Comparative performance analysis of artificial bee colony algorithm for automatic voltage regulator (AVR) system

In this study, Artificial Bee Colony (ABC) algorithm is applied to the Automatic Voltage Regulator (AVR) system for obtaining optimal control. The tuning performance of this algorithm and its contribution to the robustness of the control system are also extensively and comparatively investigated. In the performance analysis, Particle Swarm Optimization (PSO) algorithm and Differential Evolution (DE) algorithm are used for the purpose of comparison. These analyses are realized by benefiting from different analysis methods such as transient response analysis, root locus analysis, bode analysis and statistically Receiver Operating Characteristic (ROC) analysis. Afterwards, the robustness analysis is applied to the AVR system, which is tuned by ABC algorithm in order to determine its response to changes in the system parameters. At the end of the study, it is shown that the ABC algorithm is successfully applied to the AVR system for improving the performance of the controller and shows a better tuning capability than the other similar population based optimization algorithms for this control application.     

Design of PID controller based on a self-adaptive state-space predictive functional control using extremal optimization method

In proportional-integral-derivative (PID) controller design, obtaining high stability and desired closed-loop response are of great importance for system engineers. Most existing methodologies, which have validated their excellent control performance on the accurate mathematical model, face significant difficulties in the unavoidable model mismatches and disturbance. To overcome these drawbacks, this paper proposes a self-adaptive state-space predictive functional control (APFC) based on extremal optimization method to design PID controller called EO-APFC-PID, wherein, the self-adaptive means, i.e., a forgetting factor recursive least squares (FFRLS) mechanism is embedded into state-space predictive functional control (PFC), and the proposed EO is exploited to alleviate the challenging problem that the elements in weighting factors of APFC technique are lacking analytical knowledge. The performance of the proposed EO-APFC-PID control scheme is demonstrated and compared with one classic PID tuning method and two state-of-the-art control strategies on the chamber pressure control for a coke furnace. The experimental results fully illustrate that the proposed method is more effective and efficient than other existing control strategies for achieving a desired behavior on the most test cases considered in this paper in terms of set point tracking, input disturbance rejection and output disturbance rejection.     

A novel performance criterion approach to optimum design of PID controller using cuckoo search algorithm for AVR system

This article presents a novel tuning design of Proportional-Integral-Derivative (PID) controller in the Automatic Voltage Regulator (AVR) system by using Cuckoo Search (CS) algorithm with a new time domain performance criterion. This performance criterion was chosen to minimize the maximum overshoot, rise time, settling time and steady state error of the terminal voltage. In order to compare CS with other evolutionary algorithms, the proposed objective function was used in Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) algorithms for PID design of the AVR system. The performance of the proposed CS based PID controller was compared to the PID controllers tuned by the different evolutionary algorithms using various objective functions proposed in the literature. Dynamic response and a frequency response of the proposed CS based PID controller were examined in detail. Moreover, the disturbance rejection and robustness performance of the tuned controller against parametric uncertainties were obtained, separately. Energy consumptions of the proposed PID controller and the PID controllers tuned by the PSO and ABC algorithms were analyzed thoroughly. Extensive simulation results demonstrate that the CS based PID controller has better control performance in comparison with other PID controllers tuned by the PSO and ABC algorithms. Furthermore, the proposed objective function remarkably improves the PID tuning optimization technique.     

Design of optimal PID controller for multivariable time-varying delay discrete-time systems using non-monotonic Lyapunov-Krasovskii approach

This paper is concerned with stability analysis and stabilization of time-varying delay discrete-time systems in Lyapunov-Krasovskii stability analysis framework. In this regard, a less conservative approach is introduced based on non-monotonic Lyapunov-Krasovskii (NMLK) technique. The proposed method derives time-varying delay dependent stability conditions based on Lyapunov-Krasovskii functional (LKF), which are in the form of linear matrix inequalities (LMI). Also, a PID controller designing algorithm is extracted based on obtained NMLK stability condition. The stability of the closed loop system is guaranteed using the designed controller. Another property that is important along with the stability, is the optimality of the controller. Thus, an optimal PID designing technique is introduced in this article. The proposed method can be used to design optimal PID controller for unstable multi-input multi-output time-varying delay discrete-time systems. The proposed stability and stabilization conditions are less conservative due to the use of non-monotonic decreasing technique. The novelty of the paper comes from the consideration of non-monotonic approach for stability analysis of time-varying delay discrete-time systems and using obtained stability conditions for designing PID controller. Numerical examples and simulations are given to evaluate the theoretical results and illustrate its effectiveness compared to the existing methods.     

Design of automatic climbing controller for large civil aircraft

This paper focuses on automatic climbing control methods for large civil aircraft. The key technique is how to design automatic flight control laws that meet the requirements of flight performance indexes and have good characteristics of restraining various disturbances. The classical engineering methods are used to solve the above problem. Based on the aerodynamic data of Boeing707, a nonlinear model of large civil aircraft is established. Linear models which are divided into longitudinal and lateral equations are obtained by trim and linearization. The design of longitudinal control laws uses C^? criterion, three climbing schemes including pitch control mode, vertical velocity control mode and altitude control mode are designed and mutually compared. For lateral control problem, by the feedback angle of sideslip, the bank attitude control with good effect is achieved. The simulation results indicate the designed control laws can meet the requirements of performance indexes, and have satisfied characteristics of anti-gust disturbance.     

H∞ tracking control for nonlinear multivariable systems using wavelet-type TSK fuzzy brain emotional learning with particle swarm optimization

This paper studies the ${\mathit{H}}_{\infty }$ tracking control for uncertain nonlinear multivariable systems. We propose a control strategy, which combines the adaptive wavelet-type Takagi-Sugeno-Kang (TSK) fuzzy brain emotional learning controller (WTFBELC) and the $H_{\infty }$ robust tracking compensator. As for the adaptive WTFBELC, it is a main controller designed to mimic the ideal controller. The proposed WTFBELC is to obtain much better ability of handling nonlinearities and uncertainties, but the proposed $H_{\infty }$ robust tracking compensator is to compensate the residual error between the adaptive WTFBELC and the ideal controller. Furthermore, the optimal learning rates of the adaptive WTFBELC are searched quickly by using the particle swarm optimization (PSO) algorithm, and the parameter updated laws are derived based on the steepest descent gradient method. The robust tracking performance of this novel control scheme is guaranteed based on Lyapunov stability theory. The mass-spring-damper mechanical system and the three-link robot manipulator, are used to verify the effectiveness of the proposed adaptive PSO-WTFBELC $H_{\infty }$ control scheme.     

Parameter estimation of an unstable system with a PID controller in a closed loop configuration

An essential part of the auto-tuning control involves parameter estimation of a suitable low order model. Since a common way to control an unstable system is via a PID controller, there is a growing interest in the application of new PID-based algorithms for the identification task. In this light the relative advantages of two recently published methods are investigated. The first method is based on typical data of the reaction curve and the time delay is measured directly from the initial portion of the curve. The second method utilizes a least-squares algorithm to get an equivalent time delay together with the values of the other parameters. Thus, the obtained time delay approximates not only the true delay but also part of the nonlinear and the higher order dynamics. This is an advantage when a PID auto-tuning is sought. Two examples are provided to demonstrate and compare between the results of the methods.     

自适应粒子群算法在水库优化调度中的应用研究

针对传统粒子群算法在求解梯级水库调度问题时,容易陷入局部最优而早熟收敛的问题,提出自适应粒子群算法。该改进算法结合种群进化程度自适应调整算法控制参数,从而克服传统粒子群算法参数固定引起的搜索能力不足的问题。同时,采用种群局部重建策略解决种群进化后期多样性下降的问题。将改进的粒子群算法应用于清江梯级水电站的发电调度求解,模拟计算结果表明,文章提出的改进算法具有较强的全局寻优能力,可以进一步提高算法的搜索性能和求解精度。     

An optimization methodology of susceptance variation using lead-lag controller for grid connected FSIG based wind generator system

In wind power system, low frequency oscillations are observed due to imbalance between mechanical input and electrical output. Hence, variable susceptance controllers are being adopted to mitigate these oscillations. However, improper modulation of control parameters also leads to system instability. Therefore, we propose an optimization methodology for mitigating low frequency oscillations in wind power generation system. To visualize our methodology, we use a lead-lag type variable susceptance controller for fixed speed induction generator (FSIG) based wind generation system. Then, we optimize gain and time constants of lead-lag controller using three optimization algorithms: particle swarm optimization (PSO), genetic algorithm (GA), and flower pollination algorithm (FPA). Later, we perform non-linear time domain simulation and quantitative analysis to find average fitness, standard deviation, run time, and iteration number for these optimization algorithms. Moreover, non-parametric statistical analysis, such as Kolmogorov–Smirnov and Wilcoxon signed-rank tests are employed for identifying statistically significant differences among these algorithms.     

The optimal event-triggered impulsive control of a stochastic rumor spreading model incorporating time delay using the particle swarm optimization algorithm

In the digital age, rumor spreading is becoming more widespread and faster than ever before, and results in the more social panic and instability. Because of this, it is crucial to implement effective control strategies to prevent the continued spread of rumors, and avoid all kinds of unnecessary harm caused by rumors. In this paper, a stochastic rumor spreading model incorporating time delay within the framework of the event-triggered impulsive control (ETIC) strategies are presented. To begin with, the stability problem of this model is discussed and proved. Besides, the optimal ETIC strategies are explored by the particle swarm optimization (PSO) algorithm. Furthermore, some numerical simulations are performed to illustrate the optimal ETIC strategies of the given model. In addition, a real case is used to prove the validity of given model. Finally, the following conclusions are drawn that the stochastic model is feasible and consistent with actual rumor propagation trends, and ETIC strategies can help control rumors effectively. Meanwhile, different ETIC strategies should be used according to the different situations of rumor spreading. For instance, control strategies need to be more frequent and robust when transmission rates are higher or time delay are shorter.     

Robust trajectory tracking control of non-holonomic wheeled mobile robots using an adaptive fractional order parallel fuzzy PID controller

Non-holonomic wheeled mobile robots (WMRs) are highly uncertain, multi-input multi-output (MIMO), non-linear dynamic systems that are expected to perform under varying environment and structural reservations. An Adaptive Fractional Order Parallel Fuzzy Proportional-Integral-Derivative (AFO?PFPID) controller is proposed and investigated on WMR to meet the above challenges. Computer simulations were carried out under the effects of dynamic parameter variations, noise, forced displacement, time delay, and uncertainty in the pose to thoroughly assess the controller's performance. Further, to evaluate its relative assessment, the AFO?PFPID controller's performance is compared with its integer counterpart Adaptive Integer Order Parallel Fuzzy Proportional-Integral-Derivative (AIO?PFPID) controller. Both the controllers were tuned with the Multi-Objective Grey Wolf Optimization Algorithm to minimize the positional and velocity profile errors with an overall goal to attain effective trajectory tracking. Though both the controllers effectively performed tracking goals, the AFO?PFPID controller has offered a significantly robust performance even under the model uncertainties and disturbances. Therefore, based on the presented investigations, it is concluded that the AFO?PFPID controller is a superior control technique for non-holonomic WMRs trajectory tracking application.     

Variable-structure PD controller for satellite attitude: Stability analysis and design for optimal performance

A novel variable structure controller is investigated for satellite attitude control. This novel controller does not lead to a sliding mode, which avoids the chattering problem, making it suitable for practical implementation. Detailed formulation of the controller is presented along with analytical stability analysis for a second order system. The system having this nonlinear controller is homogeneous, which leads to a similar response at large and small deviations from the equilibrium. A procedure for tuning homogeneous controllers for all initial conditions is proposed. A detailed model of the satellite attitude dynamics, actuator dynamics, and delays in the system is utilized to optimize controller gains numerically. A comparative analysis shows the superiority of the proposed controller over a conventional PID controller in terms of better transients and lower energy consumption.     

增强自动烹饪机器人燃气系统安全设计

自动烹饪机器人是近几年在机电、软件、烹饪等相关技术基础上开发出来的自动化设备,通过参照EN298:2012等相关欧洲标准要求,从系统结构和软硬件入手,对其核心的火力控制系统进行安全设计改进,有效的提升了烹饪机器人的安全水平。     

Optimal location and controller design of STATCOM for power system stability improvement using PSO

The optimal location of a static synchronous compensator (STATCOM) and its coordinated design with power system stabilizers (PSSs) for power system stability improvement are presented in this paper. First, the location of STATCOM to improve transient stability is formulated as an optimization problem and particle swarm optimization (PSO) is employed to search for its optimal location. Then, coordinated design problem of STATCOM-based controller with multiple PSS is formulated as an optimization problem and optimal controller parameters are obtained using PSO. A two-area test system is used to show the effectiveness of the proposed approach for determining the optimal location and controller parameters for power system stability improvement. The nonlinear simulation results show that optimally located STATCOM improves the transient stability and coordinated design of STATCOM-based controller and PSSs improve greatly the system damping. Finally, the coordinated design problem is extended to a four-machine two-area system and the results show that the inter-area and local modes of oscillations are well damped with the proposed PSO-optimized controllers.     

国外汽车自动停车系统的介绍与分析

在汽车拥有量急剧增长和停车空间尤为紧张的今天,自动停车技术将为人们生活带来极大的便利.本文介绍了国外现有自动停车系统的发展概况,并分析自动停车系统的基本结构和应用范围,以供相关技术人员学习和参考.     

跨区域协同创新系统绩效测度与优化研究

现有研究较少从跨区域维度考察协同创新,且在进行协同创新绩效测度的过程中往往忽视了参与各方的协同联系。本研究在明晰跨区域协同创新绩效内涵的基础上,构建跨区域协同创新复合系统,测算区域间协同投入和协同产出,进而采用DEA-Tobit两阶段模型对2013年-2016年间长三角地区和京津冀地区的跨区域协同创新绩效及其关键影响因素进行了实证研究,结果发现：（1）长三角内部各区域间协同创新绩效水平呈阶梯状多元化分布,其中江浙沪各自与皖的协同创新绩效水平高于江浙沪彼此间的协同创新绩效水平,并因地理邻近性表现出一定的差异;（2）京津冀内部各区域间协同创新绩效水平呈极端化分布,京津和京冀协同创新绩效达到很高的水平,而津冀协同创新绩效水平则较低;（3）长三角地区整体协同创新绩效水平高于京津冀地区,无论是技术效率还是和规模效率,京津冀地区相比长三角地区均有较大差距;（4）区域间协同度对于跨区域协同创新绩效具有显著正向影响,地理邻近性也能在一定程度上对跨区域协同创新绩效具有促进作用,而区域间经济发展差距则对跨区域协同创新绩效影响较小。最后提出了提升绩效的优化建议。     

乘用车自动离合器性能实车实验与分析

为了研究乘用车自动离合器起步控制策略,首先,对某款乘用车自动离合器工作原理及其评价指标进行了分析和研究;然后,对该车进行了多工况自动离合器起步性能实车实验;最后,得出该款自动离合器起步控制策略不能满足乘用车舒适性要求的结论。     

开发类科研院所高层管理者年度绩效考核方案设计

借助相关绩效管理理论,首先探讨了开发类科研院所高层管理者年度绩效考核指标体系的设计原则;其次,紧密结合某开发类科研院所实际,采用Delphi法调查提出了从经营业绩、管理业绩、发展业绩三类定量指标进行业绩考核及从综合能力和关联评价两类定性指标进行能力评价而建立的开发类科研院所高层管理者年度绩效评价指标体系;然后,运用隶属度评价方法建立了这五类二级评价指标各自对应的具体三级评价指标;最后,设计出了中高层管理者年度绩效考核模型和具体实施方案。     

Transforming LSA space dimensions into a rubric for an automatic assessment and feedback system

The purpose of this article is to validate, through two empirical studies, a new method for automatic evaluation of written texts, called Inbuilt Rubric, based on the Latent Semantic Analysis (LSA) technique, which constitutes an innovative and distinct turn with respect to LSA application so far. In the first empirical study, evidence of the validity of the method to identify and evaluate the conceptual axes of a text in a sample of 78 summaries by secondary school students is sought. Results show that the proposed method has a significantly higher degree of reliability than classic LSA methods of text evaluation, and displays very high sensitivity to identify which conceptual axes are included or not in each summary. A second study evaluates the method's capacity to interact and provide feedback about quality in a real online system on a sample of 924 discursive texts written by university students. Results show that students improved the quality of their written texts using this system, and also rated the experience very highly. The final conclusion is that this new method opens a very interesting way regarding the role of automatic assessors in the identification of presence/absence and quality of elaboration of relevant conceptual information in texts written by students with lower time costs than the usual LSA-based methods.