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034 Adaptive nonlinear control of a double effect evaporator
1066
Abstracts
strategy is based on a Linear Quadratic Gaussian with Loop Transfer Recovery (LQG/LTR) method to reject disturbances due to cane changes, and modified to accommodate plant constraints. A robust linear control strategy is developed, in which the variety of changes are followed using a state estimator. This strategy is widely applicable in place of fully adaptive approaches. The ensuing controller was tested on the operating mill with some qualified success. Results and conclusions are presented. 030 Experimental Comparison of Multiloop SISO and Nonlinear MIMO Control of a Mixing Tank ICE. Hiiggblom, pp 153-158 In this study of the control of a laboratory-scale thermal mixing tank, muliiloop SISO control is compared with "model-based" control where the nonlinearity and multivariable characteristics of the process are explicitly taken into account. It is shown, especially if the operating range of the process is large, that the two outputs 0evel and temperature) cannot be adequately controlled by muliiloop SISO control even if gain scheduling is used. By nonlinnar MIMO control based on exact Eneafization, very good control performance is obtained. Two nonlinear control system designs, based on a steedy-state and a dynamic model, am considered. Hard input constraints are also handled. 031 Temperature Profile Control of a Rotary Dryer with Multivarlable Model Predictive Control J. Nishizawa, M. Numata, M. Ohshima, T. Fujiwara, I. Hashimoto, pp 159-162 This paper presents a control system for a rotary dryer coping with large load disturbances while controlling the temperature profile of the material in the dryer. The system requires only two measurements, the material temperature at the dryer exit, and the temperature at which the drying mechanism changes from a constant to a falling drying rate (the "critical point"). A "soft sensor" was developed to infer the position of the critical point from the material temperature at three different points along the dryer. The resulting 2x2 multivariable model predictive controller (MPC), integrated with the "soft sensor", showed superior performance compared to a conventional multi-loop PID control system. 032 Real-Time Identification of a Five-Effect Evaporator System M. Mulholland, D,J. Love, pp 163-168 The mass/energy model of a double-train five-effect evaporator has be,en applied in a Kalman filter. The system was linearised by integrating the mass model in parallel, forcing it to track measured exit compositions. The modelling required 33 equations and 59 variables, of which 26 could be identified. The interconnection of vaponr spaces for each pair of vessels in the two trains gave a multiplicity of energy paths through the system. In off-line tests, using long records of plant data, the system showed promise as an observer for concentration control, and for monitoring changes in the heat-transfer coefficient. 033 A Unified Approach to Dynamical Discontinuous Feedback Control of a Double Effect Evaporator H. Sira-Ramirez, O. Llanes-Santlago, pp 169-172 In this paper a unified approach is proposed for the design of dynamic discontinuous feedback controllers leading to a continuous (i.e. chattering-free) stabilization of a double effect evaporator. The proposed controllers correspond to pulse fs~.~mUency modulation, pulse width modulation and sampled g mode strategies. Simulations are performed which validate the proposed approach.
034 Adaptive Nonlinear Control of a Double Effect Evaporator V.M. Herntndez, A. Montano, G. Silva, pp 173-178 The paper is concemed with the application of adaptive nonlinear control techniques to a double effect evaporator. In order to guarantee the bounded tracking, the closed-loop system is proved to be an exponential minimum-phase system. Some simulation results are illustrated to show the performance of the adaptive nonlinear control scheme, as w e l l a s a comparison with a linearization plus PI action scheme.
035 Automatic Knowledge Acquisition System for Biast Furnace Burden Distribution Operation S. Yamamoto, R. Kimura, H. Mlyahara, pp 179-184 At the NKK Keihin Works, explanation-based learning has been applied for the on-line control system of a blast furnace, and an automatic knowledge-acquisition system has been adopted. In this system, features of operating values before and after manipulation are stored as cases, and causality relationships among the operating values are acquired, based on the entropy and static gain calculation in similar cases. The control tales are generated from each case by means of deductive learning, using the causality relationships. Thus, quantitative knowledge of blast furnace control, which was difficult to attain by using the human operators' judgement, can be achieved automatically.
036 Specific Growth Rate Control In Fed.Batch Baker's Yeast Fermentation M. Keullers, L. Arlaans, M. Giuseppln, R. Soeterbnak, pp 185-188 A simple controller scheme for the specific growth rate based on measurements of the carbon-dioxide production rate and the oxygen uptake rate is presented. The specific growth rate cannot be measured but is emmated from on-line off-gas measurements. Simulations have shown that a cascade-type controller is able to keep the observed specific growth rate at set-point obeying constraints on the ethanol concentration and the dissolved oxygen tension. Experiments have shown that the controller can handle the specific growth rate set-point, but it still needs refinement with respect to the ethanol concentration and dissolved oxygen constraints.
037 Multlrate Output Control for SISO Non-Minimum Phase Systems Z.J. Palmor, Y. Halevi, Z. Rom, pp 189-192 The application of multirate output control (MROC) considerably improves the control performance of SISO non-minimum phase (NMP) systems exhibiting inverse response. The reasons are clarified by a detailed comparison between the MROC and linear time invariant (LTI) control structures (both continuous and discrete) on a wide range of simple processes. MROCs main advantage is an improvement in disturbance attenuation, while maintaining similar tracking capabilities. The trade-off between disturbance and robusmess is discussed. It is shown that an appropriate design of the MROC leads to good robustness properties with excellent performance. A tuning algorithm for optimal pole placement, based on undershoot and settling time, is developed for two-pole, one-zero systems.
038 Optimal Design of PID Process Controllers Based on Genetic Algorithms P. Wang, D.P. Kwok, p 193-197 Genetic Algorithms (GAs) are utilized to optimize the three p[~rameters of classical PID controllers for nonlinear processes. e concept and working principle of GAs are introduced and compared with those of traditional optimization methods. A simple GA to solve this nonlinear optimization problem is destgned, based on the GA theory and the author's experience. A numerical example is presented in which a pH neutralization process is regulated by a PID controller with its parameters optimized using the proposed GA.
039 Tuning of PID Controllers Based on Gain and Phase Margin Specifications W.K. Ho, C.C. Hang, L.S. Cao, pp 199-202 An analytical method is proposed to tune the PIfPID controller to ass through two design points on the Nyquist curve as specified y the gain and phase margins. They are the appropriate use of pole-zero cancellation and algebraic simplification of certain nonlinear functions. The required process parameters can be simply computed on the basis of the ultimate gain, ultimate period and static gain which may be supplied by the well-known relayfeedback or other auto-tuners. The excellent performance of the tuning formulae has been substantiated by extensive simulation.
l
Abstracts
strategy is based on a Linear Quadratic Gaussian with Loop Transfer Recovery (LQG/LTR) method to reject disturbances due to cane changes, and modified to accommodate plant constraints. A robust linear control strategy is developed, in which the variety of changes are followed using a state estimator. This strategy is widely applicable in place of fully adaptive approaches. The ensuing controller was tested on the operating mill with some qualified success. Results and conclusions are presented. 030 Experimental Comparison of Multiloop SISO and Nonlinear MIMO Control of a Mixing Tank ICE. Hiiggblom, pp 153-158 In this study of the control of a laboratory-scale thermal mixing tank, muliiloop SISO control is compared with "model-based" control where the nonlinearity and multivariable characteristics of the process are explicitly taken into account. It is shown, especially if the operating range of the process is large, that the two outputs 0evel and temperature) cannot be adequately controlled by muliiloop SISO control even if gain scheduling is used. By nonlinnar MIMO control based on exact Eneafization, very good control performance is obtained. Two nonlinear control system designs, based on a steedy-state and a dynamic model, am considered. Hard input constraints are also handled. 031 Temperature Profile Control of a Rotary Dryer with Multivarlable Model Predictive Control J. Nishizawa, M. Numata, M. Ohshima, T. Fujiwara, I. Hashimoto, pp 159-162 This paper presents a control system for a rotary dryer coping with large load disturbances while controlling the temperature profile of the material in the dryer. The system requires only two measurements, the material temperature at the dryer exit, and the temperature at which the drying mechanism changes from a constant to a falling drying rate (the "critical point"). A "soft sensor" was developed to infer the position of the critical point from the material temperature at three different points along the dryer. The resulting 2x2 multivariable model predictive controller (MPC), integrated with the "soft sensor", showed superior performance compared to a conventional multi-loop PID control system. 032 Real-Time Identification of a Five-Effect Evaporator System M. Mulholland, D,J. Love, pp 163-168 The mass/energy model of a double-train five-effect evaporator has be,en applied in a Kalman filter. The system was linearised by integrating the mass model in parallel, forcing it to track measured exit compositions. The modelling required 33 equations and 59 variables, of which 26 could be identified. The interconnection of vaponr spaces for each pair of vessels in the two trains gave a multiplicity of energy paths through the system. In off-line tests, using long records of plant data, the system showed promise as an observer for concentration control, and for monitoring changes in the heat-transfer coefficient. 033 A Unified Approach to Dynamical Discontinuous Feedback Control of a Double Effect Evaporator H. Sira-Ramirez, O. Llanes-Santlago, pp 169-172 In this paper a unified approach is proposed for the design of dynamic discontinuous feedback controllers leading to a continuous (i.e. chattering-free) stabilization of a double effect evaporator. The proposed controllers correspond to pulse fs~.~mUency modulation, pulse width modulation and sampled g mode strategies. Simulations are performed which validate the proposed approach.
034 Adaptive Nonlinear Control of a Double Effect Evaporator V.M. Herntndez, A. Montano, G. Silva, pp 173-178 The paper is concemed with the application of adaptive nonlinear control techniques to a double effect evaporator. In order to guarantee the bounded tracking, the closed-loop system is proved to be an exponential minimum-phase system. Some simulation results are illustrated to show the performance of the adaptive nonlinear control scheme, as w e l l a s a comparison with a linearization plus PI action scheme.
035 Automatic Knowledge Acquisition System for Biast Furnace Burden Distribution Operation S. Yamamoto, R. Kimura, H. Mlyahara, pp 179-184 At the NKK Keihin Works, explanation-based learning has been applied for the on-line control system of a blast furnace, and an automatic knowledge-acquisition system has been adopted. In this system, features of operating values before and after manipulation are stored as cases, and causality relationships among the operating values are acquired, based on the entropy and static gain calculation in similar cases. The control tales are generated from each case by means of deductive learning, using the causality relationships. Thus, quantitative knowledge of blast furnace control, which was difficult to attain by using the human operators' judgement, can be achieved automatically.
036 Specific Growth Rate Control In Fed.Batch Baker's Yeast Fermentation M. Keullers, L. Arlaans, M. Giuseppln, R. Soeterbnak, pp 185-188 A simple controller scheme for the specific growth rate based on measurements of the carbon-dioxide production rate and the oxygen uptake rate is presented. The specific growth rate cannot be measured but is emmated from on-line off-gas measurements. Simulations have shown that a cascade-type controller is able to keep the observed specific growth rate at set-point obeying constraints on the ethanol concentration and the dissolved oxygen tension. Experiments have shown that the controller can handle the specific growth rate set-point, but it still needs refinement with respect to the ethanol concentration and dissolved oxygen constraints.
037 Multlrate Output Control for SISO Non-Minimum Phase Systems Z.J. Palmor, Y. Halevi, Z. Rom, pp 189-192 The application of multirate output control (MROC) considerably improves the control performance of SISO non-minimum phase (NMP) systems exhibiting inverse response. The reasons are clarified by a detailed comparison between the MROC and linear time invariant (LTI) control structures (both continuous and discrete) on a wide range of simple processes. MROCs main advantage is an improvement in disturbance attenuation, while maintaining similar tracking capabilities. The trade-off between disturbance and robusmess is discussed. It is shown that an appropriate design of the MROC leads to good robustness properties with excellent performance. A tuning algorithm for optimal pole placement, based on undershoot and settling time, is developed for two-pole, one-zero systems.
038 Optimal Design of PID Process Controllers Based on Genetic Algorithms P. Wang, D.P. Kwok, p 193-197 Genetic Algorithms (GAs) are utilized to optimize the three p[~rameters of classical PID controllers for nonlinear processes. e concept and working principle of GAs are introduced and compared with those of traditional optimization methods. A simple GA to solve this nonlinear optimization problem is destgned, based on the GA theory and the author's experience. A numerical example is presented in which a pH neutralization process is regulated by a PID controller with its parameters optimized using the proposed GA.
039 Tuning of PID Controllers Based on Gain and Phase Margin Specifications W.K. Ho, C.C. Hang, L.S. Cao, pp 199-202 An analytical method is proposed to tune the PIfPID controller to ass through two design points on the Nyquist curve as specified y the gain and phase margins. They are the appropriate use of pole-zero cancellation and algebraic simplification of certain nonlinear functions. The required process parameters can be simply computed on the basis of the ultimate gain, ultimate period and static gain which may be supplied by the well-known relayfeedback or other auto-tuners. The excellent performance of the tuning formulae has been substantiated by extensive simulation.
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