A new sliding mode controller for wind turbine pitch angle control

This paper focuses on variable-speed wind turbines where control is aimed at stabilizing the output power. A hybrid control algorithm is proposed which includes a new arrangement of two controllers along with an observer. Estimation of power coefficient via sliding mode observer reduces the amount of errors caused by changing the power coefficient parameter in different turbines. Moreover, the use of this special arrangement of sliding mode controller, proportional-integral (PI) controller and sliding mode observer, removes one of the controller parameter denoting wind speed from the designed algorithm, which in turn eliminates disturbances related to wind speed changes. In order to show the efficiency of the proposed control method, the performances of the controllers are evaluated by simulation in MATLAB software.     

Design of internal model control based fractional order PID controller

This article presents a design of the internal model control(IMC)based single degree of freedom(SDF) fractional order(FO)PID controller with a desired bandwidth specification for a class of fractional order system(FOS). The drawbacks of the SDF FO-IMC are eliminated with the help of the two-degree of freedom(TDF)FO PID controller. The robust stability and robust performance of the designed controller are analyzed using an example.     

Adaptive back-stepping pitch angle control for wind turbine based on a new electro-hydraulic pitch system

A new electro-hydraulic pitch system is proposed to smooth the output power and drive-train torque fluctuations for wind turbine. This new pitch system employs a servo-valve-controlled hydraulic motor to enhance pitch control performances. This pitch system is represented by a state-space model with parametric uncertainties and nonlinearities. An adaptive back-stepping pitch angle controller is synthesised based on this state-space model to accurately achieve the desired pitch angle control regardless of such uncertainties and nonlinearities. This pitch angle controller includes a back-stepping procedure and an adaption law to deal with such uncertainties and nonlinearities and hence to improve the final pitch control performances. The proposed pitch system and the designed pitch angle controller have been validated for achievable and efficient power and torque regulation performances by comparative experimental results under various operating conditions.     

分数阶模糊免疫PID控制器的设计

为改善分数阶PID控制器的控制性能,借鉴整数阶模糊免疫PID控制器,把模糊免疫调节与分数阶PID控制器结合起来,设计了分数阶模糊免疫PID控制器。仿真结果表明了该方法的有效性,不但提高了分数阶PID控制器跟踪性能,而且还具有良好的鲁棒性和抗干扰性。     

一种新型非线性PID控制器

将非线性函数与简单的PID控制器相级联，构成一种新型的非线性PID控制器，以提高现有PID控制器的性能，新型PID控制器的设计过程十分简单，只要适当构造非线性函数，并与原PID控制器级联起来便可实现，数值仿真结果表明，所提出的PID控制器比简单的PID控制器具有更好的动静态性能。     

Sliding mode control design via reduced order model approach

This paper presents a design of continuous-time sliding mode control for the higher order systems via reduced order model.It is shown that a continuous-time sliding mode control designed for the reduced order model gives similar performance for the higher order system.The method is illustrated by numerical examples.The paper also introduces a technique for design of a sliding surface such that the system satisfies a cost-optimality condition when on the sliding surface.     

一种神经网络分数阶PID控制器的实现

为解决分数阶PID控制器参数难于整定的问题,设计了一种基于神经网络的分数阶PID控制器。通过采用反向传播（ BP）神经网络的参数调节策略,可以实现一种五维参数自学习的PID控制器。将分数阶PID控制器数字化,通过BP算法调节神经网络突触权值,经过调整的神经网络输出作为分数阶PID控制器的参数。经过仿真验证,神经网络分数阶PID控制器比传统PID控制器精度提高6倍且控制更加稳定。     

A new design for a PID plus feedforward controller

In this paper, a new design and tuning procedure for a PID plus feedforward controller is proposed. It consists of determining a feedforward signal in order to achieve a predefined process output transition time assuming a first order plus dead time model of the process. Then, the PID parameters are tuned by any conventional method in order to assure a good load disturbance rejection and the reference signal to the closed-loop system is obtained by filtering appropriately the set-point step signal. Simulation and experimental results show that the method outperforms the typical (inverse) model-based approach despite its simplicity and it is therefore suitable to implement in Distributed Control Systems as well as in single-station controllers.     

Conical tank level control using fractional order PID controllers: a simulated and experimental study

In this paper, simulated and experimental results on the conical tank level control are presented. PI/PID controllers of integer order (IO) as well as of fractional order (FO) are studied and compared. The tuning parameters are obtained first by using root locus (RL) and Ziegler and Nichols methods, for comparison purposes. Next, particle swarm optimization (PSO) is employed to determine the optimal controllers'' parameters using as fitness function the integral of the absolute value of tracking error (IAE). From the experimental results it is concluded that PI/FOPI are the controllers presenting the lowest IAE indexes, whereas PID/FOPID controllers present the lowest energy consumption by the control signal.     

基于串级PID控制技术的堆垛机控制器的设计

本文从提高堆垛机作业系统的工作效率和可靠性的角度出发,利用串级控制原理和积分分离的PID算法,建立了堆垛机串级PID变频调速控制系统,避免了速度扰动的影响,实现了堆垛机的快速精确定位控制,提高了系统运行的稳定性和可靠性。     

基于降阶位置/力模型的机器人神经网络控制

双足机器人的双脚支撑期是实现其步行运动的重要过程,然而耦合的位置/力控制难以保证其稳定平滑运动.本文提出了一种基于降阶位置/力模型的机器人控制策略,整合了位置控制子空间模型和力控制子空间模型,通过模型降阶减小了控制器设计的复杂度,并采用神经网络自适应控制方法综合多控制目标,实现了双足机器人的平滑稳定控制并有效地抑制了系统外扰和参数不确定性的影响.最后,仿真算法验证了该控制方法和模型的有效性.     

Impulsive second‐order sliding mode control in reduced information environment

The perturbed system with input‐output dynamics of arbitrary and well‐defined relative degree is considered in a reduced information environment. A novel impulsive second‐order sliding mode control in the reduced information environment is proposed. The almost instantaneous convergence to the origin is achieved via impulsive control acting in a concert with second‐order sliding mode control, specifically supertwisting and twisting algorithms. The impulsive actions are implemented in a piecewise constant format. Numerical examples illustrate the efficiency of the proposed control algorithms.     

Maximum sensitivity based fractional IMC–PID controller design for non-integer order system with time delay

A simple approach with a small number of tuning parameters is a key goal in fractional order controller design. Recently there have been a number of limited attempts to bring about improvements in these areas. In this paper, a new design method for a fractional order PID controller based on internal model control (IMC) is proposed to handle non-integer order systems with time delay. In order to reduce the number of tuning parameters and mitigate the impact of time delay, the fractional order internal model control scheme is used. Considering the robustness of the control system with respect to process variations and model uncertainty, maximum sensitivity is applied to the tuning of the parameters. The resulting controller has the structure of a fractional order PID which is cascaded with a filter. This is named a fractional IMC–PID controller. Numerical results are given to show the efficiency of the proposed controller.     

A genetic-multivariable fractional order PID control to multi-input multi-output processes

A multivariable fractional order PID controller is designed and to get suitable coefficients for the controller, a genetic algorithm with a new topology to generate a new population is proposed. The three parts of the genetic algorithm such as reproduction, mutation, and crossover are employed and some variations in the methods are fulfilled so that a better performance is gained. The genetic algorithm is applied to design FOPID controllers for a multivariable process and the results are compared with the responses of a H_∞ based multivariable FOPID controller. The simulation responses show that in all cases, the genetic-multivariable FOPID controller has suitable performance, and the output of the system has a smaller error. Also, in the proposed method, variations in one output have a smaller effect on another output which is shown the ability of the proposed method to overcome the interaction in the multivariable processes.     

Data-driven dual-rate cascade control and application to pitch angle control of UAV

A data-driven design method for a cascade control system is proposed. The cascade control system consists of inner and outer loops, where the control interval of the outer loop is an integer multiple of the inner loop; hence, the system is a dual-rate system. In the proposed method, controllers in the inner and outer loops are designed based on one-shot data. In such a dual-rate cascade system, since the controllers are designed using different data-rate signals, the lifting technique is applied to align the dual-rate data. To show its effectiveness, the proposed method is compared with a conventional single-rate cascade control method, and numerical simulations and experiments are presented to examine servo and regulation performance.     

Precise control of linear systems subject to actuator saturation using tracking differentiator and reduced order composite nonlinear feedback control

Aiming at the actuator saturation problem and the system performance requirement, this article proposes a new control scheme, i.e. a newly developed tracking differentiator-composite nonlinear feedback (TDCNF) control law, which is the combination of a tracking differentiator (TD) and a reduced order composite nonlinear feedback (CNF) control law. The TD, used here, mainly helps to provide a smooth reference signal and largely avoid actuator saturation. The reduced order CNF control law, on the one hand, estimates those unmeasurable state variables for measurement feedback control and, on the other hand, ensures satisfactory system performance. The stability of the newly developed TDCNF is proved in detail. Finally, to verify the effectiveness of the newly developed TDCNF control law, two illustrative examples are demonstrated and therein a novel design of the proposed control law is given. Simulation results show that the proposed control law can achieve good tracking performance and effectively avoid the actuator saturation.     

Optimum design of fractional order PID controller for AVR system using chaotic ant swarm

Fractional-order PID (FOPID) controller is a generalization of standard PID controller using fractional calculus. Compared to PID controller, the tuning of FOPID is more complex and remains a challenge problem. This paper focuses on the design of FOPID controller using chaotic ant swarm (CAS) optimization method. The tuning of FOPID controller is formulated as a nonlinear optimization problem, in which the objective function is composed of overshoot, steady-state error, raising time and settling time. CAS algorithm, a newly developed evolutionary algorithm inspired by the chaotic behavior of individual ant and the self-organization of ant swarm, is used as the optimizer to search the best parameters of FOPID controller. The designed CAS-FOPID controller is applied to an automatic regulator voltage (AVR) system. Numerous numerical simulations and comparisons with other FOPID/PID controllers show that the CAS-FOPID controller can not only ensure good control performance with respect to reference input but also improve the system robustness with respect to model uncertainties.     

迭代学习在PID控制中的应用

利用迭代学习过程记忆的期望控制、期望轨迹以及跟踪误差,提出了拟合控制系统的PID控制器参数的方法。用这种方法实现的PID控制器结构简单,作用于系统可获得较佳的动态特性和较强的鲁棒性。仿真实例表明了这种方法具有很好的可行性和实用性。     

网络控制系统的自整定PID 控制器设计

结合广义预测控制（GPC）方法和PID反馈结构,设计了一种具有预测功能的PID控制器,PID参数根据未来时刻的预计输出误差进行整定.控制器导出多步控制序列,置于执行器端的延迟补偿器根据网络时延从控制序列中选择控制信息并作用于控制对象,从而对时延进行补偿,使控制性能得到极大改善.控制器结合了PID控制和预测控制的优点,具有较强的鲁棒性和工程意义.最后通过构造Lyapunov函数对闭环系统的稳定性进行了分析,并通过仿真验证了该算法的有效性.     

一阶系统预测PID控制器鲁棒稳定性分析

针对基于DCS预测PID的控制系统,利用Kharitonov定理和边缘理论分析其在参数不确定情况下输入/输出鲁棒稳定性。具体对一阶加纯滞后对象给出了系统保持稳定的最大过程参数区间。仿真结果表明,当过程参数偏离标称值时,该方法能使系统保持很好的鲁棒稳定性。