Performance-driven control theory and applications
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Summary
This study studies stochastic disturbance rejection, performance, and optimal control and poses a discounted-cost infinite-horizon optimal control problem and uses its optimal value function as the performance benchmark to which all subsequent NMPC closed loops are compared.
- Type
- article
- Published
- 2012-01-01
- Cited by
- 0
- References
- 76
- Access
- Open access
- OpenAlex
- https://openalex.org/W47305459
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:36596524
Keywords
Control theory (sociology), Model predictive control, Optimal control, Controller (irrigation), Upper and lower bounds
References
- Dynamic matrix control¿A computer control algorithm
- Model Predictive Control System Design and Implementation Using MATLAB
- Introduction to Stochastic Dynamic Programming: Probability and Mathematical
- Principles of Lithography
- Lithography Process Control
- Receding Horizon Control: Model Predictive Control for State Models
- Modern Predictive Control
- Nonlinear predictive control : theory and practice
- Model predictive heuristic control: Applications to industrial processes
- Stochastic optimal control : the discrete time case
- Predictive control : with constraints
- Adaptive Optimal Control: The Thinking Man's G.P.C.
- On Distributed Convex Optimization Under Inequality and Equality Constraints
- Discrete-time controlled Markov processes with average cost criterion: a survey
- Position Control in Lithographic Equipment [Applications of Control]
- Constrained model predictive control: Stability and optimality
- P‐type iterative learning control for systems that contain resonance
- Robust Stability Analysis of Nonlinear Discrete-Time Systems With Application to MPC
- Optimal infinite-horizon feedback laws for a general class of constrained discrete-time systems: Stability and moving-horizon approximations
- Model predictive control: past, present and future
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