We justify the choice of a unitary horizon by using. Pdf lyapunov law based model predictive control scheme. Pdf lyapunovbased model predictive control for dynamic. Lyapunovbased stochastic nonlinear model predictive control. Safe modelbased reinforcement learning understand model and learning dynamics algorithm to safely acquire data and optimize task define safety, analyze a model for safety rkhs. The proposed economic mpc is designed via lyapunov based techniques and has two different operation modes. Lyapunov based model predictive control for dynamic positioning of autonomous underwater vehicles chao shen 1, yang shi, brad buckham abstractthis paper presents a novel lyapunov based mod. In order to identify a model around an unstable equilibrium point, the system is perturbed under closedloop operation.
Future control inputs and future plant responses are predicted using a system model and. Pdf lyapunovbased model predictive control of nonlinear. The main contribution of the proposed technique is. Secondly, a nonconservative stabilizing predictive control scheme is designed for the model of the closedloop can system using the concept of a flexible control lyapunov function lazar. Lyapunovbased economic model predictive control of nonlinear.
Lee school of chemical and biomolecular engineering center for process systems engineering georgia inst. Lyapunovbased model predictive control of nonlinear. Lyapunov based model predictive control for tracking of nonholonomic mobile robots under input constraints. Lyapunovbased model predictive control of nonlinear systems subject to. Asymptotic stability in the probabilistic sense is ensured by using a lyapunovbased control. Specifically, this method is based on a lyapunov function framework and provides a subset of the domain of attraction for the closedloop sta bility under the. The main idea is to formulate appropriate constraints in the predictive controllers optimization problem based on an existing lyapunovbased controller, in such a. A cost function of the proposed model predictive controller is. Lyapunovbased stochastic nonlinear model predictive. A population balance model of a typical continuous crystallizer.
A nonlinear model predictive control mpc is proposed for underactuated surface vessel usv with constrained invariant manifolds. In a recent work, 17, we proposed a lyapunovbased model predictive control formulation that provided guaranteed stability from an explicitly characterized set of initial conditions in the. Model predictive control college of engineering uc santa barbara. Request pdf lyapunovbased hybrid model predictive control for energy management of microgrids this paper presents an advanced control structure aimed at the optimal economic. Lyapunovbased model predictive control for tracking of. In control theory, a controllyapunov function is a lyapunov function for a system with control inputs. In order to take optimality considerations into account while.
Filtering and model predictive control of networked nonlinear systems by huiping li b. Ellipsoidal lyapunovbased hybrid model predictive control for mixed logical dynamical systems with a recursive feasibility guarantee alireza olama, mokhtar shasadeghi. Nonlinear model predictive control with terminal invariant. In rolf findeisen, frank allgwer, and lorenz biegler, editors, assessment and future directions of nonlinear model. This paper presents neural lyapunov mpc, an algorithm to alternately train a lyapunov neural network and a stabilising constrained model predictive controller mpc, given a neural. In order to take optimality considerations into account while designing saturated tracking controllers, a lyapunov based. This book offers readers a thorough and rigorous introduction to nonlinear model predictive control nmpc for discretetime and sampleddata systems. Due to the optimization essential, lmpc can explicitly consider the practical constraints on the real system and generate the best possible dp control. Lyapunovbased mpc incorporated a contractive constraint that bounds the lyapunov function of the mpc with a lyapunov function that was used to derive an emd compensation control law. Stabilization of nonlinear systems with state and control.
The problem of designing feedback control systems for nonlinear systems subject to timevarying. Abstractin this work, we focus on a class of general nonlinear systems and design a model predictive control mpc scheme which is capable of optimizing. It fulfills the gap between the existing centralized. Pdf on jun 1, 2017, abdul mannan dadu and others published lyapunov law based model predictive control scheme for grid connected three phase three level neutral point clamped inverter find. Lyapunovbased model predictive control for dynamic positioning of autonomous underwater vehicles chao shen 1, yang shi, brad buckham abstractthis paper presents a novel. Lyapunovbased model predictive control springerlink. Robust model predictive control of an input delayed. Lyapunovbased model predictive control of nonlinear systems subject to data losses. Lyapunovbased model predictive control of a puc7 grid. A complete solution manual more than 300 pages is available for course. A control lyapunov approach to predictive control of hybrid systems 1 discrete states.
To this end, a recently developed procedure for construction of constrained control lyapunov functions is utilized within a lyapunov. Lyapunov based model reference adaptive control for aerial. Pdf neural lyapunov model predictive control semantic. Lyapunovbased finite controlset model predictive control. Shaping the state probability density functions edward a. In this work, we propose the integration of a distributed model predictive control architecture with lyapunovbased model predictive control lmpc and lyapunovbased economic model. Unlimited viewing of the articlechapter pdf and any associated supplements and figures.
How we measure reads a read is counted each time someone views a publication summary such. This paper presents a novel lyapunovbased model predictive control lmpc framework for the dynamic positioning dp control of autonomous underwater vehicles auvs. Filtering and model predictive control of networked. Control solutions based on mpc are particularly powerful. In this work, we design a lyapunovbased model predictive controller lmpc for nonlinear systems subject to stochastic uncertainty. The main contribution of the proposed technique is the assurance of the closedloop stability and recursive feasibility, by a novel approach focused on mld models, using ellipsoidal terminal constraints and the. Lyapunovbased predictive control methodologies for.
Mpc model predictive control also known as dmc dynamical matrix control. Over the past few years significant progress has been achieved in the field of nonlinear model predictive control nmpc, also referred to as receding horizon control or moving horizon. The lyapunovbased controllers define a general class of feedback control laws which result in the closedloop system achieving negative definiteness of the drift of the lyapunov function derivative over the set. Lyapunovbased model predictive control of nonlinear systems. This result was further relaxed in 2,3 towards using a terminal inequality constraint on the. Preliminaries controlled dynamical system let us consider a discretetime, timeinvariant, deterministic dynamical system of the form. Flexible lyapunov function based model predictive direct. Lyapunov based predictive control of vehicle drivetrains. This paper presents a novel finite control set model predictive control fcsmpc strategy for solving the wellknown challenges in predictive control. Distributed lyapunovbased model predictive control for collision avoidance of multiagent formation. This paper studies the tracking problem of nonholonomic wheeled robots subject to control input constraints. Lyapunovbased model predictive control for dynamic. Lyapunovbased model predictive control of stochastic.
Model predictive control mpc 1, 2, 3 is an optimization based control method that can handle general nonlinear dynamics and constraints. This work focuses on state feedback, model predictive control of particulate processes subject to asynchronous measurements. Lyapunovbased predictive control methodologies for networked control systems. Distributed lyapunovbased model predictive control for. Lyapunovbased model predictive control of particulate. Lyapunovbased model predictive control lmpc scheme 3335 see also 36, 37 based on uniting receding horizon control with control lyapunov functions, because it allows for an. Lyapunovbased hybrid model predictive control for energy. Based on the analysis of mathematical model of overhead crane, this research. Model predictive control mpc is an optimal control strategy based on numerical optimization.
The proposed controller consists of a lyapunovbased hybrid model predictive control based on mixed logical dynamical mld framework. Lyapunovbased model predictive control of a puc7 gridconnected multilevel inverter. Lyapunov based model reference adaptive control for aerial manipulation matko orsag, christopher korpela, stjepan bogdan, and paul oh abstractthis paper presents a control. Nonlinear model predictive control theory and algorithms. Aimed at the special structure of usv, the invariant. Pdf in this work, we focus on model predictive control of nonlinear systems subject to data losses. Ellipsoidal lyapunovbased hybrid model predictive control. The problem considered in this chapter is to control a vehicle drivetrain. Techniques for uniting lyapunovbased and model predictive control. This work considers distributed predictive control of large. Neural lyapunov model predictive control preprint pdf available february 2020. Safeness indexbased economic model predictive control of. Predictive observer based lyapunov antiswing control for.
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