# Adaptive Integral Sliding Mode Control for Temperature Regulation in Gas-Phase Ethylene Polymerization Fluidized Bed Reactors

## TL;DR

This paper introduces a new control strategy for managing temperature in ethylene polymerization reactors, which outperforms existing methods in accuracy and robustness.

## Contribution

The novel contribution is the development and evaluation of an Adaptive Integral Sliding Mode Control (AISMC) strategy for temperature regulation in fluidized bed reactors.

## Key findings

- AISMC achieves a mean absolute error of 0.092 K, significantly better than PID and conventional sliding mode control.
- AISMC demonstrates superior disturbance rejection and steady-state accuracy in dynamic operating scenarios.
- Compared to NMPC, AISMC provides better tracking performance under disturbance conditions without excessive computational cost.

## Abstract

Temperature regulation of gas-phase ethylene polymerization fluidized bed reactors (FBRs) is challenging due to strong nonlinearities, highly exothermic reaction kinetics, and frequent process disturbances. Conventional Proportional–Integral–Derivative (PID) control often exhibits limited robustness under such conditions, while advanced strategies such as Nonlinear Model Predictive Control (NMPC) may suffer from sensitivity to model mismatch and disturbances. In this study, an Adaptive Integral Sliding Mode Control (AISMC) strategy is proposed for temperature control of nonlinear gas-phase FBRs. The controller integrates adaptive gain adjustment with an integral sliding surface to improve disturbance rejection and steady-state accuracy while mitigating chattering. The performance of the proposed approach is evaluated through closed-loop simulations over an 18 h dynamic operating scenario involving multiple setpoint changes, catalyst activity variations, and feed flow disturbances. Simulation results demonstrate that AISMC achieves the best overall tracking performance, with a mean absolute error (MAE) of 0.092 K and the lowest maximum temperature deviation among the evaluated controllers. Compared to PID (MAE = 0.794 K) and conventional sliding mode control (MAE = 0.179 K), AISMC provides substantial improvements in transient and steady-state behaviors. In contrast, NMPC exhibits degraded tracking performance (MAE = 0.809 K) under the considered disturbance conditions. All controllers demonstrate sub-millisecond execution times; however, AISMC attains superior accuracy without excessive computational cost. These results indicate that AISMC offers an effective balance between robustness, accuracy, and real-time feasibility for industrial gas-phase polymerization reactors.