Fast explicit nonlinear model predictive control via multiresolution function approximation with guaranteed stability
نویسندگان
چکیده
In this paper an algorithm for nonlinear explicit model predictive control is introduced based on multiresolution function approximation that returns a low complexity approximate receding horizon control law built on a hierarchy of second order interpolets. Feasibility and stability guarantees for the approximate control law are given using reachability analysis, where interval methods are used to construct a capture basin (feasible region). A constructive algorithm is provided that combines adaptive function approximation with interval methods to build a receding horizon control law that is suboptimal, yet with a region of guaranteed feasibility and stability. The resulting control law is built on a grid hierarchy that is fast to evaluate in real-time systems.
منابع مشابه
Controlling Nonlinear Processes, using Laguerre Functions Based Adaptive Model Predictive Control (AMPC) Algorithm
Laguerre function has many advantages such as good approximation capability for different systems, low computational complexity and the facility of on-line parameter identification. Therefore, it is widely adopted for complex industrial process control. In this work, Laguerre function based adaptive model predictive control algorithm (AMPC) was implemented to control continuous stirred tank rea...
متن کاملMin-max Nonlinear Model Predictive Control with Guaranteed Input-to-State Stability
In this paper we consider discrete-time nonlinear systems that are affected, possibly simultaneously, by parametric uncertainties and disturbance inputs. The min-max model predictive control (MPC) methodology is employed to obtain a controller that robustly steers the state of the system towards a desired equilibrium. The aim is to provide a priori sufficient conditions for robust stability of ...
متن کاملPredictive Visual Feedback Control with Eye-In/to-Hand Configuration Via Stabilizing Receding Horizon Approach
This paper investigates vision based robot control via a receding horizon control strategy for an eye-in/to-hand system, as a predictive visual feedback control. Firstly, the dynamic visual feedback system with the eye-in/to-hand configuration is reconstructed in order to improve the performance of the estimation. Next, a stabilizing receding horizon control for the 3D dynamic visual feedback s...
متن کاملPresentation of quasi-linear piecewise selected models simultaneously with designing of bump-less optimal robust controller for nonlinear vibration control of composite plates
The idea of using quasi-linear piecewise models has been established on the decomposition of complicated nonlinear systems, simultaneously designing with local controllers. Since the proper performance and the final system close loop stability are vital in multi-model controllers designing, the main problem in multi-model controllers is the number of the local models and their position not payi...
متن کاملPosition Control Improvement of Permanent Magnet Motor Using Model Predictive Control
Fast and accurate transient response is the main requirement in electric machine position control. Conventional cascade control structure has sluggish response due to the limitation of inner control loop bandwidth. In this paper, in order to decrease the Permanent Magnet Synchronous Motor (PMSM) transient response time it can be used reference model using feed-forward signals. In this structure...
متن کامل