Abstract:

For the strong nonlinear coupling between the level control and product density control loops of the forced-circulation evaporation system, a kind of linear time-invariant active disturbance rejection decoupling control based on particle swarm optimization is proposed.First, two virtual control variables are introduced to transform the system into two single-input-single-output subsystems, and a reduced-order extended state observer is designed for each loop of the system.Then two proportional controllers are employed to control the approximate integrators.At last, the time-invariant coupling matrix of the controller and the proportional gains are obtained by using particle swarm optimization in the possible operation envelope.Therefore, the dynamic coupling part is estimated and compensated by the observer, so the dependency of the controller on the refined mathematical model can be reduced considerably.The constant control gain matrix is optimized and there is no need to measure the temperature of the product.Therefore, the temperature sensor can be removed.These improvements can enhance reliability and the implementation is readily done by applying time-invariant control strategy.Simulation results show that the proposed method can not only decouple the loops effectively but also ensure performance robustness under external disturbances.

Key words: model, optimization, active disturbance rejection control, decoupling control, particle swarm optimization, computer simulation

摘要：

针对强制循环蒸发系统液位与出料密度两个回路的非线性耦合问题,提出了一种基于粒子群算法的线性定常自抗扰解耦控制设计。首先通过引入虚拟控制量,将对象解耦配置为两个单输入单输出子系统,并对每个回路设计降维线性扩张状态观测器。随后,对观测器动态线性化得到的近似积分器环节进行比例控制。最后,在可能的大工况内通过粒子群算法优化控制增益耦合矩阵和比例增益。该算法使用观测器估计并补偿动态耦合部分,降低了控制器对数学模型的依赖程度;使用粒子群算法优化定常控制增益矩阵,避免了实时测量出料温度,降低了对传感测量的要求,提高了可靠性并降低了实施难度。数学仿真结果表明该算法能有效地消除液位回路和出料密度回路的耦合作用,在大工况内具有很强的鲁棒性。

关键词: 模型, 优化, 自抗扰控制, 解耦控制, 粒子群算法, 计算机模拟