In this way, this work investigates the formulation of a Model Predictive Control (MPC) application developed within a Linear Parameter Varying (LPV) formalism, which serves as a model of the solar collector process. The proposed system is an adaptive MPC, developed with terminal set constraints ...
Thus, LPV models preserve the advantageous properties of LTI models, while being able to represent a large class of nonlinear systems [10]. LPV model-based control has been applied in many application areas (e.g., aerospace engineering, automotive applications, high-tech systems) as it benefits...
This paper presents a learning- and scenario-based model predictive control (MPC) design approach for systems modeled in linear parameter-varying (LPV) framework. Using input-output data collected from the system, a state-space LPV model with uncertainty quantification is first learned through the ...
Model predictive controlOff-line approachEstimation error setIn case when a nonlinear system is represented by quasi-LPV model with bounded disturbance, we adopt the parameter-dependent dynamic output feedback MPC (PDDOFMPC) with guaranteed quadratic boundedness and physical constraints. We pre-specify...
Fast Nonlinear MPC for Reference Tracking Subject to Nonlinear Constraints via Quasi-LPV RepresentationsModel predictive controlLinear parameter varying systemsNonlinear systemsConstrained controlEfficient algorithmsThis paper presents an approach to efficiently implement Nonlinear Model Predictive Control (NMPC) ...
Performance is assessed in terms of open-loop prediction on test data and of controlling the system via nonlinear model predictive control (MPC) based on the identified nonlinear state–space model. Introduction Nonlinear system identification has gained increasing popularity in recent years (Pillonetto...
Some nonlinear control algorithms such as sliding-mode control for fault-tolerant control [42], robust LPV control [43], decentralized sliding-mode control [44], and nonlinear model predictive control (MPC) [45] have been widely used. SMC (sliding-mode control) and BSC were implemented in [...
There are several nonlinear control methods in GTEs, such as LPV control, sliding mode control (SMC), adaptive control, and model predictive control (MPC). This section will detail the four control methods mentioned and introduce their applications in GTEs. 3.3.1 Linear parameter varying control...
model predictive controloff-line approachestimation error setIn case when a nonlinear system is represented by quasi-LPV model with bounded disturbance, we adopt the parameter-dependent dynamic output feedback MPC (PDDOFMPC) with guaranteed quadratic boundedness and physical constraints. We pre-specify...