摘要
绝大多数工业工程控制仍然使用PID控制器,但由于它不易获得精确的数学模型和其非线性时变系统的性质,传统PID控制难以获得良好的控制品质、难以满足精确的控制要求。为了使PID控制器达到理想的控制效果,提出了一种基于改进蚁群算法的PID参数优化整定算法。该算法采用了信息素挥发系数和信息素强度自适应调整机制和动态更新策略,用以加速优化算法的收敛。该算法简单易行,更容易找到全局最优解,优化效率和性能明显提高。仿真实验结果表明,同现有的优化算法整定的结果比较,被控系统的超调量、调整时间等明显减少,动态特性、鲁棒性和稳定性等明显提高,进而验证了所设计算法的可行性和优越性。
Most of the industrial process control still uses PID （Proportion Integration Differentiation） controller. However, because the traditional PID controller is time-varying nonlinear system and can＇t acquire accurate model easily, it is difficult to obtain good performance and can＇t meet the precise control requirements. An improved ant colony algorithm （IACA） is proposed for PID parameters optimization in order to attain ideal control effect in this paper. The proposed algorithm uses an adaptive tuning mechanism and a dynamic updating strategy of pheromone intensity and pheromone evaporation coefficient to accelerate algorithm convergence. The control system has better dynamic performance, robustness and more advantages in many aspects such as settling time （ts）, rise time （tr） and peak time （tp） by using IACA. Moreover, the feasibility and superiority of the algorithm is further validated. IACA is simple and easy to find the optimal solution. Secondly, it can improve optimization efficiency and stability. Simulation results show it can reduce the overshoot, ts, tr and tp of the PID control systems, compared with other tuning algorithms.
出处
《计算机与应用化学》
CAS
CSCD
北大核心
2012年第12期1421-1424,共4页
Computers and Applied Chemistry
基金
Supported by the Natural Science Foundation of Anhui province(No.KJ2011Z310)
The Natural Science Foundation of Hefei Normal University(No.2011kj06)~~
关键词
蚁群算法
参数优化
自适应
PID控制
ant colony algorithm, parameter optimization, adaptive, PID control
作者简介
吴剑威（1974-），男，安徽安庆人，讲师，博士研究生，主要研究方向为智能控制和智能算法
联系人：孔慧芳（1964-），女，汉族，安徽合肥人，博士，教授，博士生导师，从事控制理论与控制工程和汽车电子技术等方面的研究E-mail：wujianwei200504@163．com
