John Pittner

A Useful Control Model for Tandem Hot Metal Strip Rolling

The tandem hot metal strip rolling process is a highly complex nonlinear system that presents a difficult control challenge. This challenge is exacerbated by the hostile hot metal rolling environment, which precludes the location of sensors to measure variables that are important for control. In addition, the controller must have a structure that offers simplicity of tuning during commissioning by personnel who usually are unfamiliar with advanced process control techniques. Based on our previous work using a state-dependent Riccati equation technique for control of the tandem cold metal rolling process, it is considered that a similar method might also be useful for control of tandem hot strip rolling. For the hot rolling process, the development of a process model in a form that is suitable for control development is a significant and challenging task. This paper describes our work to expand on an initial portion of this model to develop a comprehensive nonlinear model of this process. Based on simulation results, it is determined that the complete model has the potential to be useful in the development of a viable nonlinear control method for significant improvement in the control of the tandem hot rolling process.

An Initial Model for Control of a Tandem Hot Metal Strip Rolling Process

The tandem rolling of hot metal strip presents a significant control challenge because of nonlinearities and process complexities. The challenge is heightened by an extremely hostile environment that precludes the location of sensors to measure process variables that are important for control. In addition, it is essential that the controller structure allows for a high degree of physical intuition in the design process and provides for simplicity of tuning during commissioning. Based on our previous work using a state-dependent Riccati equation (SDRE) technique for control of the tandem cold rolling process, it is considered that a similar method might also be useful as a basis for the development of a control technique for tandem hot strip rolling. For the hot rolling process, the development of a process model in a form that is suitable for use with a SDRE-based method is a significant and challenging task. This paper describes our work to develop an initial model for this process. Based on simulation results, it is determined that this initial model has the potential to be the basis for the development of the complete nonlinear model that can be used for development of a viable control method which offers the likelihood for improvement in the control of the hot metal rolling process.

State-dependent Riccati equation approach for optimal control of a tandem cold metal rolling process

The tandem cold rolling of metal strip is a large multiinput-multioutput process that presents a difficult challenge to the control designer because of the following factors: 1) the complex interactions between the process variables; 2) the nonlinearities; and 3) the interstand time delays that change significantly with the mill speed. Control systems using the present technology have produced an acceptable product but are limited in their capability for improvement in performance and robustness, and therefore, there is a need for a better approach. It is considered that the state-dependent algebraic Riccati equation technique for the control of nonlinear systems that has been quite successful in the aerospace industry might fulfil this need. This paper presents the results of an initial work performed to investigate the theoretical and applied aspects of this technique for the control of the tandem cold rolling mill. In this paper, nonlinear state space equations are derived from a mathematical model of the mill, and a controller using the state-dependent Riccati equation approach (with trims) is developed. By simulation of typical operating conditions, the controller, when coupled to the model, is shown to be effective in reducing the effects of disturbances in entry strip thickness and hardness.

Controller for improving the quality of the tandem rolling of hot metal strip

The tandem hot metal strip rolling process presents a difficult control challenge because of its highly complex and nonlinear nature. This challenge is heightened by the hostile hot metal rolling environment which precludes the location of certain sensors to measure variables that are important for control. Based on our previous work using a state-dependent Riccati equation technique for development of a controller for the tandem cold metal rolling process, it is considered that a similar basis could be expanded upon to realize an improved method for the control of this more complex application. In this paper we present a comprehensive model of this process plus the results of our first efforts in the development of a suitable controller, which for control of this application is different than previous methods. The results of simulations of the controller coupled to the model show a strong potential for improvement in the quality of the final product.

Optimal Control of Tandem Cold Rolling Using A Pointwise Linear Quadratic Technique With Trims

The tandem cold rolling of metal strip is a complex multivariable process whose control presents a significant engineering challenge because of the complex interaction between the process variables, the nonlinearities (which change with operating conditions), and the interstand time delays (which change significantly with the mill speed). The present technology generally relies on a control structure that has been successful in producing an acceptable output, but has limited capability for improvement in performance. This paper describes a new strategy for control of the mill that overcomes many limitations of the present controllers. The new strategy is based on a pointwise linear quadratic technique wherein a state-dependent algebraic Riccati equation is solved pointwise to establish a control law for a multiinput-multioutput controller, with appropriate trimming functions. For this application, the features of this novel strategy compare favorably to those of other techniques for control of nonlinear systems in the areas of simplicity of implementation, provision for the use of physical intuition in the design process, and strong robustness to disturbances and uncertainties. During simulations using the new controller coupled to a nonlinear model of the process, the tolerance in mill exit thickness was ∼0.2% for several rolling schedules using mild steel during operations at steady speed and during speed changes, and in the presence of typical disturbances with uncertainties in modeling and measurement. This offers the potential for improvement over present industrial controllers, which typically hold the tolerance in mill exit thickness to within 0.5-0.8%. In addition, excursions in the individual mill stand output thicknesses and interstand tensions are reduced, which contributes to the stability of the rolling process.

Pointwise linear quadratic optimal control of a tandem cold rolling mill

The tandem cold rolling of metal strip is a complex nonlinear multivariable process whose optimization presents significant challenges to the control design. Existing systems using the present technology are limited in their capability for improvement in performance and robustness and therefore the need arises for a better approach. It is considered that a pointwise linear quadratic optimal control might fulfill this need. This paper presents the results of work performed to investigate the theoretical and applied aspects of this technique for control of a tandem cold rolling mill. In this paper nonlinear state space equations are derived from a mathematical model of the mill, and a pointwise linear quadratic optimal controller is developed. The controller when coupled to the model is shown by simulation of typical operating conditions to be effective in reducing the effects of disturbances in entry strip thickness and hardness.

An Optimal Control Method for Improvement in Tandem Cold Metal Rolling

Controlling the tandem cold rolling of metal strip is a significant engineering challenge mostly because of the complexity of the interactions between the process variables, the nonlinearities which change with the operating conditions, and the long time delays which change significantly with the mill speed. The present technology is based on methods that divide the control problem into several independent control sub-problems, which results in a limited capability for improvement in performance. This paper describes a new control strategy wherein the control of the mill is treated as a single interconnected problem that is addressed by solving a state-dependent algebraic Riccati equation pointwise to establish a control law for a multi-input-multi-output (MIMO) controller which is enhanced by appropriate trimming functions. Simulation testing of the new controller coupled to a nonlinear model of the process showed that the tolerance in mill exit thickness could be held to about .2% for typical rolling operations, which compares favorably to the tolerances of .5% to .8% using existing techniques. In addition to this improvement in performance, the simplicity of the new control method also offers the potential to reduce the efforts required for design, commissioning, and maintenance.

Improvement in Control of the Tandem Hot Strip Mill

Our previous work has shown that the use of the state-dependent Riccati equation (SDRE) technique as a basis for the development of a suitable controller for the tandem hot metal rolling process has resulted in significant improvements in performance. However, the method of setting the controller parameters was left as a part of future efforts. In this paper, we show that improvements in the implementation of the SDRE method provide a method of easily setting initial control parameters and then making automatic adjustments to the controller as the strip is processed through the mill. This eliminates the need for an online solution of the SDRE or the need for lookup tables to make controller settings. These improvements greatly simplify the design and implementation of the controller and also make the SDRE technique even more attractive in the control of many similar complex industrial processes.

A New Strategy for Optimal Control of Continuous Tandem Cold Metal Rolling

The control of continuous tandem cold rolling of metal strip is similar to the control of stand-alone tandem cold rolling except that additional challenges occur during the passage of the weld, which generally is done at reduced speed. The more significant issues that must be considered are the following: 1) reducing the length of strip near the weld that has excessive excursions in thickness; 2) reducing the excursions in tension and roll force as the weld goes through a stand; and 3) maintaining the mass flow balance in the mill. This paper presents the results of an investigation of the application of the state-dependent Riccati equation (SDRE) technique developed for improvement in the control of stand-alone tandem cold rolling, to continuous tandem cold rolling, particularly during passage of the weld. Two methods of control during this regime of operation are evaluated and a preferred method is selected. Using the preferred method, it was determined by simulation that the SDRE technique has the capability for successfully controlling the mill during weld passage, so that this novel approach offers a strong potential for improvement in the control of both the stand-alone and continuous tandem cold rolling processes.

Quality improvement of tandem hot metal strip rolling using an augmented state-dependent Riccati equation technique

The tandem rolling of hot metal strip is a highly complex nonlinear large-scale industrial process with significant time delays plus major uncertainties and disturbances. The control challenge also is heightened by a hostile environment that precludes the location of certain sensors to measure variables that are important for control. Based on the results of our previous work using a modified state-dependent Riccati equation technique for control of the tandem cold metal rolling process, it is considered that a similar basis could be expanded upon to realize an improved method for the control of this more complex application. In this paper we present a comprehensive process model and expand on the results of our first efforts in the development of a suitable controller for this process. The results of simulations of the controller coupled to the model show a strong potential for improvement in the quality of the final product. The methodology used also has the potential for expansion to improve the control of other large nonlinear systems.