Given any positive integer r, our objective is to develop a strategy for grouping the states of a n-node network into r ≤ n distinct non-overlapping groups. The criterion for this partitioning is defined as follows. First, a LQR controller is defined for the original n-node network. Then, a r-dimensional reduced-order network is created by imposing a projection matrix P on the n-node open-loop ...

An alternative method to formulate the stable Model Predictive Control (MPC) optimization problem, which allows controlling unstable systems with a large domain of attraction, is presented in this work. Usually, stability is guaranteed by means of an appropriate selection of a terminal cost, a terminal constraint, and a local unconstrained controller for predictions beyond the control horizon. ...

The design of MIMO PI controller is formulated as an LQR problem. The weighting matrices of the quadratic performance index are chosen so that tuning can be done for each inputoutput channel and for tradeoff between transient response and robustness with respect to modeling error. The number of tuning parameters is the same as that of a decentralized PI controller. A d&ign example is given to d...

An active control strategy for controlling impact response in composite plates is proposed. A linear quadratic regulator (LQR) controller is designed based on a reduced-order model that captures the essential dynamics of the system. Simulations results show that the proposed controller reduces the energy transferred to the structure. Thus, the possibility of impact-induced structural damage is ...

The problem of state feedback control design is conventionally handled by pole assignment or Linear Quadratic Regulator (LQR) method via Algebraic Riccati Equation (ARE). However, these methods still suffer from the disadvantage of trial and error approach for parameter tuning. To be specific, selecting the weighting matrices Q and R of LQR has to be done by trial and error approach. Hence to a...

Designing controller for the Multi Input Multi Output (MIMO) process is difficult because of the changes in process dynamics and interactions between process variables. This paper presents the approach to design a Linear Quadratic Gaussian (LQG) Controller for a multivariable process with a transmission zero using Linear Quadratic Regulator (LQR) and Kalman’s state estimation techniques. The pe...

In this paper, we derive the model of a three-magnet positioning device and design a nonlinear control that stabilizes it. The motivation of this work is to develop tools that may have practical significance to, e.g., photolithography and to create a challenging nonlinear control problem which can be used to test novel nonlinear control approaches. The nonlinear controller designed here transfo...

This paper has been designed optimize feed-back controller for dynamic response of the power systems. The power system consists of the infinite bus through a transmission line supplied by a synchronous machine and also multi machine power system. The effect of two control signals fed to the voltage regulator and the mechanical system is investigated. Robust Linear quadratic Gawssian (LQG) contr...

A hybrid proportional double derivative and linear quadratic regulator (PD2-LQR) controller is designed for altitude (z) attitude (roll, pitch, yaw) control of a quadrotor vehicle. The derivation mathematical model the formulated based on Newton–Euler approach. An appropriate controller’s parameter must be obtained to obtain superior performance. Therefore, we exploit advantages nature-inspired...