This paper provides a survey of results in linear parameter-varying (LPV) control that have been validated by experiments and/or high-fidelity simulations. The LPV controller synthesis techniques employed the references this are briefly reviewed and compared. methods classified into polytopic, fractional transformation, gridding-based it is how each these approaches, can be carried out as convex optimization problem via finite number matrix inequalities (LMIs) for both parameter-independent...

A common problem in the context of linear parameter-varying (LPV) systems is how input-output (IO) models can be efficiently realized terms state-space (SS) representations. The originates from fact that LPV literature discrete-time identification and modeling often accomplished via IO model structures. However, to utilize these LPV-IO for control synthesis, commonly it required transform them into an equivalent SS form. In general, such a transformation complicated due phenomenon dynamic...

In this paper, robust design and tuning of power system stabilizers is considered. A new approach presented that utilizes recently developed techniques based on linear matrix inequalities (LMIs) for mixed H/sub 2//H/sub /spl infin//-design under pole region constraints. Uncertainty about plant parameters - due to variations in generation load patterns expressed the form a fractional transformation, systematic procedure constructing uncertainty representation proposed. The easily carried out...

LPV representations of given nonlinear or parameter dependent plants are usually not unique, and different models lead to achievable performance when LMI techniques used design controllers. To facilitate the construction suitable plant models, a method for automated generation affine has been developed is presented in this paper. Moreover, heuristic measure "quality" discussed. The proposed implemented Matlab illustrated with practical application: an model problem charge control car engine

This brief presents a method for an automated generation of improved representations linear parameter varying (LPV) systems, which is based on principal component analysis applied to typical scheduling trajectories. The procedure can help reduce the conservatism in controller design by finding tighter regions space parameters that contain set given In addition, this allows determine approximations LPV models with reduced number and facilitates systematic tradeoff between desired accuracy...

Nonlinear Model Predictive Control often suffers from excessive computational complexity, which becomes critical when fast plants are to be controlled. This papers presents an approach NMPC that exploits the quasi-LPV framework. For systems, scheduling variables determined by state and/or inputs. By calculating estimate of during prediction, prediction model can adapted estimated evolution in each step. Stability proposed algorithm is enforced offline solution optimization problem with...

In this article, event-triggered attitude consensus is considered for multiagent systems with guaranteed fixed-time convergence. Due to the non-Euclidean property of configuration space, more challenging achieve under sampled-data setting. An protocol and condition are proposed based on axis–angle representation. The reached if initial attitudes lie in local regions space. theoretical results reveal that settling time related interevent interval algebraic connectivity topology graph. We...

This paper presents an analytical non-linear model of the power controlling terminal a VSC HVDC (Voltage Source Converter High Voltage Direct Current) transmission system attached to weak (high impedance) AC network. In contrast standard 2 state VSC, proposed explicitly includes behaviour Phased Locked Loop and filter in system. When linearised around particular operating points, follows rigorous PSCAD more closely than model. The is therefore appropriate for use control design analysis...

Summary This article presents a nonlinear model predictive control (NMPC) approach based on quasi‐linear parameter varying (quasi‐LPV) representations of the and constraints. Stability proposed algorithm is ensured by offline solution an optimization problem with linear matrix inequality constraints in conjunction online terminal state constraint. Furthermore, iterative presented which NMPC can be handled solving series Quadratic Programs at each time step, this being highly computationally...

This study concentrates on the differential private distributed optimization problem with an event-triggered mechanism, whose goals include preserving privacy of agents' initial states and local cost functions improving communication efficiency. A mechanism is integrated into differentially subgradient-push algorithm then a new named as DP-ETSP designed, where real-time information propagation among agents avoided. Additionally, under proposed analysis mean-square consensus optimality over...

This paper concentrates on the torque commands for electric propulsion motors in a through road hybrid vehicle. By using linear quadratic gaussian controller, flat feed forward controller and desired value generator lateral vehicle dynamics are influenced. Understeering, oversteering, agility cornering speed can be optimized by proper design. A 14 degree of freedom model with Dugoff tire is used to simulate behaviour. The simulation results show improved increased handling driver compared...

In this paper we present an application of a recently developed strategy for robust distributed controller design formations and show way including performance requirements in the design. The proposed synthesis method guarantees stability all possible arbitrary fast changes communication topology. number agents formation can also be chosen arbitrarily. We illustrate results by performing simulation flight quad-rotor helicopters.

In this paper a practical approach to Nonlinear Model Predictive Control (NMPC) of robotic manipulator subject nonlinear state constraints is presented, which leads successful experimental implementation the control algorithm. The use quasi-LPV modelling at core scheme as complex optimization replaced by efficient Quadratic Programming (QP) exploiting quasi-linearity resulting model and constraints. obtained via velocity-based linearization results in an exact representation dynamics enables...

This brief presents a velocity-form nonlinear model predictive control (NMPC) scheme via velocity-based linearization. The main features of this approach are built-in offset-free in the presence disturbances, tracking piecewise constant, possibly unreachable, reference signals, and simple implementation, as parameterization all equilibria is not necessary. Furthermore, velocity form can be expressed quasi-linear parameter-varying (quasi-LPV) model, for which efficient online optimization...