共查询到20条相似文献,搜索用时 15 毫秒
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This paper proposes a sliding mode controller with fuzzy adaptive perturbation compensator (FAPC) to get a good control performance
and reduce the chatter. The proposed algorithm can reduce the chattering because the proposed fuzzy adaptive perturbation
compensator compensates the perturbation terms. The compensator computes the control input for compensating unmodeled dynamic
terms and disturbance by using the observer-based fuzzy adaptive network (FAN). The weighting parameters of the compensator
are updated by on-line adaptive scheme in order to minimize the estimation error and the estimation velocity error of each
actuator. Therefore, the combination of sliding mode control and fuzzy adaptive network gives the robust and intelligent routine
to get a good control performance. To evaluate the control performance of the proposed approach, tracking control is experimentally
carried out for the hydraulic motion platform which consists of a 6-DOF parallel manipulator. 相似文献
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L. Zhu Dr D. Toncich R. Nagarajah K. Romanski 《The International Journal of Advanced Manufacturing Technology》1997,13(10):696-707
This paper introduces a PID-like fuzzy controller model, which consists of only five fuzzy rules. Each fuzzy rule is designed to carry out a single control task. A self-learning procedure is used to determine the input scale factor for auto-tuning the system. A new performance criterion is suggested as an object function for the auto-tuning procedure. The features of this fuzzy controller, used in position control applications, are demonstrated by the simulation results of two different types of plants — a d.c. motor and an inverted pendulum.Nomenclature
adjusting parameter of AIAE
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C
I
integral control constant in ruleR
I
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C
L
leading control constant in ruleR
zn
andR
zp
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C
P
proportional control constant in ruleR
P
andR
N
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D
ZE
domain of membership function
ZE
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K
a
adaptive adjusting constant ofC
L
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K
H
adjusting parameter for high-border of dynamic domain space
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K
L
adjusting parameter for low-border of dynamic domain space
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P
R
ramp input command
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P
S
step input command
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S
de
scaling factor for input variable de(change of error)
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S
e
scaling factor for input variablee(error)
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S
o
controller output scaling factor
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U
max
maximum output limit of fuzzy controller 相似文献
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Adaptive backstepping fault-tolerant control for flexible spacecraft with unknown bounded disturbances and actuator failures 总被引:2,自引:0,他引:2
In this paper, a robust adaptive fault-tolerant control approach to attitude tracking of flexible spacecraft is proposed for use in situations when there are reaction wheel/actuator failures, persistent bounded disturbances and unknown inertia parameter uncertainties. The controller is designed based on an adaptive backstepping sliding mode control scheme, and a sufficient condition under which this control law can render the system semi-globally input-to-state stable is also provided such that the closed-loop system is robust with respect to any disturbance within a quantifiable restriction on the amplitude, as well as the set of initial conditions, if the control gains are designed appropriately. Moreover, in the design, the control law does not need a fault detection and isolation mechanism even if the failure time instants, patterns and values on actuator failures are also unknown for the designers, as motivated from a practical spacecraft control application. In addition to detailed derivations of the new controller design and a rigorous sketch of all the associated stability and attitude error convergence proofs, illustrative simulation results of an application to flexible spacecraft show that high precise attitude control and vibration suppression are successfully achieved using various scenarios of controlling effective failures. 相似文献
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柔性机械手具有双时标特性,现有控制策略中需要对电机转角及机械臂转角的状态反馈,增加了控制策略的复杂性.建立了柔性关节机械手动力学模型,针对目前控制策略存在的算法复杂问题,提出了基于输入整形技术的柔性关节机械手运动控制策略.以电机转角作为反馈,根据机械手末端输出与目标输入之间的传递函数,设计了脉冲序列,通过与目标轨迹的卷积进行整形,可以实现轨迹跟踪.通过仿真实例表明,通过对目标轨迹的整形,能够有效减小超调和残余振动,具有一定的可行性. 相似文献
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We develop a novel adaptive tuning method for classical proportional–integral–derivative (PID) controller to control nonlinear processes to adjust PID gains, a problem which is very difficult to overcome in the classical PID controllers. By incorporating classical PID control, which is well-known in industry, to the control of nonlinear processes, we introduce a method which can readily be used by the industry. In this method, controller design does not require a first principal model of the process which is usually very difficult to obtain. Instead, it depends on a fuzzy process model which is constructed from the measured input–output data of the process. A soft limiter is used to impose industrial limits on the control input. The performance of the system is successfully tested on the bioreactor, a highly nonlinear process involving instabilities. Several tests showed the method's success in tracking, robustness to noise, and adaptation properties. We as well compared our system's performance to those of a plant with altered parameters with measurement noise, and obtained less ringing and better tracking. To conclude, we present a novel adaptive control method that is built upon the well-known PID architecture that successfully controls highly nonlinear industrial processes, even under conditions such as strong parameter variations, noise, and instabilities. 相似文献
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This paper presents a unique approach for active vibration control of a one-link flexible manipulator. The method combines a finite element model of the manipulator and an advanced model predictive controller to suppress vibration at its tip. This hybrid methodology improves significantly over the standard application of a predictive controller for vibration control. The finite element model used in place of standard modelling in the control algorithm provides a more accurate prediction of dynamic behavior, resulting in enhanced control. Closed loop control experiments were performed using the flexible manipulator, instrumented with strain gauges and piezoelectric actuators. In all instances, experimental and simulation results demonstrate that the finite element based predictive controller provides improved active vibration suppression in comparison with using a standard predictive control strategy. 相似文献
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针对梭式窑温度控制过程存在非线性、时变性和不确定性等情况,设计了基于模糊神经网络的自适应控制(MRAC)系统并运用于梭式窑中,即采用RBF径向基网络作为梭式窑温度对象的辨识网络,它产生的Jacobin信息与控制误差一起提供给模糊神经网络控制器作为其学习信号,经过MATLAB仿真调整初始参数。最后运用VC++软件结合数据采集卡对燃气梭式窑进行控制。该控制系统能辨识出梭式窑时变性、非线性、长滞后性的对象特性,实时修正控制器参数,以适应对象特性的变化,在实际应用中取得了良好的控制效果。 相似文献
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In this study, an adaptive fuzzy prescribed performance control approach is developed for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems with unknown control direction and unknown dead-zone inputs. The properties of symmetric matrix are exploited to design adaptive fuzzy prescribed performance controller, and a Nussbaum-type function is incorporated in the controller to estimate the unknown control direction. This method has two prominent advantages: it does not require the priori knowledge of control direction and only three parameters need to be updated on-line for this MIMO systems. It is proved that all the signals in the resulting closed-loop system are bounded and that the tracking errors converge to a small residual set with the prescribed performance bounds. The effectiveness of the proposed approach is validated by simulation results. 相似文献
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提出一种基于参考模型的复合模糊控制方法,它把主模糊控制器与基于参考模型的逆模糊控制器进行复合,构成复合模糊控制器,主、逆模糊控制器输出构成合成控制量。并把该方法用于航空发动机控制,通过让被控制量逼近参考模型性能,实现对低压转子转速的无静差控制与基本模糊控制相比,控制性能改善较大,供油量变化物理可实现。仿真结果证明了该方法的有效性。 相似文献
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一种新的模糊神经网络及在化工过程控制系统的应用研究 总被引:2,自引:0,他引:2
本文提出一种新的采用补偿模糊算子的神经网络,它使控制系统具有更强的适应性和鲁棒性。该系统不仅能够自适应地调整隶属度函数。而且能够动态优化模糊规则,将其应用于化学反应器(CSTR)的控制中。仿真实验表明该网络的良好性能。 相似文献
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M. H. Korayem S. E. Farahmandpour S. A. Hashemi 《The International Journal of Advanced Manufacturing Technology》2006,30(3-4):357-368
Application of a numerical method to determine the maximum dynamic load carrying capacity (DLCC) for a robotic manipulator carrying an automobile petrol tank with joint elasticity subject to accuracy and actuator constraints is described in this paper. The maximum DLCC which can be achieved by a manipulator during a given trajectory is limited by a number of factors. The most important of which are the dynamic specification of the manipulator, the actuator limitations, and the elasticity of the joints such as reducers and servo drive system. Initially, the kinematic equations for carrying the automobile petrol tank by the robotic arm with 6 degrees of freedom (DOF) were calculated. The mechanical modeling was achieved via software programming. Dynamic modeling of the flexible joints manipulator was done simply for the three major axes. A method for determination of the dynamic load capacity with specific reference to both accuracy and actuator constraints is explained. The results obtained indicate the importance of both constraints and which constraint is more critical for accuracy and tracking. 相似文献
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为提高智能车辆在高速工况下进行转向换道避撞时的行驶稳定性,设计了一种基于ANFIS及MPC的车辆转向换道控制系统。车辆转向换道控制系统是以模型预测控制(Model Predictive Control, MPC)算法为基础,结合五阶多项式换道路径和最小车距安全模型搭建的;以理想横摆角速度与实际横摆角速度的偏差及其变化率为双输入,利用自适应神经模糊系统(Adaptive Network-based Fuzzy Inference System, ANFIS)规则输出所需的附加横摆力矩,对车轮进行差动制动,以修正车身姿态,实现行车稳定。仿真结果对比表明,此车辆转向换道控制系统可显著提高车辆在高速工况下进行转向换道避撞时的行驶稳定性。 相似文献
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Trong Hieu Bui Jin Ho Suh Sang Bong Kim Tan Tien Nguyen 《Journal of Mechanical Science and Technology》2002,16(12):1613-1626
This paper presents hybrid control of an active suspension system with a full-car model by using H∞ and nonlinear adaptive control methods. The full-car model has seven degrees of freedom including heaving, pitching and rolling
motions. In the active suspension system, the controller shows good performance: small gains from the road disturbances to
the heaving, pitching and rolling accelerations of the car body. Also the controlled system must be robust to system parameter
variations. As the control method, H∞ controller is designed so as to guarantee the robustness of a closed-loop system in the presence of uncertainties and disturbances.
The system parameter variations are taken into account by multiplicative uncertainty model and the system robustness is guaranteed
by small gain theorem. The active system with H∞ controller can reduce the accelerations of the car body in the heaving, pitching and rolling directons. The nonlinearity
of a hydraulic actuator is handled by nonlinear adaptive control based on the back-stepping method. The effectiveness of the
controllers is verified through simulation results in both frequency and time domains. 相似文献
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In the paper, a model predictive controller based on reduced order model is proposed to control belt conveyor system, which is an electro-mechanics complex system with long visco-elastic body. Firstly, in order to design low-degree controller, the balanced truncation method is used for belt conveyor model reduction. Secondly, MPC algorithm based on reduced order model for belt conveyor system is presented. Because of the error bound between the full-order model and reduced order model, two Kalman state estimators are applied in the control scheme to achieve better system performance. Finally, the simulation experiments are shown that balanced truncation method can significantly reduce the model order with high-accuracy and model predictive control based on reduced-model performs well in controlling the belt conveyor system. 相似文献