The time-optimal control of a distributed parameter system is derived in closed form. The class of systems studied in this work is distributed parameter systems whose dynamics are governed by the wave equation. A frequency domain approach is utilized to arrive at the time-optimal solution that is bang-off-bang. To corroborate the optimally of the control profile derived for the distributed para...

In this paper a new controller parameter adaptation rule is proposed. The proposed adaptation rule is derived via unfalsification control theory and gradient method without imposing many assumptions on the plant. Convergence of parameter is discussed. Numerical examples and simulation results are also provided.

A direct adaptive simultaneous perturbation stochastic approximation (DA SPSA) control system with a diagonal recurrent neural network (DRNN) controller is proposed. The DA SPSA control system with DRNN has simpler architecture and parameter vector size that is smaller than a feedforward neural network (FNN) controller. The simulation results show that it has a faster convergence rate than FNN ...

A decentralized, adaptive control law is presented to drive a network of mobile robots to an optimal sensing configuration. The control law is adaptive in that it uses sensor measurements to learn an approximation of the distribution of sensory information in the environment. It is decentralized in that it requires only information local to each robot. The controller is then improved upon by im...

This paper presents two indirect adaptive fuzzy control schemes for a class of uncertain continuous-time multiinput multi-output nonlinear dynamic systems. Within these schemes, fuzzy systems are employed to approximate the plant’s unknown nonlinear functions and robustifying control terms are used to compensate for approximation errors. By using a regularized matrix inverse, a stable well-defi...

This paper is concerned with adaptive stabilization of an undamped non-linear beam with disturbed outputs by boundary feedback control. The adaptive controller is constructed by the concept of high-gain adaptive feedback and the estimation mechanism for the unknown parameters of the measurement noise. The global existence and uniqueness of the solution of the closed-loop system is justified. Th...

This paper proposes a novel intelligent control scheme using type-2 fuzzy neural network type-2 FNN system. The control scheme is developed using a type-2 FNN controller and an adaptive compensator. The type-2 FNN combines the type-2 fuzzy logic system FLS , neural network, and its learning algorithm using the optimal learning algorithm. The properties of type-1 FNN system parallel computation ...

This paper addresses control design in networked control system by considering stochastic packet dropouts in the forward path of the control loop. The packet dropouts are modelled by mutually independent stochastic variables satisfying Bernoulli binary distribution. A sliding mode controller is utilized to overcome the adverse influences of stochastic packet dropouts in networked control system...

omotopy analysis method (ham) is a promising method for handling func-tional equations. recent publications proved the eectiveness of ham in solvingwide variety of problems in dierent elds. ham has a unique property whichmakes it superior to other analytic methods, this property is its ability to con-trol the convergence region of the solution series. in this work, we claried theadvantages ...

We apply retrospective cost adaptive control (RCAC) to a broadband disturbance rejection problem under limited modeling information and assuming that the performance variable is measured. The goal is to compare the asymptotic performance (that is, after convergence of the controller) of the adaptive controller with the performance of discrete-time LQG controller, which uses complete modeling in...