This paper provides a novel solution to the problem of tuning linear output feedback model predictive control (MPC). A systematic tuning method that allows to obtain all the parameters of an unconstrained output feedback MPC based on disturbance model and observer is presented. It is shown that such tuning can be translated to a frequency domain control design problem, which can be solved using existing techniques. Experimental results on a quadrotor reference tracking problem show the effectiveness of the proposed MPC tuning method.</p
In control engineering, system identification is frequently used to create models from inputoutput d...
A two-layer approach for the auto-tuning of model predictive control (MPC) is proposed. The bottom l...
This technical report presents a method for designing a constrained output-feedback model predictive...
This paper provides a novel solution to the problem of tuning linear output feedback model predictiv...
This paper presents a frequency domain based approach to tune the penalty weights in the model predi...
This paper presents an intuitive on-line tuning strategy for linear model predictive control (MPC) a...
The effectiveness of model predictive control (MPC) in dealing with input and state constraints duri...
Model predictive control (MPC) strategies can efficiently deal with constraints on system states, in...
Research Doctorate - Electrical EngineeringThis thesis studies the use of model predictive control (...
This paper describes a new method for the design of model predictive control (MPC) using non-minimal...
This paper demonstrates a method for finding the cost function and state observer to be used in mode...
Model predictive control (MPC) is a successful technique which enables to deliver the desired goals...
The difficulties imposed by actuator limitations in a range of active vibration and noise control pr...
This paper presents an online tuning strategy for model predictive control. Specifically, the tuning...
Model predictive control (MPC) has been widely implemented in the motor because of its simple contro...
In control engineering, system identification is frequently used to create models from inputoutput d...
A two-layer approach for the auto-tuning of model predictive control (MPC) is proposed. The bottom l...
This technical report presents a method for designing a constrained output-feedback model predictive...
This paper provides a novel solution to the problem of tuning linear output feedback model predictiv...
This paper presents a frequency domain based approach to tune the penalty weights in the model predi...
This paper presents an intuitive on-line tuning strategy for linear model predictive control (MPC) a...
The effectiveness of model predictive control (MPC) in dealing with input and state constraints duri...
Model predictive control (MPC) strategies can efficiently deal with constraints on system states, in...
Research Doctorate - Electrical EngineeringThis thesis studies the use of model predictive control (...
This paper describes a new method for the design of model predictive control (MPC) using non-minimal...
This paper demonstrates a method for finding the cost function and state observer to be used in mode...
Model predictive control (MPC) is a successful technique which enables to deliver the desired goals...
The difficulties imposed by actuator limitations in a range of active vibration and noise control pr...
This paper presents an online tuning strategy for model predictive control. Specifically, the tuning...
Model predictive control (MPC) has been widely implemented in the motor because of its simple contro...
In control engineering, system identification is frequently used to create models from inputoutput d...
A two-layer approach for the auto-tuning of model predictive control (MPC) is proposed. The bottom l...
This technical report presents a method for designing a constrained output-feedback model predictive...