Nonlinear Model Predictive Control: Towards New Challenging Applications (Lecture Notes in Control and Information Sciences, 384)

Title Page
Preface
Contents
Stability and Robusteness
	Input-to-State Stability: A Unifying Framework for Robust Model Predictive Control
		Introduction
		Problem Statement
		Input-to-State Stability
			{\\it A Gentle Motivation for the ISS Notion}
			{\\it Regional Input-to-State Practical Stability (ISpS)}
		Input-to-State Stability of Nominal MPC
		Input-to-State Stability of Robust MPC
			{\\it Tube Based Methods for Robust Constraint Satisfaction}
			{\\it Predictive Controllers Based on Nominal Predictions}
			{\\it Min-Max Model Predictive Controllers}
		Conclusions
		References
	Self-optimizing Robust Nonlinear Model Predictive Control
		Introduction
		Preliminary Definitions and Results
			{\\it Basic Notions and Definitions}
			{\\it ISS Definitions and Results}
			{\\it Inherent ISS through Continuous and Convex Control Lyapunov Functions}
		Problem Definition
		MainResults
			{\\it Optimized ISS through Continuous and Convex CLFs}
			{\\it Self-optimizing Robust Nonlinear MPC}
			{\\it Decentralized Formulation}
			{\\it Implementation Issues}
		Illustrative Example
		Conclusions
		References
	Set Theoretic Methods in Model Predictive Control
		Introduction
		System Description and Role of Information
		Constrained Controllability
		Fragility of Receding Horizon Control
		Simple Tube Model Predictive Control
		Concluding Remarks
		References
	Adaptive Robust MPC: A Minimally-Conservative Approach
		Introduction
			Notation and Mathematical Preliminaries
		Problem Description
		Adaptive Robust Design Framework
			{\\it Adaptation of Parametric Uncertainty Sets}
			{\\it Feedback-MPC Framework}
			{\\it Generalized Terminal Conditions}
			{\\it Closed-Loop Stability}
		Computation and Performance Issues
			{\\it Excitation of the Closed-Loop Trajectories}
			{\\it Extension to Open-Loop MPC}
			{\\it A Practical Design Approach for W and ${\\mathbb X}_{f}$}
		Robustness Issues
		Conclusions
		References
	Enlarging the Terminal Region of NMPC with Parameter-Dependent Terminal Control Law
		Introduction
		Preliminaries
		Enlarging the Terminal Region of Quasi-infinite Horizon NMPC
			{\\it Polytopic Linear Differential Inclusions}
			{\\it Terminal Region of NMPC Based on PLDI}
		Optimization of the Terminal Region
		A Numerical Example
		Conclusions
		References
	Model Predictive Control with Control Lyapunov Function Support
		Introduction
		System Description and Problem
		Model Predictive Control Algorithm
		Choice of ${\\bar x} ^{+}$
			{\\it Open-Loop Approach}
			{\\it Closed-Loop Approach}
		Example
		Conclusion and Future Work
		References
	Further Results on “Robust MPC Using Linear Matrix Inequalities”
		Introduction
		Preliminary Definitions and Results
			{\\it Basic Notions and Definitions}
			{\\it Input-to-State Stability}
			{\\it Input-to-State Stability Conditions for Inf-sup Robust MPC}
		Problem Formulation
			{\\it Existing Solutions}
		Main Results
			{\\it LMI-Based-Solution}
			{\\it Relation to LMI-Based ${\\mathbb H}_{\\infty}$ Control Design}
		Conclusions
		References
	LMI-Based Model Predictive Control for Linear Discrete-Time Periodic Systems
		Introduction
		Problem Setup
		MPC For Linear Periodic Systems
		Simulation Results
		Conclusions
		References
	Receding Horizon Control for Linear Periodic Time-Varying Systems Subject to Input Constraints
		Introduction
		Problem Statement
			{\\it Receding Horizon Control without Input Constraints}
			{\\it Receding Horizon Control with Input Constraints}
		Simulation Results
		Conclusion
		References
Control of Complex Systems
	Optimizing Process Economic Performance Using Model Predictive Control
		Introduction
		Overview of the Process Control Literature
		Turnpike Theorems
		Linear Models
			{\\it Terminal Constraint MPC}
			{\\it Terminal Penalty MPC}
			{\\it Economic Cost Function}
		Nonlinear Models
			{\\it Maximizing Production Rate in a CSTR}
		Conclusions and Future Work
		References
	Hierarchical Model Predictive Control of Wiener Models
		Introduction
		System and Control at the Upper Level
			{\\it System and Control Problem}
			{\\it Robust MPC for the Upper Level}
		System and Control at the Lower Level
			{\\it System}
			{\\it MPC for the Lower Level}
		The Hierarchical Control System
		Conclusions
		References
	Multiple Model Predictive Control of Nonlinear Systems
		Introduction
		Control Structure
			{\\it Model Bank}
			{\\it State Estimation}
			{\\it Model Weighting Calculation}
		Model Predictive Control
		Example System
		Simulation Results
		Summary
		References
	Stabilizing Nonlinear Predictive Control over Nondeterministic Communication Networks
		Introduction
		Problem Statement
		Proposed Method
			{\\it Compensation of Measurement Delays}
			{\\it Compensation of Actuation Delays}
			{\\it Packet Dropouts}
		Simulation Results
		Conclusions
		References
	Distributed Model Predictive Control System Design Using Lyapunov Techniques
		Introduction
		Preliminaries
			{\\it Problem Formulation}
			{\\it Lyapunov-Based Controller}
			{\\it Centralized Lyapunov-Based MPC}
		Distributed LMPC
			{\\it Distributed LMPC Formulations}
			{\\it Distributed LMPC Stability}
		Application to a Reactor-Separator Process
		Conclusion
		References
	Stabilization of Networked Control Systems byNonlinear Model Predictive Control: A Set Invariance Approach
		Introduction
		Main Notations
		Problem Formulation
			{\\it Network Delay Compensation}
			{\\it Current State Reconstruction and Prediction}
			{\\it Finite Horizon Predictive Controller}
		Set Invariance Theory and Robust Stability
		References
	Nonlinear Model Predictive Control for Resource Allocation in the Management of Intermodal Container Terminals
		Introduction
		A Dynamic Model of Terminal Operations
		Predictive Control of Container Flows
		Simulation Results
		References
	Predictive Power Control of Wireless Sensor Networks for Closed Loop Control
		Introduction
		WSNs for Networked Control
		Trading Energy Use for Control Performance
		Predictive Power Control
		Simulation Study
		Conclusions
		References
	On Polytopic Approximations of Systems with Time-Varying Input Delays
		Introduction
		Preliminaries
			{\\it Basic Notation and Definitions}
			{\\it Problem Definition}
			{\\it Existing Solutions}
		MainResult
		Suitability for MPC
		Conclusions
		References
Stochastic Systems
	A Vector Quantization Approach to Scenario Generation for Stochastic NMPC
		Introduction
		Motivational Problem
		Stochastic Optimization Strategies
		Scenario Generation
		Return to the Motivational Problem
		Conclusion
		References
	Successive Linearization NMPC for a Class of Stochastic Nonlinear Systems
		Introduction
			{\\it Problem Statement}
		Successive Linearization MPC
		Probabilistic Tubes
			{\\it Tube Constraints}
			{\\it Terminal Sets and Terminal Cost}
		Receding Horizon Control Law
		Example
		References
	Sequential Monte Carlo for Model PredictiveControl
		Introduction
		Problem Formulation
		Monte Carlo Optimisation
		Stochastic Control Using MPC Based on SMC
		Numerical Examples
		References
State Estimation
	An NMPC Approach to Avoid Weakly Observable Trajectories
		Introduction
		Problem Setup and Motivation
		Avoiding Weakly Observable Trajectories
		Collision Avoidance Maneuver with Guaranteed Observability
			{\\it Vehicle Dynamics}
			{\\it Collision Avoidance Maneuver}
		Conclusions
		References
	State Estimation and Fault Tolerant Nonlinear Predictive Control of an Autonomous Hybrid System Using Unscented Kalman Filter
		Introduction
		State Estimation Using UKF
		UKF Based NMPC Formulation
		Fault Diagnosis
		NMPC with Fault Accommodation
		Simulation Study
		Conclusions
		References
	Design of a Robust Nonlinear Receding-Horizon Observer - First-Order and Second-Order Approximations
		Introduction
		Problem Statement
			{\\it Receding-Horizon Estimation}
			{\\it Robust Receding-Horizon Estimation}
		On the Use of Linearization Techniques
		Extension to Second-Order
		Continuous Cultures of Phytoplankton
		Conclusions
		References
	State Estimation in Nonlinear Model Predictive Control, Unscented Kalman Filter Advantages
		Introduction
		Nonlinear Model Predictive Control
		State Estimation: Unscented Kalman Filter
			{\\it UKF Formulation}
		A Locally Weakly Unobservable System
		Conclusions
		References
Tracking
	MPC for Tracking of Constrained Nonlinear Systems
		Introduction
		Problem Description
		MPC for Tracking
		Example
		Conclusion
		References
	A Flatness-Based Iterative Method for Reference Trajectory Generation in Constrained NMPC
		Introduction
		Flatness and Trajectory Parameterisation
			{\\it Parameterisation of Flat Outputs and Their Derivatives}
			{\\it Trajectory Parameterisation Using Splines}
		Using MPC to Shape the Reference Trajectory
			{\\it MPC Formulation}
			{\\it Iterative Method for Reference Trajectory Generation}
		Simulation Example
		Conclusion
		References
	Nonlinear Model Predictive Path-Following Control
		Introduction
		Model Predictive Path-Following Control
		Simulation Results
		References
Algorithms for Explicit Solution
	A Survey on Explicit Model Predictive Control
		Model Predictive Control
			{\\it Linear Model and Quadratic Cost}
			{\\it Linear Model and Linear Cost}
			{\\it Linear Uncertain Model and Min-Max Costs}
			{\\it Hybrid Model and Linear or Quadratic Costs}
			{\\it Extensions of the MPC Formulation}
		Explicit Model Predictive Control
			{\\it Multiparametric Programming: General Formulation}
			{\\it Multiparametric Quadratic Programming}
			{\\it Multiparametric Linear Programming}
			{\\it Explicit Solution of Min-Max MPC}
			{\\it Explicit Solution of Hybrid MPC}
		Reducing Complexity of Explicit MPC
			{\\it A Novel Practical Approach for Reducing Complexity of Explicit MPC}
		Implementation of Explicit MPC
		Tools for Explicit MPC
		Explicit MPC in Applications
		Conclusions
		References
	Explicit Approximate Model Predictive Control of Constrained Nonlinear Systems with Quantized Input
		Introduction
		Formulation of Quantized Nonlinear Model Predictive Control Problem
		Approximate mp-NIP Approach to Explicit Quantized NMPC
			{\\it Computation of Feasible PWC Solution}
			{\\it Estimation of Error Bounds}
			{\\it Approximate mp-NIP Algorithm}
		Explicit Quantized NMPC of an Electropneumatic Clutch Actuator Using On/Off Valves
			{\\it Description of the Electropneumatic Clutch Actuator}
			{\\it Design of Explicit Quantized NMPC}
		References
	Parametric Approach to Nonlinear Model Predictive Control
		Introduction
		Problem Statement
		Transformation to Shortest Path DOP
			{\\it Optimality Conditions}
			{\\it Parametrization of the HJB Equation}
			{\\it Shortest Path DOP}
		Parametric Solutions for 2D Cases
		Illustrative Example
		Conclusion
		References
Algorithms for Numerical Solution
	Efficient Numerical Methods for Nonlinear MPC and Moving Horizon Estimation
		Introduction
		Problem Formulation
			{\\it NMPC Optimal Control Problem}
			{\\it Moving Horizon Estimation: Nearly a Dual Problem}
			{\\it Sequential vs. Simultaneous Optimal Control}
		Newton Type Optimization
			{\\it Sequential Quadratic Programming}
			{\\it Interior Point Methods}
		Numerical Optimal Control
			{\\it The Linearized Optimal Control Problem}
			{\\it Elimination of Algebraic Variables}
			{\\it Condensing}
			{\\it Band Structure Exploiting Riccati Based Solutions}
			{\\it A Classification of Optimal Control Methods}
		Online Initialization and NLP Sensitivities
			{\\it Shift Initialization}
			{\\it Parametric Sensitivities}
			{\\it Generalized Tangential Predictors via SQP Methods}
		Online Algorithms
			{\\it A Survey of Online Optimization for NMPC}
		Conclusions
		References
	Nonlinear Programming Strategies for State Estimation and Model Predictive Control
		Introduction
		MHE and NMPC Formulations
		Full-Space Interior-Point NLP Solvers
			{\\it Computational Issues}
			{\\it NLP Sensitivity and Warm-Starts}
		Advanced-Step MHE and NMPC Strategies
			{\\it Stability Issues}
		Case Study
		Conclusions
		References
	A Framework for Monitoring Control Updating Period in Real-Time NMPC Schemes
		Introduction
		Problem Statement
			{\\it Recall on Parameterized NMPC}
			{\\it Implementation Scheme for Fast Systems}
			{\\it The Scope of the Present Contribution}
		Theoretical Framework
		On-Line Identification of the Key Maps
		Numerical Investigations
			{\\it Qualitative Analysis}
			{\\it An Illustrative Example}
		Conclusion
		References
	Practical Issues in Nonlinear Model Predictive Control: Real-Time Optimization and Systematic Tuning
		Introduction
		Problem Formulation
		Real-Time Algorithms
			{\\it Real-Time Costate Equation}
			{\\it Continuation/GMRES Method}
			{\\it Applications}
		Tuning of Performance Index
			{\\it Reference Model}
			{\\it Performance Index}
			{\\it Numerical Examples}
		Conclusions
		References
	Fast Nonlinear Model Predictive Control via Set Membership Approximation: An Overview
		Introduction
		Problem Settings
			{\\it Approximated NMPC Laws: Stability Results}
		Set Membership Approximation Techniques for NMPC
			{\\it Prior Information}
			{\\it “Optimal” Approximation}
			{\\it “Nearest Point” Approximation}
			{\\it “Local” Approximation}
		Numerical Example
		Conclusions
		References
	Fast Nonlinear Model Predictive Control with an Application in Automotive Engineering
		Introduction
		Direct Multiple Shooting for NMPC
			{\\it Parameterization of the Infinite OCP}
			{\\it Structure-Exploiting Nonlinear Programming}
		The Multi-level Iteration Scheme
			{\\it Initial Value Embedding and Real-Time Iterations}
			{\\it Multi-level Extensions}
		Computational Results
			{\\it Classical Real-Time Iterations}
			{\\it Multi-level Iteration Schemes}
			{\\it Computation Times}
		Conclusions
		References
	Unconstrained NMPC Based on a Class of Wiener Models: A Closed Form Solution
		Introduction
		OBF-WienerModel
		Multistep Quadratic Control Law
		Experimental Studies
		Conclusion
		References
	An Off-Line MPC Strategy for Nonlinear Systems Based on SOS Programming
		Introduction
		Problem Formulation
		MainResult
		A Low-Demanding Receding Horizon Control Algorithm
		Illustrative Example
		Conclusions
		References
Applications
	NMPC for Propofol Drug Dosing during Anesthesia Induction
		Introduction
		Patient Model
		The NEPSAC Approach to MPC
		Simulation Results during Induction Phase
			{\\it Ideal Case: No Modelling Errors}
			{\\it Real Case: Modelling Errors}
		Conclusion
		References
	Spacecraft Rate Damping with Predictive Control Using Magnetic Actuators Only
		Introduction
		Nonlinear Model Predictive Control
		Spacecraft Dynamics
		Rate Damping with NMPC
		Simulation Results
		Conclusions
		References
	Nonlinear Model Predictive Control of a Water Distribution Canal Pool
		Introduction
		Water Distribution Canal Pool Prototype
		Orthogonal Collocation
		NMPC for Hyperbolic Systems
		Results
		Conclusions
		References
	Swelling Constrained Control of an Industrial Batch Reactor Using a Dedicated NMPC Environment: $OptCon$
		Introduction
		Motivation and Process Model
		The NMPC Strategy and the OptCon Environment
			{\\it The Control Problem}
			{\\it The NMPC Formulation}
			{\\it Solution Strategy and Software Tool: OptCon}
			{\\it Real-Time Implementation}
		Results and Discussion
		Conclusions
		References
	An Application of Receding-Horizon Neural Control in Humanoid Robotics
		Introduction
		Receding Horizon Regulator: A Neural Approach
			{\\it From a Functional Optimization Problem to a Nonlinear Programming One}
			{\\it Solution of the Nonlinear Programming Problem by Stochastic Gradient}
		Results
		Conclusion
		References
	Particle Swarm Optimization Based NMPC: An Application to District Heating Networks
		Introduction
		Particle Swarm Optimization Based NMPC
			{\\it Classical PSO Algorithm}
			{\\it Application to NMPC}
		District Heating Networks Control
			{\\it District Heating Networks Modeling}
			{\\it Receding Horizon Based Control of District Heating Networks}
			{\\it Numerical Results}
		Conclusions and Discussion
		References
	Explicit Receding Horizon Control of Automobiles with Continuously Variable Transmissions
		Introduction
		Modeling
		Controller Design
			{\\it ERHC Design}
			{\\it Reference Signal Generator}
		Simulator Based Verification
		Conclusions
		References
Author Index