Chapter 11 Optimal control of batch processes in the continuous time domain
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Riju De
Abstract
Batch processes are vital in manufacturing specialty and fine chemicals, which are commonly employed in small-scale industries targeting a lower production volume. Optimal control problems (OCPs) are paramount to optimizing the batch processes owing to their nonlinear dynamical behavior and a wider range of operating conditions. This chapter briefly reviews various OCPs applied to batch processes along with their mathematical formulations while considering case-specific constraints defined on the control and state variables. The key challenges and commonly appeared decision variables pertaining to chemical or biochemical batch operations are summarized. Numerical techniques to solve the OCPs using an indirect method, i.e., Pontryagin’s minimum principle and a direct method involving sequential and simultaneous collocation-based approaches are provided. This study further explores the quadratic regulator problem and optimal tracking controller design for the batch processes using linearized dynamical models by illustrating a case study. Selected applications of the OCPs on diverse batch processes from chemical, biochemical, and ecosystem engineering domains, viz., transesterification, acid pre-treatment, hydrothermal liquefaction, enzymatic hydrolysis, and predator-prey system are reviewed from the literature. Current trends and progress toward developing new OCPs algorithms are also discussed.
Abstract
Batch processes are vital in manufacturing specialty and fine chemicals, which are commonly employed in small-scale industries targeting a lower production volume. Optimal control problems (OCPs) are paramount to optimizing the batch processes owing to their nonlinear dynamical behavior and a wider range of operating conditions. This chapter briefly reviews various OCPs applied to batch processes along with their mathematical formulations while considering case-specific constraints defined on the control and state variables. The key challenges and commonly appeared decision variables pertaining to chemical or biochemical batch operations are summarized. Numerical techniques to solve the OCPs using an indirect method, i.e., Pontryagin’s minimum principle and a direct method involving sequential and simultaneous collocation-based approaches are provided. This study further explores the quadratic regulator problem and optimal tracking controller design for the batch processes using linearized dynamical models by illustrating a case study. Selected applications of the OCPs on diverse batch processes from chemical, biochemical, and ecosystem engineering domains, viz., transesterification, acid pre-treatment, hydrothermal liquefaction, enzymatic hydrolysis, and predator-prey system are reviewed from the literature. Current trends and progress toward developing new OCPs algorithms are also discussed.
Chapters in this book
- Frontmatter I
- Contents V
- List of contributing authors VII
- Chapter 1 Optimization and its importance for chemical engineers: challenges, opportunities, and innovations 1
- Chapter 2 Deterministic optimization of distillation processes 25
- Chapter 3 Optimal design of process energy systems integrating sustainable considerations 79
- Chapter 4 Metaheuristics for the optimization of chemical processes 113
- Chapter 5 Surrogate-based optimization techniques for process systems engineering 159
- Chapter 6 Data-driven techniques for optimal and sustainable process integration of chemical and manufacturing systems 215
- Chapter 7 Applications of Bayesian optimization in chemical engineering 255
- Chapter 8 Sensitivity assessment of multi-criteria decision-making methods in chemical engineering optimization applications 283
- Chapter 9 Hybrid optimization methodologies for the design of chemical processes 305
- Chapter 10 Optimization under uncertainty in process systems engineering 343
- Chapter 11 Optimal control of batch processes in the continuous time domain 379
- Chapter 12 Supply chain optimization for chemical and biochemical processes 401
- Chapter 13 Future insights for optimization in chemical engineering 425
- Index 445
Chapters in this book
- Frontmatter I
- Contents V
- List of contributing authors VII
- Chapter 1 Optimization and its importance for chemical engineers: challenges, opportunities, and innovations 1
- Chapter 2 Deterministic optimization of distillation processes 25
- Chapter 3 Optimal design of process energy systems integrating sustainable considerations 79
- Chapter 4 Metaheuristics for the optimization of chemical processes 113
- Chapter 5 Surrogate-based optimization techniques for process systems engineering 159
- Chapter 6 Data-driven techniques for optimal and sustainable process integration of chemical and manufacturing systems 215
- Chapter 7 Applications of Bayesian optimization in chemical engineering 255
- Chapter 8 Sensitivity assessment of multi-criteria decision-making methods in chemical engineering optimization applications 283
- Chapter 9 Hybrid optimization methodologies for the design of chemical processes 305
- Chapter 10 Optimization under uncertainty in process systems engineering 343
- Chapter 11 Optimal control of batch processes in the continuous time domain 379
- Chapter 12 Supply chain optimization for chemical and biochemical processes 401
- Chapter 13 Future insights for optimization in chemical engineering 425
- Index 445
