Dynamic optimization of state-dependent switched systems with free switching sequences

Abstract

Without necessarily assuming that switching sequences are fixed, a dynamic optimization method is proposed for optimal control of state-dependent switched systems. First, a parameterization method is developed to parameterize the switching instants and control vectors to facilitate the calculation of the gradient information, and then the original problem becomes a finite-dimensional mixed discrete–continuous nonlinear program as the switching sequence is discrete and the other variables are continuous. Secondly, the mixed discrete–continuous nonlinear program is transformed into an equivalent problem that contains only continuous variables by relaxing 0 and 1 discrete variables into continuous variables between 0 and 1 and adding proper linear and quadratic constraints. Thirdly, the formulas to compute the gradients of the objective function with respect to all the arguments are derived by solving the variational systems and a two-point boundary value differential algebraic equations (DAEs). Fourthly, an algorithm is proposed to locate a feasible point satisfying the Karush–Kuhn–Tucker (KKT) conditions to a specified tolerance of dynamic optimization of switched systems (DOSS) while guaranteeing feasibility of inequality path constraints, and the finite convergence of the algorithm is proved. Finally, the performance of the algorithm is analyzed via a numerical example.