Simultaneous stabilization of two discrete-time plants using a2-periodic controller

A generic method for designing a 2-periodic controller for the simultaneous placement of the closed-loop poles of two single-input-single-output discrete shift-invariant plants at the origin is presented. The method consists of first recasting the simultaneous pole-placement problem as one of solving a coupled pair of linear polynomial equations involving three unknown polynomials, and then obtaining the controller parameters in terms of the coefficients of these polynomials. The isolated cases for which such pole placement is not possible have been listed. Simulation results show that the performances of systems thus compensated are superior to their performances when compensated using the higher periodicity controllers suggested in literature     

非连续含有准周期分量时间实例系列的实时监测

本文提出了一种新的线性增长型数字模型选值标准。该标准适合于分析含有准周期分量的时间序列。根据这种新标准选值，尽管时间序列含有随机的倾向变化和准周期分量，线性增长型模型仍可预报该随机过程的期望和倾向。基于双模刑法，本文还提出了一种新的披露微小倾向变化的方法。应用该办法及对阶跃变化和瞬间变化的探测，使我们有可能对含有伪周期分量的非连续时间序列进行实时的检测和预报。     

一类乘积型区间二型模糊控制器的解析结构

区间二型模糊控制器的降型算法需要使用迭代计算,是导致其解析结构推导困难的主要原因.针对乘积型区间二型模糊控制器,本文提出了一种新的解析结构推导方法.区间二型模糊控制器的配置为:三角形输入模糊集,一型输出模糊单值,集合中心法降型器,平均法解模糊器和基于乘积型"与"操作的规则前件.通过对比传统PID控制器的解析结构,证明了区间二型模糊控制器等效于两个PI(或PD)控制器之和.利用KM算法的迭代终止条件,提出了6步骤IC划分法,保证了激活子空间的正确划分.叠加各个子空间,即可得出全局IC划分图.为了避免重复求解符号数学方程,提出了IC边界线的直接定义法,改进了6步骤IC划分法的便利性.本文方法避开了降型算法的迭代计算,可以保证推导出区间二型模糊控制器的闭环解析表达式.     

Influence of meta-heuristic optimization on the performance of adaptive interval type2-fuzzy traffic signal controllers

Intelligent traffic control systems optimized using meta-heuristic algorithms can greatly alleviate traffic congestions in urban areas. Meta-heuristics are broadly used as efficient approaches for complex optimization problems. Comparing the performance of optimization methods on different applications is a way to evaluate their effectiveness. The current literature lacks studies on how performance of traffic signal controllers is affected by utilized optimization algorithms. This paper evaluates the performance of three meta-heuristic optimization methods on an advanced interval type-2 adaptive neuro-fuzzy inference system (IT2ANFIS)-based controller for complex road networks. Simulated annealing (SA), genetic algorithm (GA), and the cuckoo search (CS) are applied for optimal tuning of IT2ANFIS controller. Optimizations methods adjust the parameters in a way to reduce the total travel time of vehicles in the road network. Paramics is used to design and simulate urban traffic network models and implement proposed timing controllers. Comprehensive simulation and performance evaluation are done for both single and multi-intersection traffic networks. Obtained results reveal significant superiority of IT2ANFIS trained using CS method over other controllers. The average performance of the CS-IT2ANFIS is about 31% better than the benchmark fixed-time controllers. This is 17% and only 3% for GA-IT2ANFIS and SA-IT2ANFIS controllers respectively.     

H2 guaranteed cost fuzzy control design for discrete-time nonlinear systems with parameter uncertainty

This paper presents a design method of H₂ guaranteed cost (GC) fuzzy controllers for discrete-time nonlinear systems with parameter uncertainties. The Takagi and Sugeno (T-S) fuzzy model with parameter uncertainties is employed to represent an uncertain discrete-time nonlinear system. A sufficient condition for the existence of H₂ GC fuzzy controllers is presented in terms of linear matrix inequalities (LMIs). The resulting fuzzy controllers not only guarantee that the closed-loop fuzzy system is quadratically stable, but also provide a guaranteed cost on the H₂ performance index. Furthermore, an optimal H₂ GC fuzzy controller in the sense of minimizing a bound on the guaranteed cost is provided by means of an LMI optimization procedure. Finally, it is also demonstrated, through numerical simulations on the backing up control of a truck-trailer, that the proposed design method is effective.     

A new view to Ziegler–Nichols step response tuning method: Analytic non-fragility justification

Recently, exploiting the centroids of stability regions (admissible regions) to be used in tuning two-parameter controllers has been considered as an approach to obtain non-fragile two-parameter controllers. Such an approach can be extended for three-dimensional stability spaces (admissible spaces) by considering the center of mass of these spaces in tuning three-parameter controllers. In this paper, the mentioned approach is used to tune PID controllers for controlling integrator plus dead-time (IPDT) and first order plus dead-time (FOPDT) processes. It is shown that the tuning method resulted from this approach is very similar to the Ziegler–Nichols step response tuning method. Consequently, this paper presents an analytic non-fragility justification for the mentioned tuning method.     

Phase identification in linear time-periodic systems

An identification procedures is developed for a (T=2π)-periodic linear observed system. Cases where C (a real matrix) is diagonizable and not diagonizable are considered     

Gain-scheduled output-feedback controllers depending solely on scheduling parameters via parameter-dependent Lyapunov functions

In this paper, we propose a new design method for Gain-Scheduled Output Feedback (GSOF) controllers for continuous-time Linear Parameter-Varying (LPV) systems via Parameter-Dependent Lyapunov Functions (PDLFs). The GSOF controllers depend solely on scheduling parameters. Although our method requires a line search to obtain suboptimal controllers, it produces practical GSOF controllers, being independent of the derivatives of scheduling parameters. Our method is proved to be no more conservative than conventional design methods via constant Lyapunov functions as well as particularly structured PDLFs.     

Optimization of interval type-2 fuzzy logic controllers using evolutionary algorithms

A method for designing optimal interval type-2 fuzzy logic controllers using evolutionary algorithms is presented in this paper. Interval type-2 fuzzy controllers can outperform conventional type-1 fuzzy controllers when the problem has a high degree of uncertainty. However, designing interval type-2 fuzzy controllers is more difficult because there are more parameters involved. In this paper, interval type-2 fuzzy systems are approximated with the average of two type-1 fuzzy systems, which has been shown to give good results in control if the type-1 fuzzy systems can be obtained appropriately. An evolutionary algorithm is applied to find the optimal interval type-2 fuzzy system as mentioned above. The human evolutionary model is applied for optimizing the interval type-2 fuzzy controller for a particular non-linear plant and results are compared against an optimal type-1 fuzzy controller. A comparative study of simulation results of the type-2 and type-1 fuzzy controllers, under different noise levels, is also presented. Simulation results show that interval type-2 fuzzy controllers obtained with the evolutionary algorithm outperform type-1 fuzzy controllers.     

Low-order stabilizing controllers

A method for designing low-order stabilizing controllers is described. It is shown that for some plants the order of stabilizing controllers may be less than or equal to l (respectively m), where l (respectively m) is the number of plant outputs (respectively inputs). An explicit characterization of a set of low-order stabilizing controllers is given and numerical examples are provided to illustrate the results of the note     

Neurofuzzy network based self-tuning control with offset eliminating

The design of nonlinear controllers involves first selecting the input and then determining the nonlinear functions for the controllers. Since systems described by smooth nonlinear functions can be approximated by linear models in the neighbourhood of the selected operating points, the input of the nonlinear controller at these operating points can be chosen to be identical to those of the local linear controllers. Following this approach, it is proposed that the input of the nonlinear controller are similarly chosen, and that the local linear controllers are designed based on the integrating and k-incremental suboptimal control laws for their ability to remove offsets. Neurofuzzy networks are used to implement the nonlinear controllers for their ability to approximate nonlinear functions with arbitrary accuracy, and to be trained from experimental data. These nonlinear controllers are referred to as neurofuzzy controllers for convenience. As the integrating and k-incremental control laws have also been applied to implement self-tuning controllers, the proposed neurofuzzy controllers can also be interpreted as self-tuning nonlinear controllers. The training target for the neurofuzzy controllers is derived, and online training of the neurofuzzy controllers using a simplified recursive least squares (SRLS) method is presented. It is shown that using the SRLS method, computing time to train the neurofuzzy controllers can be drastically reduced and the ability to track varying dynamics improved. The performance of the neurofuzzy controllers and their ability to remove offsets are demonstrated by two simulation examples involving a linear and a nonlinear system, and a case study involving the control of the drum water level in the boiler of a power generation system.     

一类不确定广义系统的分散容错控制

讨论一类不确定广义系统分散容错控制器设计问题.首先利用线性矩阵不等式(LMI)设计分散状态反馈控制器,使得广义系统执行器未出现故障时渐近稳定;接着针对广义系统的部分执行器出现故障的情况设计分散状态反馈控制器,使得闭环广义系统渐近稳定;进而利用LMI设计广义系统在分散状态反馈作用下具有完整性的容错控制器;同时对传感器故障情形设计了广义系统在分散输出反馈作用下具有完整性的容错控制器,得到了不确定广义系统关于执行器和传感器的分散容错控制器设计的方法.将所设计的控制器用于实际电子网络系统,验证了所提出方法的有效性.     

Tuning of PI controllers with one-way decoupling in 2×2 MIMO systems based on finite frequency response data

A method of tuning for PI controllers with one-way lead/lag decoupling tuning is demonstrated for 2×2 input-output systems, based on finite frequency response data. The frequency response estimates are obtained from closed loop tests using an identification technique based on bandpass filters. The open-loop frequency response is calculated and used to tune PI controllers and to fit lead-lag compensators for decoupling by weighted least-squares. Separate optimization of the PI controllers and the lead-lag compensator is preferred. The tuning takes into account violations of desired multivariable robustness criteria. The method is illustrated by application to a paper machine headbox simulation and by experiments in distillation column temperature control.     

Designs of Bisimilar Petri Net Controllers With Fault Tolerance Capabilities

This paper proposes an approach for providing tolerance against faults that may compromise the functionality of a given controller modeled by a Petri net. The method is based on embedding the given Petri net controller into a larger (redundant) Petri net controller that retains the original functionality and properties, and uses additional places, connections, and tokens to impose invariant conditions that allow the systematic detection and identification of faults via linear parity checks. In particular, this paper considers two types of redundant Petri net controllers: 1) nonseparate redundant Petri net controllers have the same functionality as the given Petri net controller and allow for fault detection and identification, but do not necessarily retain the given controller intact; and 2) separate redundant Petri net controllers are a special case of the nonseparate redundant controllers that retain the given Petri net controller intact but enhance it with additional places to enable fault detection and identification. The work in this paper obtains complete characterizations of both types of redundant controllers along with necessary and sufficient conditions for them to be bisimulation equivalent to the given original Petri net controller. In addition, this paper discusses how each type of redundant controllers can be designed to have desirable fault detection and identification capabilities. When the bisimulation equivalence requirement is not directly enforced, nonseparate redundant controllers can potentially have advantages over separate ones (e.g., they can use fewer connections to detect and identify the same number of faults). An example of a Petri net controller for a production cell and its fault tolerance capabilities using separate and nonseparate embeddings is used to illustrate the approach.     

Analytical structures and analysis of the simplest fuzzy PI controllers

This paper deals with simplest fuzzy PI controllers which employ two fuzzy numbers on the universe of discourse (UOD) of each input variable, and three fuzzy numbers on the UOD of output variable. Analytical structures of such controllers are derived using triangular membership functions for fuzzification, different combinations of T-norms and T-conorms, different inference methods, and center of area (COA) method for defuzzification. Properties of these controllers are investigated. A comparative study is made on (i) the fuzzy PI controllers derived, and (ii) on the fuzzy PI controllers and their counterpart—conventional PI controller. Moreover, sufficient conditions for bounded-input bounded-output (BIBO) stability of fuzzy PI control systems are established using the well-known small gain theorem.     

Simulation of novel hybrid method to improve dynamic responses with PSS and UPFC by fuzzy logic controller

In this paper, a hybrid method is proposed to damp frequency and power oscillations in the power system equipped with unified power flow controller (UPFC) and power system stabilizer (PSS) controllers. The method is robust with respect to operating point’s changes. This hybrid method consists of two stages: offline and online. In the offline stage, the coefficients of PSS and UPFC controllers for different operating points have been found by PSO algorithm; then in the second stage, online new fuzzy controller is proposed to select the best PSS and UPFC coefficients according to operating point. The proposed method is simulated for single machine infinite bus system-associated PSS and UPFC for three different operating points in MATLAB software, and results of proposed method simulation are investigated and compared with conventional PSS (CPSS) + UPFC, CPSS controllers. Simulation results show that the proposed method has a better performance.

     

H∞ strong stabilization

This note presents a technique for designing stable H_∞ controllers. Similar to some methods in the existing literature, the proposed method also uses the parameterization of all suboptimal H _∞ controllers so that the stable H_∞ design problem can be (conservatively) converted into another 2-block standard H_∞ problem. However, a weighting function is introduced in this method to alleviate the conservativeness of the previous formulations. It is further shown that the resulting high-order controller can be significantly reduced by a two-step reduction algorithm. Numerical examples are presented to demonstrate the effectiveness of the proposed method     

A family of robust adaptive excitation controllers for synchronous generators with steam valve via Hamiltonian function method

Using the Hamiltonian function method,this paper proposes a family of robust adaptive excitation controllers for synchronous generators with steam valve control.First,a parameterization method of robus...     

A simple method of tuning series cascade controllers for unstable systems

A simple method is proposed to design P/PI controllers for a series cascade control system for unstable first order plus time-delay （FOPTD） systems. In this paper, the controller design for unstable FOPTD systems cascaded in series with stable/unstable FOPTD systems is considered. The proposed method is based on equating the coefficients of corresponding powers of s and s2 in the numerator to α1 and α2 times those of the denominator of the closed-loop transfer function for a servo problem. The open loop system consists of an unstable FOPTD system cascaded in series with a stable/unstable FOPTD system. Only two tuning parameters （α1 and α2） are required for the design of controllers. The closed-loop performances are evaluated for both the servo and regulatory problems and the performances are found to be better than that of the well established synthesis method. The robustness for uncertainty in the model parameters is studied and compared with that of the controllers designed by the synthesis method.