© 2016 IEEE. A method based on a quantifier elimination algorithm is suggested for obtaining explicit model predictive control (MPC) laws for linear time invariant systems with quadratic objective and polytopic constraints. The structure of the control problem considered allows Weispfenning's 'quantifier elimination by virtual substitution' algorithm to be used. This is applicable to first order formulas in which quantified variables appear at most quadratically. It has much better practical computational complexity than general quantifier elimination algorithms, such as cylindrical algebraic decomposition. We show how this explicit MPC solution, together with Weispfenning's algorithm, can be used to check recursive feasibility of the syste...
We propose an algorithm for the effective solution of quadratic programming (QP) problems arising fr...
this paper we investigate some of the expressive power of this theory. We consider dynamical systems...
This paper presents a development for the model predictive control (MPC) of nonlinear systems employ...
© 2016 IEEE. A method based on a quantifier elimination algorithm is suggested for obtaining explici...
We present the application of real quantifier elimination to formal verification and synthesis of co...
In order to design and deploy a feedback controller in a real application, one must determine suitab...
The control based on online optimization, popularly known as model predictive control (MPC), has lon...
Abstract: Explicit piecewise linear (PWL) state feedback laws solving constrained linear model predi...
A model predictive control (MPC) scheme is deployed via the quadratic dissipativity constraint (QDC)...
This paper proposes a guaranteed feasible control allocation method based on the model predictive co...
This paper proposes an approximate explicit model predictive control design approach for regulating ...
Explicit solutions to constrained linear model-predictive control (MPC) problems can be obtained by ...
AbstractMany problems in control theory can be formulated as formulae in the first-order theory of r...
A method of solving the online optimization in model predictive control (MPC) of input-constrained l...
The problem of controlling a high-dimensional linear system subject to hard input and state constrai...
We propose an algorithm for the effective solution of quadratic programming (QP) problems arising fr...
this paper we investigate some of the expressive power of this theory. We consider dynamical systems...
This paper presents a development for the model predictive control (MPC) of nonlinear systems employ...
© 2016 IEEE. A method based on a quantifier elimination algorithm is suggested for obtaining explici...
We present the application of real quantifier elimination to formal verification and synthesis of co...
In order to design and deploy a feedback controller in a real application, one must determine suitab...
The control based on online optimization, popularly known as model predictive control (MPC), has lon...
Abstract: Explicit piecewise linear (PWL) state feedback laws solving constrained linear model predi...
A model predictive control (MPC) scheme is deployed via the quadratic dissipativity constraint (QDC)...
This paper proposes a guaranteed feasible control allocation method based on the model predictive co...
This paper proposes an approximate explicit model predictive control design approach for regulating ...
Explicit solutions to constrained linear model-predictive control (MPC) problems can be obtained by ...
AbstractMany problems in control theory can be formulated as formulae in the first-order theory of r...
A method of solving the online optimization in model predictive control (MPC) of input-constrained l...
The problem of controlling a high-dimensional linear system subject to hard input and state constrai...
We propose an algorithm for the effective solution of quadratic programming (QP) problems arising fr...
this paper we investigate some of the expressive power of this theory. We consider dynamical systems...
This paper presents a development for the model predictive control (MPC) of nonlinear systems employ...