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Two schemes for feedback scheduling on hybrid control systems. Chen Xi. Reference. Feedback scheduling of model predictive controllers
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Two schemes for feedback scheduling on hybrid control systems Chen Xi
Reference • Feedback scheduling of model predictive controllers Dan Henriksson, Anton Cervin, Johan Åkesson, Karl-Erik Årzén Dept. of Automatic Control, Lund Institution of Technology . 8th IEEE Real-Time and Embedded Technology and Applications Symposium ,San Jose,CA, September 2002 On pages: 207- 216
Two main ways for CPU utilization: (1) tuning task periods focus : system with small variation in execution time e.g. hybrid control system (2) manipulating the execution times focus: systems with large variation on execution time e.g. model predictive controllers
MPC model • Feedback scheduling of MPCs x-state vector; u-control signals vector y-measured output vector; z-controlled output vector Goal: make the controlled outputs z follows the reference trajectory r Solve control signal by minimizing a quadratic cost function on the form:
Motivation to scheduling MPC by tuning execution time • Number of iterations required for the optimization is different from sample to sample • number of active constrains on control signals and outputs • Reference changes • Un-modeled disturbances acting on the plant • The quality of u(k-1)
Real- time Implementation of MPC • Sampling jitter • Computational delay and actuation • preemption from higher-priority tasks • the highly varying execution time of the optimization algorithm itself
Feedback scheduling of MPC • Motivation: • Make trade-off between computational delay and optimization effect
Method for feedback scheduling • a simpler stop criterion based onthe specification of a maximum allowed delay for the controller
Method (continue) • let the current values of the MPC cost functions act as dynamic task priorities
Idea • Apply MPC method to feedback scheduling for hybrid control system • Teak the sampling time using MPC method • Motivation: • (1) CPU utilization can be estimated on every sampling point • (2) let current CPU utilization track reference input by minimizing a cost function which has relation to the performance of each hybrid system
scheme2 • Teak sampling time by taking performance error of each system into consideration If else