This paper presents a new framework for controller robustness verification with respect to F-16 aircraft’s closed-loop performance in longitudinal flight. We compare the state regulation performance of a linear quadratic regulator (LQR) and a gain-scheduled linear quadratic regulator (gsLQR), applied to nonlinear open-loop dynamics of F-16, in presence of stochastic initial condition and parame...

<p><span>One of the most challenging aspects in nonlinear control a magnetic levitation (Maglev) system is to find an efficient algorithm achieve stability and accuracy closed-loop system. The challenge then develop linearizing maintain steel ball at desired position. In this paper, novel proposed, which consists Lyapunov direct method (LDM) model reference (MRC). function developed...

This paper studies the discrete-time sampled-data approximation of the input-constrained finite-horizon linear quadratic regulator problem. Explicit estimates for the error in the performance index rendered by the solution of a discrete-time approximation are provided. This result can be used to evaluate the level of sub-optimality of the sampled-data solution corresponding to a given discretis...

This paper is concerned with a proportional plus derivative (PD) state feedback control problem for discrete and continuous descriptor linear systems. We aim to design a (PD) state feedback controller which guarantees the stability of closed-loop system. The existence of such a controller is determined by developing a necessary and sufficient condition in terms of LMIs. Then, the desired PD sta...

In this paper, we consider the robust linear quadratic (LQ) control problem for a class of uncertain linear systems which are subject to a general type of integral quadratic constraints (IQCs). Both analysis and synthesis problems are considered in this paper. For the analysis problem, we determine if the system satisses a desired linear quadratic performance index for all admissible uncertaint...

In this paper, a Q-learning algorithm is proposed to solve the linear quadratic regulator problem of black box systems. The only has access input and output measurements. A Luenberger observer parametrization constructed using control new obtained from factorization utility function. An integral reinforcement learning approach used develop approximator structure. gradient descent update rule es...

Our purpose is to deal with quadratic operators acting between vector lattices of continuous mappings on a compact Hausdorff space. In our first main result we characterize quadratic-multiplicative operators, whereas in the second one we provide necessary and sufficient conditions for a quadratic operator to be proportional to the square of a continuous linear operator.