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Linear Matrix Inequalities in System and Control Theory. Solmaz Sajjadi Kia Adviser: Prof. Jabbari System, Dynamics and Control Seminar UCI, MAE Dept. April 14, 2008. Linear Matrix Inequality (LMI). Set of n polynomial inequalities in x , e.g., Convex constraint on x.
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Linear Matrix Inequalities in System and Control Theory Solmaz Sajjadi Kia Adviser: Prof. Jabbari System, Dynamics and Control Seminar UCI, MAE Dept. April 14, 2008
Linear Matrix Inequality (LMI) • Set of n polynomial inequalities in x, e.g., • Convex constraint on x
Matrices as Variable Multiple LMIs
LMI Problems Feasibility Minimization Problem
How do we cast our control problems in LMI form? We rely on quadratic function V(x)=x’Px Three Useful Properties to Cast Problems in Convex LMI From • Congruent Transformation • S-Procedure • Schur Complement
S Procedure • Three Useful Properties to Cast Problems in Convex LMI From • Congruent Transformation • S-Procedure • Schur Complement
Reachable Set/Invariant Set for Peak Bound Disturbance • The reachable set (from zero): is the set of points the state vector can reach with zero initial condition, given some limitations on the disturbance. • The invariant set: is the set that the state vector does not leave once it is inside of it, again given some limits on the disturbance.
Reachable Set/Invariant Set for Peak Bound Disturbance Ellipsoidal Estimate Peak Bound Disturbance
Linear (thus convex) Verses Nonlinear Convex inequality Three Useful Properties to Cast Problems in Convex LMI From Nonlinear (convex) inequalities are converted to LMI form using Schur Complement • Congruent Transformation • S-Procedure • Schur Complement
Norm of a vector in an ellipsoid Find Max of ||u||=||Kx|| for x in {x| xTPx≤c2 }
A Saturation Problem Problem: Synthesis/Analysis of a Bounded State Feedback Controller (||u||<umax) exposed wT(t)w(t)≤w2max • Analysis: What is the largest disturbance this system can tolerate with K • Synthesis: Find a K such that controller never saturates
Analysis: What is the largest disturbance (e.g. wmax) the system can tolerate ? xTPx<wTmax -umax=Kx umax=Kx
Synthesis: Find a K such that controller never saturates xTPx<wTmax Kx=-umax Kx=umax
Good Reference • Prof. Jabbari’s Note on LMIs • S. Boyd, L. El Ghaoui, E. Feron, V. Balakrishnan, “Linear Matrix Inequalities in Systems and Control Theory”