CDC2000 Optimal Control of Hybrid Systems

Optimal Control of Hybrid Systems
Home Full List of Titles 1: Proceedings of CDC2000 Discrete Event Systems Control in Communication Systems Optimal Control and Applications I Optimisation Approaches and Methods Model Predictive Control Advances in Linear Estimation Stochastic and Uncertain Systems Nonlinear Control and Applications Nonlinear Estimation and Filtering Formation Control and its Applications New Approaches to Fuzzy Control Manufacturing Systems Automotive Applications Stability Issues in Hybrid Control Recent Advances in Stochastic Networks Optimal Control and Applications II Robust Controller Design - mu, L1 and H2 Constrained and Receding Horizon Control Identification and Control around the World Markov Decision Processes Nonlinear Optimisation Observers for Nonlinear Systems Motion Planning Neural / Fuzzy Stability and Control Motor Control Control of Quantum Phenomena I Hybrid Systems Methods Control in Communication Networks Robustness and Optimisation Bumpless Transfer, Antiwindup and Saturation Adaptive Control: Linear Systems Estimation and Closed Loop Identification Control of Markov Processes Nonlinear Filtering and Control Modelling, Identification and Validation of Nonlinear Systems Differential Geometric Control Theory for Mechanical Systems Nonlinear Output Feedback Control Pneumatics and Compression Systems Control of Quantum Phenomena II Stability of Hybrid Systems Performance Analysis in Communication Networks Adaptive Control of Nonlinear Systems LMI Methods in Design Robust Control of Time Delay Systems Subspace Identification Methods Nonlinear Stochastic Filtering and Estimation Bifurcations, Chaos and Control I New Progress in Synthesis of Nonlinear Systems I Implementation Issues of Sliding Mode Control Theory Control of Mixing in Shear Flows Novel Neural Network Control Techniques for Industrial Motion Control Systems Physiological Control Systems Optimal Control of Hybrid Systems Stochastic Models for Communication Networks Control and Stabilisation of Nonlinear Systems New Directions in Robust Control Linear Systems Theory Advanced Topics in Systems Theory Estimation in Action Bifurcations, Chaos and Control II New Progress in Synthesis of Nonlinear Systems II Numerical Design and Analysis Techniques for Nonlinear Systems Analysis and Control of Underactuated Systems Sliding Mode Control I Challenges in the Application of Control to Computer Systems Estimation and Diagnosis of Discrete Event Systems Communications and Games Optimal Control Stochastic Systems Model Reduction Methodologies Identification and Subspace Methods Applications of Nonlinear Adaptive Control Advances in Nonlinear Output Feedback Design The Behavioural Approach to Systems and Control Vision Based Estimation and Control: Recent Advances and Open Problems Agile Control of Military Operations Sliding Mode Control II Model-based Fault Diagnosis of Industrial Processes Discrete Event Systems / Petri Nets System Identification and Confidence Estimation New Approaches to H-Infinity Control I Probabilistic Approaches to Robust Control Time Delay System Stabilisation Identification Methods Controlled Stochastic Processes Output Feedback of Nonlinear Systems Topics in Nonlinear Stabilisation Mobile Robots: Tracking Control Robust Control of Nonlinear Systems Power Systems Stabilisation and Control Disk Drive Control Hybrid Control Applications Discrete Time Systems New Approaches to H-Infinity Control II Linear Systems with Saturating Actuators New Theories in Distributed Parameter Systems Applications of Estimation and Identification Stochastic Control and Tuning Methodologies Control of Nonlinear Systems Iterative Learning and Control Coordinating Robot Systems Nonlinear Time Varying Systems Novel Applications of Neural Networks Aerospace Applications Switched Systems Implicit and Descriptor Systems LQG Periodic Systems and Disturbances New Horizons for Distributed Parameter Systems State Estimation Learning and Neuro-Control Nonlinear Control and Stabilisation I Tracking Vision Servoing Controllability of Nonlinear Systems Control of Flexible Systems Electro-Mechanical Systems Robust Control Methods and Applications Fault Detection and Diagnosis Optimisation and Applications Robust Stability Analysis Numerical Methods in Control Filtering in Continuous Time Stochastic Systems Interplay between Control and Signal Processing Fault Detection and Analysis Nonlinear Dynamical Systems Nonlinear Time Delay Systems Computational Issues in Nonlinear Control Disturbance Rejection Process Control Industry Applications Linear Parameter Varying Systems Linear Control Systems Dynamic and Nonlinear Programming Model Reduction Applications New Techniques for Control and Systems: Numerical Linear Algebra Estimation and Identification using Hidden Markov Models Applications of Stochastic Control Topics in Linear Design Nonlinear Control and Stabilisation II Ambulatory Robot Systems Chaotic and Oscillatory Systems Biomedical System Control Integrated Control and CPU Scheduling Linear Design Techniques Adaptive Disturbance / Noise Compensation Nonlinear Model Predictive Control Sensitivity Design, Analysis and Limitations Analysis of Linear Systems Linear Matrix Inequalities in Design Lyapunov's 2nd Method Robotics: Tracking Control Lagrangian and Hamiltonian Theory Variable Structure Control Machine Vision Signal Processing Methods in Control Applied Nonlinear Control Author Index A B C D E F G H I J K L M N O P Q R S T U V W X Y Z	Optimal Controllers for Hybrid Systems: Stability and Piecewise Linear Explicit Form Authors: Alberto Bemporad, Francesco Borrelli, Manfred Morari, Volume: 1, Page 1810 Paper number 2601 Abstract: In this paper we propose a procedure for synthesizing piecewise linear optimal controllers for hybrid systems and investigate conditions for closed-loop stability. Hybrid systems are modeled in discrete-time within the mixed logical dynamical (MLD) framework introduced by Bemporad and Morari (1999), or, equivalently as piecewise affine (PWA) systems. A stabilizing controller is obtained by designing a model predictive controller (MPC), which is based on the minimization of a weighted 1/infinity-norm of the tracking error and the input trajectories over a finite horizon. The control law is obtained by solving a mixed-integer linear program (MILP) which depends on the current state. Although efficient branch and bound algorithms exist to solve MILPs, these are known to be NP-hard problems, which may prevent their on-line solution if the sampling-time is too small for the available computation power. Rather than solving the MILP on line, in this paper we propose a different approach where all the computation is moved off line, by solving a multiparametric MILP (mp-MILP). As the resulting control law is piecewise affine, on-line computation is drastically reduced to a simple linear function evaluation. An example of piecewise linear optimal control of the heat exchange system considered in Hedlund and Rantzer (1999) shows the potential of the method. CD002601.PDF (From Author) TOP A Hierarchical Decomposition Method for Optimal Control of Hybrid Systems Authors: Kagan Gokbayrak, Christos G. Cassandras, Volume: 1, Page 1816 Paper number 2602 Abstract: We consider optimal control problems for hybrid systems with a separable cost structure allowing us to decompose them into two components: a lower-level component with time-driven dynamics (describing the physical state of the system) interacting with a higher-level component with event-driven dynamics (describing the changes in the operating modes of the system). We develop a hybrid controller which aims at jointly optimizing the performance of both hierarchical components. We demonstrate this approach on two problems: a linear system switching from one operating mode to another and a multistage manufacturing system. In the first problem, the main difficulty is due to the coupling of the physical states across modes, whereas in the second it is due to the nondifferentiable event-driven dynamics. CD002602.PDF (From Author) TOP A Dynamic Programming Approach for Optimal Control of Switched Systems Authors: Xuping Xu, Panos J. Antsaklis, Volume: 1, Page 1822 Paper number 2603 Abstract: In optimal control problems of switched systems, in general, one needs to find both optimal continuous inputs and optimal switching sequences, since the system dynamics vary before and after every switching instant. In a previous paper, we proved that an optimal control problem can be posed as a two stage optimization problem under some additional assumptions. In general, the two stage optimization problem is still difficult to solve analytically. In this paper, we develop a search algorithm to explore the solution of the two stage optimization problem and find useful suboptimal solutions. This algorithm is motivated by the idea of dynamic programming which studies the value functions. The algorithm is used to determine suboptimal solutions for general switched linear quadratic problems CD002603.PDF (From Author) TOP Efficient Pruning of Search Trees in LQR Control of Switched Linear Systems Authors: Bo Lincoln, Bo Bernhardsson, Volume: 1, Page 1828 Paper number 2604 Abstract: This paper considers off-line optimization of a switching sequence for a given finite set of linear control systems and joint optimization of control laws. A linear quadratic full information criterion is optimized and dynamic programming is used to find the optimal switching sequence and control laws. The main result is a method for efficient pruning of the search tree to avoid combinatoric explosion. A method to prove optimality of a found candidate switch sequence and corresponding control laws is presented. CD002604.PDF (From Author) TOP Semidecidable Controller Synthesis for Classes of Linear Hybrid Systems Authors: Omid Shakernia, George J. Pappas, Shankar Sastry, Volume: 1, Page 1834 Paper number 2605 Abstract: A problem of great interest in the control of hybrid systems is the design of least restrictive controllers for reachability specifications. Controller design typically uses game theoretic methods to compute the region of the state space for which there exists a control such that for all disturbances, an unsafe set is not reached. In general, the computation of the controllers requires the steady state solution of a Hamilton-Jacobi partial differential equation which is very difficult to compute, if it exists. In this paper, we show that for special classes of hybrid systems where the continuous vector fields are linear, the controller synthesis problem is semi-decidable: There exists a computational algorithm which, if it terminates in a finite number of steps, will exactly compute the least restrictive controller. This result is achieved by a very interesting interaction of results from mathematical logic and optimal control. CD002605.PDF (From Author) TOP On-Line Techniques for Behavioral Programming Authors: Michael S. Branicky, Tor Arne Johansen, Idar Petersen, Emilio Frazzoli, Volume: 1, Page 1840 Paper number 2606 Abstract: Many control problems of interest can be cast as an optimal hybrid system control problems, wherein an objective function represents some global goals and the input at each time instant is a choice among a finite set of control laws. There are many approaches to solving such problems in the literature, all based on dynamic programming in some form or another, and all suffering from overwhelming computational complexity. Herein, we attempt to lower this complexity by examining techniques that take advantage of the underlying properties of the individual controllers among which we are switching. We call this process ``behavioral programming,'' since we are now attempting to perform dynamic programming at the more abstract level of behaviors of the constituent systems. We present our paradigm and discuss two arenas of its use: motion planning for autonomous agents and LQR with state and input constraints. Applications to helicopter and wheel slip control are used to illustrate problem-solving in each of these arenas, respectively. CD002606.PDF (From Author) TOP