DCS control systems achieve plant-wide automation, allowing almost all enterprise decision-makers to proactively select a DCS system to control their production lines. Expert optimization systems, however, are often overlooked by decision-makers, but their importance will gradually become apparent with their increasing adoption. From a control function perspective, DCS systems solve the control problems of conventional objects. However, for complex controlled objects, the uncertainty, nonlinearity, and imprecision pose a challenge for both DCS control systems and automation engineers with limited knowledge of production processes and equipment. Expert optimization systems can address this issue. Developed collaboratively by production process experts, production equipment experts, and automation control experts, expert optimization systems are intelligent systems incorporating expert experience and modern control technologies. These systems include expert control, multi-mode control, and self-tuning PID control. Industrial IT control systems , developed by ABB, combine industrial and information technologies to create an open application system based on an attribute-target platform. Industrial IT not only provides control functions but also serves as a platform for enterprise production, management, and decision-making. The system structure of Industrial IT is shown in Figure 1. Figure 1: Industrial IT System Structure Diagram. Depending on the different hardware requirements of the expert optimization system for the Industrial IT system, the expert optimization system can be fully integrated into the hardware of the Industrial IT system, with the optimization program integrated into the controller, and configured, debugged, and operated using engineering workstations and operator workstations. Alternatively, the expert optimization system can be configured with an independent SERVER/CLIENT structure, adding an Application Server as the server for the expert optimization system and several Workplaces as workstations. The ACC system and the EO system are two expert optimization systems applied to different process controls. The ACC system is fully integrated into the Industrial IT control system; the EO system has an independent SERVER/CLIENT hardware structure. Automatic Combustion Control System (ACC): The Automatic Combustion Control System (ACC) is a combustion optimization control system developed by TAKUMA for the control of grate-type waste incinerators. Its purpose is to maintain stable combustion and efficiently utilize energy. The main task of the Automatic Combustion Control System (ACC) is to obtain a stable steam volume while strictly controlling the oxygen content in the exhaust gas, requiring simultaneous adjustment of primary air volume, secondary air volume, feed rate, and grate speed. The Automatic Combustion Control (ACC) system consists of a steam flow control subsystem, a grate speed control subsystem, a combustion air flow control subsystem, and an oxygen content control subsystem. Steam Flow Control Subsystem The quality of waste fuel, i.e., its calorific value, is greatly affected by time and season. During combustion, the combustion air flow and the speed of each grate section are adjusted to reduce fluctuations in the calorific value of the waste fuel, stabilize furnace temperature, steam flow, daily waste processing volume, and control fly ash quality. Steam flow control is achieved by minimizing combustion fluctuations. When the calorific value of the waste fuel changes, an appropriate amount of combustion air is introduced into the furnace, while ensuring an appropriate amount of waste fuel is in the combustion zone. The target steam flow is set by the operator, and the combustion air flow is automatically calculated based on the set target steam flow and target oxygen content values. Then, the grate speed is calculated based on the steam flow and combustion air flow values. Therefore, steam flow control is achieved through grate speed control and combustion air flow control. Grate Speed ​​Control Grate speed control has manual and automatic modes. In manual mode, the operator can directly set the speed. In automatic mode, the target speed is set by the ACC program. After commissioning, the speed of each grate section remains essentially constant, with its setpoint determined during commissioning. The speed of the combustion grate is calculated based on the target steam flow rate and the deviation between the actual and target flow rates. Additionally, this speed is controlled by the air-to-fuel ratio and the measurements from the burnout section sensors. Combustion fluctuations in the combustion grate are detected by dedicated sensors. If combustion fluctuations in the burnout section are due to significant changes in the quality of the waste fuel or other extreme conditions, the combustion grate speed will be slowed down to prevent an increase in unburned waste. The speed of the drying grate is essentially proportional to the speed of the combustion grate and is also corrected for the waste bed thickness. A waste level switch located above the combustion section is used to detect the waste bed thickness and to calibrate the speed of the drying grate, ensuring a constant bed thickness. The feeder speed is essentially proportional to the speed of the drying grate and is also corrected for the bed thickness. The ACC does not control the speed of the burnout grate. Its speed is a constant value, and the operator can change this value according to fly ash conditions. Combustion Air Flow Control Subsystem The necessary combustion air flow is calculated based on the target steam flow and the specified oxygen content. Primary and secondary air are appropriately allocated to each grate. Their allocation ratio remains essentially unchanged after commissioning and tuning. Combustion air flow control includes manual, automatic, and cascade control modes. In manual mode, the operator can directly open the control air damper to a certain position; in automatic control mode, the operator can control the air flow to a constant based on the target flow; in cascade control mode, the target air flow value is set by the ACC. Secondary air flow is compensated by oxygen content and furnace flue gas temperature. Integration of the ACC System with the Industrial IT Controller Figure 2 shows the interface of the Industrial IT system configuration. The ACC system's algorithm becomes a task of the controller, and it will be downloaded into the controller along with other programs; that is, the ACC system is embedded in the Industrial IT system. Figure 2: Industrial IT System Configuration Interface EO System The EO system is an expert optimization system developed by ABB and widely used in industrial kiln control and industrial grinding mill control. The EO system includes artificial intelligence control algorithms (AI) and model-based control algorithms (MBC). The configuration of control strategies is completed using algorithms such as fuzzy logic control, neural network control, and model predictive control. The EO system can significantly improve production efficiency and ensure production stability through optimal control strategies. The application of the EO system in dry-process cement kilns can increase clinker output, improve clinker quality, improve clinker stability, reduce emissions of waste gas and waste, and reduce heat energy consumption by 3-7%. See Figure 3: Schematic Diagram of Cement Kiln Operation. Figure 3: Schematic Diagram of Cement Kiln Operation The variables collected by the EO system from the Industrial IT control system include: preheater oxygen content, preheater temperature, carbon monoxide concentration, kiln inlet temperature, kiln outlet temperature, decomposition section temperature, and kiln main drive motor current, etc. After completing calculations, the EO system outputs control variables to the Industrial IT system, including induced draft fan speed, kiln feed rate, kiln rotation speed, and pulverized coal (oil) injection rate. EO system configuration and commissioning: The EO system is generally configured by process engineers, who use a graphical interface, unlike traditional text-based environments, allowing process engineers to quickly master the configuration methods. EO system commissioning typically requires two steps. The first commissioning can begin after system installation and usually takes about 5 weeks. The second commissioning can begin 3 months after clinker production begins and usually takes 5 weeks to accurately debug the control strategy. The EO system can also be applied to older production lines that do not employ optimized control. Industrial IT control systems have excellent interface capabilities, allowing for easy integration with various expert optimization systems through multiple integration methods. Projects implementing optimized control based on Industrial IT control systems are increasingly common. In large and medium-sized control systems, the proportion choosing the "DCS system + expert optimization system" control mode is increasing year by year. The role of expert optimization systems will gradually become apparent, and they will inevitably be adopted by more and more enterprise decision-makers. The CS control system achieves plant-wide automated control. Almost all enterprise decision-makers can proactively choose a DCS system to control their production lines. However, expert optimization systems are not initially valued by enterprise decision-makers, but their role will gradually become apparent with the continuous introduction of expert optimization systems. From a control function perspective, DCS systems solve the control problems of conventional objects. However, for complex controlled objects, the uncertainty, nonlinearity, and imprecision pose a challenge for both DCS control systems and automation engineers with limited knowledge of production processes and equipment. Expert optimization systems can solve this problem. Expert optimization systems are jointly developed by production process experts, production equipment experts, and automation control experts. They are intelligent systems that integrate expert experience and modern control technology. Expert optimization control systems include expert control, multi-mode control, and self-tuning PID control. The Industrial IT control system is ABB's control system. It combines industrial technology and information technology to build an open application system based on an attribute-objective platform. Industrial IT not only provides control functions but also serves as a working platform throughout enterprise production, management, and decision-making. The system structure of Industrial IT is shown in the Industrial IT system structure diagram (Figure 1). Depending on the different hardware requirements of the expert optimization system for the Industrial IT system, the expert optimization system can be fully integrated into the Industrial IT system hardware, with the optimization program integrated into the controller, and configured, debugged, and operated using engineering workstations and operator workstations. Alternatively, the expert optimization system can be configured with a separate SERVER/CLIENT structure, adding an Application Server as the server for the expert optimization system and several Workplaces as workstations. The ACC system and the EO system are two expert optimization systems applied to different process controls. The ACC system is fully integrated into the Industrial IT control system; the EO system has a separate SERVER/CLIENT hardware structure. The Automatic Combustion Control System ( ACC) is a combustion optimization control system developed by TAKUMA for the control of grate-type waste incinerators. Its purpose is to maintain stable combustion and efficiently utilize energy. The main task of the Automatic Combustion Control System (ACC) is to obtain a stable steam volume while strictly controlling the oxygen content in the exhaust gas, requiring simultaneous adjustment of primary air volume, secondary air volume, feed rate, and grate speed. The Automatic Combustion Control (ACC) system consists of a steam flow control subsystem, a grate speed control subsystem, a combustion air flow control subsystem, and an oxygen content control subsystem. Steam Flow Control Subsystem The quality of waste fuel, i.e., its calorific value, is greatly affected by time and season. During combustion, the combustion air flow and the speed of each grate section are adjusted to reduce fluctuations in the calorific value of the waste fuel, stabilize furnace temperature, steam flow, daily waste processing volume, and control fly ash quality. Steam flow control is achieved by minimizing combustion fluctuations. When the calorific value of the waste fuel changes, an appropriate amount of combustion air is introduced into the furnace, while ensuring an appropriate amount of waste fuel is in the combustion zone. The target steam flow is set by the operator, and the combustion air flow is automatically calculated based on the set target steam flow and target oxygen content values. Then, the grate speed is calculated based on the steam flow and combustion air flow values. Therefore, steam flow control is achieved through grate speed control and combustion air flow control. Grate Speed ​​Control Grate speed control has manual and automatic modes. In manual mode, the operator can directly set the speed. In automatic mode, the target speed is set by the ACC program. After commissioning, the speed of each grate section remains essentially constant, with its setpoint determined during commissioning. The speed of the combustion grate is calculated based on the target steam flow rate and the deviation between the actual and target flow rates. Additionally, this speed is controlled by the air-to-fuel ratio and the measurements from the burnout section sensors. Combustion fluctuations in the combustion grate are detected by dedicated sensors. If combustion fluctuations in the burnout section are due to significant changes in the quality of the waste fuel or other extreme conditions, the combustion grate speed will be slowed down to prevent an increase in unburned waste. The speed of the drying grate is essentially proportional to the speed of the combustion grate and is also corrected for the waste bed thickness. A waste level switch located above the combustion section is used to detect the waste bed thickness and to calibrate the speed of the drying grate, ensuring a constant bed thickness. The feeder speed is essentially proportional to the speed of the drying grate and is also corrected for the bed thickness. The ACC does not control the speed of the burnout grate. Its speed is a constant value, and the operator can change this value according to fly ash conditions. Combustion Air Flow Control Subsystem The necessary combustion air flow is calculated based on the target steam flow and specified oxygen content. Primary and secondary air are appropriately allocated to each grate. Their allocation ratio remains essentially unchanged after commissioning and tuning. Combustion air flow control includes manual, automatic, and cascade control modes. In manual mode, the operator can directly open the control air damper to a certain position; in automatic control mode, the operator can control the air flow to a constant based on the target flow; in cascade control mode, the target air flow value is set by the ACC. Secondary air flow is compensated by oxygen content and furnace flue gas temperature. Integration of the ACC System with the Industrial IT Controller Figure 2 shows the interface of the Industrial IT system configuration. The ACC system's algorithm becomes a task of the controller, and it will be downloaded into the controller along with other programs; that is, the ACC system is embedded in the Industrial IT system. The EO system , developed by ABB, is an expert optimization system widely used in industrial kiln and grinding mill control. The EO system incorporates artificial intelligence (AI) control algorithms and model-based control (MBC) algorithms. Control strategy configuration utilizes algorithms such as fuzzy logic control, neural network control, and model predictive control. The EO system can significantly improve production efficiency and ensure production stability through optimal control strategies. In dry-process cement kilns, the application of the EO system can increase clinker yield, improve clinker quality and stability, reduce waste gas and waste emissions, and simultaneously reduce heat energy consumption by 3-7%. See Figure 3 for a schematic diagram of a cement kiln operation. Variables collected by the EO system from the Industrial IT control system include: preheater oxygen content, preheater temperature, carbon monoxide concentration, kiln inlet temperature, kiln outlet temperature, decomposition zone temperature, and kiln main drive motor current. After calculation, the EO system outputs control variables to the Industrial IT system, including: induced draft fan speed, kiln feed rate, kiln rotation speed, and pulverized coal (oil) injection rate. The configuration and commissioning of EO systems are typically handled by process engineers, who configure the control strategies. EO provides a graphical interface, unlike traditional text-based environments, enabling process engineers to quickly master the configuration methods. Commissioning of EO systems generally requires two steps. The first commissioning can begin immediately after system installation and typically takes five weeks. The second commissioning can begin three months into clinker production and usually takes five weeks to precisely tune the control strategies. EO systems can also be applied to older production lines that do not employ optimized control. Industrial IT control systems have excellent interface capabilities, allowing for easy integration with various expert optimization systems through multiple integration methods. Projects implementing optimized control based on Industrial IT control systems are increasingly common. In large and medium-sized control systems, the proportion choosing the "DCS system + expert optimization system" control mode is increasing year by year. The role of expert optimization systems will gradually become apparent, and they will undoubtedly be adopted by more and more enterprise decision-makers.