nonlinear controllers

This paper deals with the design of nonlinear controllers for the wing-rock phenomenon of a delta wing aircraft. A fifth order dynamic model is used to describe this phenomenon. A state transformation is introduced such that the transformed dynamic model is in a form which is suitable for a variety of control designs. A feedback linearization control scheme and a sliding-mode control (SMC) scheme are then proposed to suppress wing rock oscillations. It is shown that the two controllers successfully suppress the undesired oscillations and guarantee the asymptotic convergence of all system trajectories to their desired values. The effectiveness of the proposed controllers is verified through simulation studies.

     

A criterion of robustness intelligent nonlinear control for multiple time-delay systems based on fuzzy Lyapunov methods

A control system with state feedback controllers, in which the fuzzy Lyapunov approach is developed for the stability criterion, is studied. The proposed intelligent design provides a systematic and effective framework for the control systems. The global nonlinear controller is constructed based on T–S (Takagi–Sugeno) fuzzy controller design techniques, blending all such local state feedback controllers. Based on this design, the stability conditions of a multiple time-delay system are derived in terms of the fuzzy Lyapunov theory. The effectiveness and the feasibility of the proposed controller design method are demonstrated through numerical simulations.     

Stochastic optimal active control of a half-car nonlinear suspension under random road excitation

The random response analysis and the stochastic optimal active control of a half-car model with nonlinear suspension stiffness and damping traversing a rough road are studied in this paper. The road roughness height is modeled as the output of a first-order linear filter to Gaussian white noise. Considering the hysteretic nonlinear stiffness and the square damping of the vehicle model, the response statistics of the nonlinear suspension with active control are obtained by using the equivalent linearization method. The performance indexes of the active suspension are evaluated and compared with those of the corresponding passive suspension. It is found that the nonlinear active suspension gives a better vehicle performances like ride comfort, suspension stroke and overall performance. Finally, the theoretical results are verified through Monte Carlo simulation.     

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.     

Fuzzy-PID设计及控制性能分析

分析了PID、Fuzzy-PID和FLC（Fuzzy Logic Controller）的相关性和内在联系，介绍了一种由PID参数间接推导出Fuzzy-PID参数的方法。以典型二阶线性系统为例进行了仿真研究，同时利用遗传算法优化控制器参数，并对比分析了Fuzzy-PID和PID、FLC这三种控制器的控制性能，验证了方法的有效性和实用性。     

A fuzzy wavelet neural network-based approach to hypersonic flight vehicle direct nonaffine hybrid control

A direct nonaffine hybrid control methodology is proposed for a generic hypersonic flight models based on fuzzy wavelet neural networks (FWNNs). The addressed strategy extends the previous indirect nonaffine control approaches stemming from simplified models of affine formulations. To cope with nonaffine effects on control design, analytically invertible models are constructed and then novel hybrid controllers are developed directly using nonaffine models. Furthermore, by employing FWNNs to devise adaptive terms, inversion errors are canceled via fuzzy neural approximations. In addition, robust terms are designed to achieve larger stable region in comparison with earlier work using Lyapunov synthesis. Finally, numerical simulation results from a hypersonic flight vehicle model are given to clarify the efficiency of the proposed direct nonaffine control scheme in the presence of parametric uncertainties.     

Nonlinear Stiffness of a Magneto-Rheological Damper

The last decade has witnessed an important role of magneto-rheological dampers in the semi-active vibration control on the basis of empirical models. Those models established by fitting experimental data, however, do not offer any explicit expressions for the stiffness and the damping of magneto-rheological dampers. Hence, it is not easy for engineers to get any intuitive information about the effects of stiffness and damping of a magneto-rheological damper on the dynamic performance of a controlled system. To manifest the nonlinear properties of a magneto-rheological damper, this paper presents the hysteretic phenomena and the additional nonlinear stiffness of a typical magneto-rheological damper in terms of equivalent linear stiffness and equivalent linear damping. Then, it gives a brief discussion about the effect of nonlinear stiffness on the vibration control through the numerical simulations and an experiment for the semi-active suspension of a quarter car model with a magneto-rheological damper installed. Both numerical simulations and experimental results show that the additional nonlinear stiffness in the magneto-rheological damper is remarkable, and should be taken into consideration in the design of vibration control.     

Fuzzy evaluation for an intelligent air-cushion tracked vehicle performance investigation

This paper presents the fuzzy logic expert system (FLES) for an intelligent air-cushion tracked vehicle performance investigation operating on swamp peat terrain. Compared with traditional logic model, fuzzy logic is more efficient in linking the multiple units to a single output and is invaluable supplements to classical hard computing techniques. Therefore, the main purpose of this study is to investigate the relationship between vehicle working parameters and performance characteristics, and to evaluate how fuzzy logic expert system plays an important role in prediction of vehicle performance. Experimental values are taken in the swamp peat terrain for vehicle performance investigation. In this paper, a fuzzy logic expert system model, based on Mamdani approach, is developed to predict the tractive efficiency and power consumption. Verification of the developed fuzzy logic model is carried out through various numerical error criteria. For all parameters, the relative error of predicted values are found to be less than the acceptable limits (10%) and goodness of fit of the predicted values are found to be close to 1.0 as expected and hence shows the good performance of the developed system.     

Comparative research on semi-active control strategies for magneto-rheological suspension

This paper presents the comparison results of a study to identify an appropriate semi-active control algorithm for a MR suspension system from a variety of semi-active control algorithms for use with MR dampers. Five representative control algorithms are considered including the skyhook controller, the hybrid controller, the LQG controller, the sliding mode controller and the fuzzy logic controller. To compare the control performances of the five control algorithms, a quarter car model with a MR damper is adopted as the baseline model for our analysis. After deriving the governing motion equations of the proposed dynamic model, five controllers are developed. Then each control policy is applied to the baseline model equipped with a MR damper. The performances of each control algorithm under various road conditions are compared along with the equivalent passive model in both time and frequency domains through the numerical simulation. Subsequently, a road test is performed to validate the actual control performance. The results show that the performance of a MR suspension system is highly dependent on the choice of algorithm employed, and the sliding mode control strategy exhibits an excellent integrated performance.     

Effectiveness evaluation of hydro-pneumatic and semi-active cab suspension for the improvement of ride comfort of agricultural tractors

Advances have been made to agricultural tractors to improve their ride comfort. However, the ride comfort of tractors is relatively low compared to that of passenger vehicles. Many researchers have developed various types of suspension for tractors. While most studies have focused on the geometry of the suspension, few studies have been carried out on the development of a control algorithm for tractor suspension.In this paper, to improve the ride comfort of an agricultural tractor, a hydro-pneumatic suspension model with a semi-active suspension control is developed with computer simulation, and the effectiveness of the suspension is evaluated before the vehicle is equipped with the suspension and placed into production.An optimal control algorithm for the semi-active suspension of the tractor is developed using a linear quadratic Gaussian. In the simulation, a hydro-pneumatic suspension system model is developed using SimulationX and is applied to a full vehicle model using MATLAB/Simulink. The suspension is assessed by experiments and simulations. The ride comfort using the ride comfort index according to ISO 2631 is evaluated by comparing a vehicle with a passive cab suspension to that with a hydro-pneumatic suspension applied with the semi-active control.