Portfolio · Projects

Selected projects

Exact algorithms, control applications, and interactive tools developed around continuous-time optimization and control.

01
Research framework

Continuous-time explicit optimal control

An algorithm that solves Pontryagin’s optimality conditions directly: it identifies the sequence of active constraints, computes the switching times, and constructs the critical regions without converting the model to discrete time.

PMP Critical regions Explicit MPC
02
Exact boundary computation

Exact curved critical-region boundaries

The critical regions are characterized by the switching times, the instants at which the active constraints change. For a given sequence of active constraints and fixed switching times the optimality conditions are linear in the initial state, so every boundary, hyperplane or curved, is computed exactly from linear equations rather than optimal control problems. Whether a boundary is a hyperplane or curved is known from the two sequences of active constraints alone, before any computation.

Exact boundary computation Hyperplane or curved from the labels No optimal control solves
03
Algorithm

Building the whole partition

Builds the complete map of critical regions from one region outward, without solving optimal control problems and without gridding the initial-state space, and verifies with the method’s own optimality check that no region is missing. Demonstrated on process models with up to ten states, where the map has a handful of regions and is built in seconds.

Complete map Any number of states Completeness check
04
Comparison

Continuous time versus discrete time

The same explicit controller built both ways, on forced-circulation evaporators in series with one, three, and five effects. The continuous-time critical regions are few, fixed, and faster to compute, and the controller holds the constraints at every instant. The discrete-time regions multiply with the number of discretization intervals and with the number of states until the computation becomes intractable, and the resulting controller is less accurate and leaves the constraints between discretization instants.

PPOPT benchmark Build time and memory Accuracy between instants
05
Process-control application

Continuous-time multiparametric MPC within PAROC

Integration of the continuous-time controller-synthesis step with process modeling, model approximation, critical-region construction, and closed-loop validation. Current work includes a binary distillation benchmark, forced-circulation evaporators in series with up to five effects, and preparation for intensified column applications.

PAROC Distillation Evaporators in series Disturbance rejection
06
Research communication

Neon Gate Challenge

An interactive website experience that lets visitors feel the effect of timing, constraints, continuous control, and changing initial conditions before introducing the mathematical language behind the problem.

Interactive visualization Optimal control Web communication
Questions or collaboration ideas? lida.lamakani@tamu.edu