论文部分内容阅读
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 industrial engineering control still use PID controller, but because of its difficult to obtain precise mathematical model and the nature of its nonlinear time-varying system, traditional PID control is difficult to obtain good control quality, it is difficult to meet the precise control requirements. In order to achieve the desired PID control effect, a PID algorithm based on improved ant colony algorithm optimization tuning algorithm. The algorithm uses the pheromone volatility and pheromone intensity adaptive adjustment mechanism and dynamic update strategy to accelerate the convergence of the optimization algorithm. The algorithm is simple and easy to find the global optimal solution, optimization efficiency and performance improved significantly. Simulation results show that compared with the results of the existing optimization algorithms, the overshoot and adjustment time of the controlled system are significantly reduced, and the dynamic characteristics, robustness and stability are significantly improved, and the validity of the proposed algorithm Feasibility and superiority.