Lecturer: Marin Kobilarov Consider the general setting where we are minimizing J = φ(x(t f), t f) + t f t 0 L(x(t), u(t), t)dt, (1) subject to: x(t 0) = x 0 , x(t f) and t f free (2) ˙ x(t) = f (x(t), u(t), t) (3) c(x(t), u(t), t) ≤ 0, for all t ∈ [t 0 , t f ] (4) ψ(x(t f), t f) ≤ 0, (5) We will consider three families of numerical methods for solving the optimal control problem: • dynamic prog...

In this paper, optimal distributed control of the time-dependent Navier-Stokes equations is considered. The control problem involves the minimization of a measure of the distance between the velocity field and a given target velocity field. A mixed numerical method involving a quasi-Newton algorithm, a novel calculation of the gradients and an inhomogeneous Navier-Stokes solver, to find the opt...

In order to obtain a solution to an optimal control problem‎, ‎a numerical technique based on state-control parameterization method is presented‎. ‎This method can be facilitated by the computation of performance index and state equation via approximating the control and state variable as a function of time‎. ‎Several numerical examples are presented to confirm the analytical findings and illus...

In this paper an approach based on evolutionary algorithms to find Pareto optimal pair of state and control for multi-objective optimal control problems (MOOCP)'s is introduced‎. ‎In this approach‎, ‎first a discretized form of the time-control space is considered and then‎, ‎a piecewise linear control and a piecewise linear trajectory are obtained from the discretized time-control space using ...

‎In the present paper‎, ‎optimal heating of temperature field which is modelled as a boundary optimal control problem‎, ‎is investigated in the uncertain environments and then it is solved numerically‎. ‎In physical modelling‎, ‎a partial differential equation with stochastic input and stochastic parameter are applied as the constraint of the optimal control problem‎. ‎Controls are implemented ...

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A new technique for solving polynomial nonlinear constrained optimal control problems is presented. The problem is reformulated into a parametric optimization problem, which in turn is solved in a two step procedure. First, in a pre-computation step, the equation part of the corresponding first order optimality conditions is solved for a generic value of the parameter. Relying on the underlying...

This paper gives a very brief overview of material of the short course entitled “Numerical Methods for Linear Control Systems” delivered by Biswa Nath Datta and Daniel Boley at the MTNS ’96. As with the short course, the paper has two parts. Part I, written by B. Datta deals with computational aspects of dense linear algebra problems in control theory, and part II, written by D. Boley deals wit...

Numerical algorithms for efficiently solving optimal control problems are important for commonly used advanced control strategies, such as model predictive control (mpc), but can also be useful for advanced estimation techniques, such as moving horizon estimation (mhe). In mpc, the control input is computed by solving a constrained finite-time optimal control (cftoc) problem on-line, and in mhe...

We present numerical methods for the solution of the optimal H∞ control problem. In particular, we investigate the iterative part often called the γ-iteration. We derive a method with better robustness in the presence of rounding errors than other existing methods. It remains robust in the presence of rounding errors even as γ approaches its optimal value. For the computation of a suboptimal co...