Sohrab Haghighat

Coordinated Control of a Dual-Stage Positioning System Using Constrained Model Predictive Control

Dual-stage positioning systems have been widely used in factory automation, robotic manipulators, high-density data storage systems, and manufacturing systems. Trajectory generation and control of dual-stage positioning systems is of great importance and is made complicated by the presence of physical and operational constraints. In this work, we describe how to generate feasible reference trajectories for a dual-stage positioning system consisting of a fine stage and a coarse stage, and how to use them in a model predictive control algorithm for which recursive feasibility is guaranteed. The reference generation algorithm is guaranteed to generate trajectories that satisfy all the constraints for the fine and coarse stages. We also describe a constrained model predictive control algorithm used to control the coarse stage. The simulation results of applying the developed methodology to track a pre-determined pattern is presented.Copyright

Robust dual control MPC with application to soft-landing control

Dual control frameworks for systems subject to uncertainties aim at simultaneously learning the unknown parameters while controlling the system dynamics. We propose a robust dual model predictive control algorithm for systems with bounded uncertainty with application to soft landing control. The algorithm exploits a robust control invariant set to guarantee constraint enforcement in spite of the uncertainty, and a constrained estimation algorithm to guarantee admissible parameter estimates. The impact of the control input on parameter learning is accounted for by including in the cost function a reference input, which is designed online to provide persistent excitation. The reference input design problem is non-convex, and here is solved by a sequence of relaxed convex problems. The results of the proposed method in a soft-landing control application in transportation systems are shown.

Robust Stall Flutter Suppression Using ℋ2/ℋ∞ Control

Following the current trend in aeroelastic optimization, as wing structures have been made more flexible, active control systems such as flutter suppression systems have been widely adopted to reduce undesirable aeroelastic behaviors. The stability and the performance of flutter suppression control systems can be negatively affected as the inflow speed deviates from the nominal design value. In this work, a mixed-norm robust controller is designed to perform stall flutter suppression. A 2-dimensional nonlinear time-domain aeroservoelastic model is developed. The nonlinear equations are linearized at different flight conditions and are employed to construct an uncertainty model, which affects the nominal dynamics in an affine way. The obtained uncertain model of the aeroservoelastic system is used to design a mixed-norm H2/H∞ controller. The performance of the designed controller is compared with the performance of a non-robust H2 controller at different flight conditions. The proposed control architecture reduces the adverse effect of inflow speed variation on the performance of the closed-loop system.Copyright