By Matthew Ellis, Jinfeng Liu, Panagiotis D. Christofides
This booklet provides common tools for the layout of financial version predictive keep watch over (EMPC) structures for huge periods of nonlinear platforms that deal with key theoretical and functional issues together with recursive feasibility, closed-loop balance, closed-loop functionality, and computational potency. in particular, the e-book proposes:
- Lyapunov-based EMPC tools for nonlinear systems;
- two-tier EMPC architectures which are hugely computationally effective; and
- EMPC schemes dealing with explicitly uncertainty, time-varying price services, time-delays and multiple-time-scale dynamics.
The proposed equipment hire a number of instruments starting from nonlinear platforms research, via Lyapunov-based keep watch over ideas to nonlinear dynamic optimization. The applicability and function of the proposed tools are validated via a couple of chemical method examples.
The ebook provides state of the art equipment for the layout of monetary version predictive regulate structures for chemical processes.In addition to being mathematically rigorous, those tools accommodate key useful concerns, for instance, direct optimization of approach economics, time-varying monetary fee services and computational potency. various reviews and comments delivering basic knowing of the merging of procedure economics and suggestions regulate right into a unmarried framework are integrated. A regulate engineer can simply tailor the various exact examples of commercial relevance given in the textual content to a selected application.
The authors current a wealthy number of new study subject matters and references to major fresh paintings making Economic version Predictive Control a huge resource of data and concept for teachers and graduate scholars learning the realm and for technique engineers attracted to utilising its ideas.
Read Online or Download Economic Model Predictive Control: Theory, Formulations and Chemical Process Applications PDF
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Extra resources for Economic Model Predictive Control: Theory, Formulations and Chemical Process Applications
27 achieves better economic performance compared to the economic performance at steady-state for some τ . Moreover, the economic performance depends on the period which is shown in Fig. 4. 20 yields the best performance (Fig. 4). 30 percent better than the performance at the optimal steady-state. 96 achieve worse performance compared to that at steady-state. The state, input, and B T λ = b1T λ = λ1 + λ3 /τ trajectories are given in Fig. 5 over one period. From Fig. 5, the input trajectory satisfies the necessary condition of Eq.
The Hamiltonian function, adjoint variables, Pontryagin’s maximum principal . Nevertheless, these concepts are not needed later in the book. 20) 0 d x3 (t) 1 = (u(t) − u avg ). 21) The non-isothermal CSTR with the stage cost (Eq. 22) where x˙ denotes the time derivative of x, B ∈ Rn×m is a constant matrix and f¯ : Rn → Rn is a differentiable vector function. 23) le (x, u) = l¯e (x) where l¯e : Rn → R is a differentiable function. The Hamiltonian function of the system of Eq. 22 and cost of Eq.
5, the input trajectory satisfies the necessary condition of Eq. 26. From these results, timevarying operation is better than steady-state operation from an economical point of view for this example. If the average constraint of Eq. 19 was not imposed, the optimal operating strategy would be steady-state operation at the steady-state corresponding to the input u max . The average constraint plays a crucial role for this particular example. As pointed out, the above analysis only considers economic performance.
Economic Model Predictive Control: Theory, Formulations and Chemical Process Applications by Matthew Ellis, Jinfeng Liu, Panagiotis D. Christofides