1761-L32BWA A-B处理器模块 DCS控制模块

1761-L32BWA A-B处理器模块 DCS控制模块

1761-L32BWA与传统的PID控制不同，基于非参数模型的预测控制算法是通过预测模型预估系统的未来输出的状态，采用滚动优化策略计算当前控制器的输出。根据实施方案的不同，有各种算法，例如，内模控制、模型算法控制、动态矩阵控制等。

目前，实用预测控制算法已引入DCS，例如IDCOM控制算法软件包已广泛应用于加氢裂化、催化裂化、常压蒸馏、石脑油催化重整等实际工业过程。

1761-L32BWA这类预测控制器不是单纯把卡尔曼滤波器置于以往预测控制之前进行噪声滤波，而是把卡尔曼滤波器作为优状态推测器，同时进行优状态推测和噪声滤波控制算法还有很多。

目前，国内、外许多控制软件公司和DCS厂商都在竞相开发控制和优化控制的工程软件包，希望在组态软件中嵌入控制和优化控制策略。

Different from the traditional PID control, the non-parametric model-based predictive control algorithm estimates the future output state of the system through the predictive model, and uses the rolling optimization strategy to calculate the output of the current controller. Depending on the implementation, there are various algorithms, such as internal model control, model algorithm control, dynamic matrix control, etc.

At present, practical predictive control algorithms have been introduced into DCS, such as IDCOM control algorithm software package has been widely used in hydrocracking, catalytic cracking, atmospheric distillation, naphtha catalytic reforming and other practical industrial processes.

The 1761-L32BWA predictive controller does not simply put the Kalman filter before the previous predictive control for noise filtering, but uses the Kalman filter as an optimal state speculator, and there are many control algorithms for optimal state prediction and noise filtering at the same time.

At present, many domestic and foreign control software companies and DCS manufacturers are competing to develop control and optimization control engineering software packages, hoping to embed control and optimization control strategy in the configuration software.