Publications (10)0 Total impact
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Article: Predictive Control for Polynomial Systems Subject to State and Input Constraints.
Automatisierungstechnik. 01/2011; 59:479-488. -
Conference Proceeding: MPC with one Free Control Action for Constrained LPV Systems.
Proceedings of the IEEE International Conference on Control Applications, CCA 2010, Yokohama, Japan, September 8-10, 2010; 01/2010 -
Chapter: LMI-Based Model Predictive Control for Linear Discrete-Time Periodic Systems
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ABSTRACT: This paper presents a newmodel predictive control (MPC) scheme for linear constrained discrete-time periodic systems. In each period of the system, a new periodic state feedback control law is computed via a convex optimization problem that minimizes an upper bound on an infinite horizon cost function subject to state and input constraints. The performance of the proposed model predictive controller, that stabilizes the discrete-time periodic system if it is initially feasible, is illustrated via an example.05/2009: pages 99-108; -
Chapter: Spacecraft Rate Damping with Predictive Control Using Magnetic Actuators Only
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ABSTRACT: A nonlinear model predictive control (NMPC) approach for rate damping control of a low Earth orbit satellite in the initial acquisition phase is proposed. The only available actuators are magnetic coils which impose control torques on the satellite in interaction with the Earth’s magnetic field. In the initial acquisition phase large rotations and high angular rates, and therefore strong nonlinearities must be dealt with. The proposed NMPC method, which is shown to guarantee closed-loop stability, efficiently reduces the kinetic energy of the satellite while satisfying the constraints on the magnetic actuators. Furthermore, due to the prediction of future trajectories, the negative effect of the well-known controllability restriction in magnetic spacecraft control is minimized. It is shown via a simulation example that the obtained closed-loop performance is improved when compared to a classical P-controller.05/2009: pages 511-520; -
Chapter: Enlarging the Terminal Region of NMPC with Parameter-Dependent Terminal Control Law
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ABSTRACT: Nominal stability of a quasi-infinite horizon nonlinear model predictive control (QIH-NMPC) scheme is obtained by an appropriate choice of the terminal region and the terminal penalty term. This paper presents a new method to enlarge the terminal region, and therefore the domain of attraction of the QIH-NMPC scheme. The proposed method applies a parameter-dependent terminal controller. The problem of maximizing the terminal region is formulated as a convex optimization problem based on linear matrix inequalities. Compared to existing methods using a linear time-invariant terminal controller, the presented approach may enlarge the terminal region significantly. This is confirmed via simulations of an example system.05/2009: pages 69-78; -
Chapter: Receding Horizon Control for Linear Periodic Time-Varying Systems Subject to Input Constraints
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ABSTRACT: In this paper, a receding horizon control scheme able to stabilize linear periodic time-varying systems, in the sense of asymptotic convergence, is proposed. The presented approach guarantees that input constraints are always satisfied if the optimization problem is feasible at the initial time. Unlike the usual approaches for linear systems, a finite prediction horizon is used. Stability is ensured by choosing a time-varying terminal cost, that approximates an infinite horizon cost and is related to the solution of a Matrix Riccati differential equation. Sufficient conditions on the system for the design of its corresponding time-varying terminal region are derived, such that it is also possible to incorporate input constraints. This region is based on the time-varying terminal cost and can be calculated off-line.05/2009: pages 109-117; -
Chapter: An NMPC Approach to Avoid Weakly Observable Trajectories
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ABSTRACT: Nonlinear systems can be poorly or non-observable along specific state and output trajectories or in certain regions of the state space. Operating the system along such trajectories or in such regions can lead to poor state estimates being provided by an observer. Such trajectories should be avoided if used for state feedback control or monitoring purposes. In this paper, we outline a possible approach to avoid weakly observable trajectories in the frame of nonlinear model predictive control (NMPC). To illustrate the practical relevance and applicability, the proposed controller is used for an emergency collision avoidance maneuver for passenger cars.01/1970: pages 275-284; -
Article: Offline NMPC for continuous-time systems using sum of squares
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ABSTRACT: An offline nonlinear model predictive control (NMPC) approach for continuous time nonlinear systems sub-ject to input and state constraints is presented. The approach deals with nonlinear systems which can be represented by polynomial parameter-varying systems. Since the applicability of NMPC is often limited by the speed at which an optimization problem can be solved online, we propose an NMPC scheme with drastically reduced online computational burden. The basic idea involves the offline computation of nested invariant sets and associated feedback laws by solving a convex optimiza-tion problem subject to sum of squares (SOS) constraints via semidefinite programming (SDP). Online, a search algorithm is executed to determine the feedback law suitable for the current state. The resulting offline NMPC controller guarantees stability and constraint satisfaction. Its applicability and effectiveness is shown by means of simulation of an example system. -
Article: Stability analysis of periodically time-varying systems using periodic Lyapunov functions
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ABSTRACT: This paper proposes a novel approach to stability analysis of discrete-time nonlinear periodi-cally time-varying systems. The contributions are as follows. Firstly, a relaxation of standard Lyapunov conditions is derived. This leads to a less conservative Lyapunov function that is required to decrease at every period rather than at each time instant. Secondly, for linear periodic systems with constraints, we show that compared to standard Lyapunov theory, the novel stability concept yields a larger estimate of the region of attraction. An example illustrates the effectiveness of the developed theory. -
Article: Avoidance of Poorly Observable Trajectories: A predictive control perspective
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ABSTRACT: Nonlinear systems can be poorly or non-observable along specific state and output trajectories or in certain regions of the state space. Operating the system along such trajectories or in such regions can lead to poor state estimates being provided by an observer. Such trajectories should be avoided if used for state-feedback control or monitoring purposes. In this paper, we outline two possible approaches to avoid weakly observable trajectories in the frame of nonlinear predictive control. The first approach is based on the use of a term in the cost functional that penalizes weakly observable trajectories and thus leads to avoidance of weakly or non-observable regions of operation. In the second approach, the observer error dynamics are directly considered in the prediction. Large state estimation errors lead to a large penalization in the cost functional and are thus avoided. The approaches are exemplified by considering an example system.
