Approximate discrete maximum principle for the difference approximation of optimal periodic control problems

An optimal boundary control problem in a domain with oscillating boundary has been investigated in this paper. The controls are acting periodically on the oscillating boundary. The controls are applied with suitable scaling parameters. One of the major contribution is the representation of the optimal control using the unfolding operator. We then study the limiting analysis (homogenization) and obtain two limit problems according to the scaling parameters. Another notable observation is that the limit optimal control problem has three controls, namely, a distributed control, a boundary control, and an interface control. Copyright © 2016 John Wiley & Sons, Ltd.

Continuously operated autonomous processes governed by hereditary state equations are considered. The problem of improving of the optimal steady-state solution by periodic variations of control and state variables is discussed. A new formulation of the periodic hereditary control problem exploiting the heredity shift operator is presented, and its advantages are pointed out. This problem is solved iteratively by descent methods using variable metric ideas and implemented with the help of the Mathematica system. The proposed approach is illustrated by a simple example of ecological hereditary system.KeywordsHereditary autonomous processperiodic control problemheredity shift operatordescent methodMathematica system.

Trigonometric polynomials are used to approximate the state trajectory, the control and the functions in differential equations and in the criterion of the constrained optimal periodic control problem. Several discretized problems using such polynomials are proposed to approximate the problem considered. Sufficient conditions for the convergence of solutions of approximating problems to the optimal solution of the basic problem are given. The application to a class of optimal periodic control problems in chemical engineering is discussed.

This paper builds up two equivalence theorems for different kinds of optimal control problems of internally controlled Schrodinger equations. The first one is an equivalence of the minimal norm and the minimal time control problems where the target sets are the origin of the state space. (The minimal time control problems are also called the first type of optimal time control problems.) The second one is an equivalence of three optimal control problems: optimal target control problems, optimal norm control problems, and the second type of optimal time control problems.

1 A Survey on Computational Optimal Control.- Issues in the Direct Transcription of Optimal Control Problems to Sparse Nonlinear Programs.- Optimization in Control of Robots.- Large-scale SQP Methods and their Application in Trajectory Optimization.- Solving Optimal Control and Pursuit-Evasion Game Problems of High Complexity.- 2 Theoretical Aspects of Optimal Control and Nonlinear Programming.- Continuation Methods In Boundary Value Problems.- Second Order Optimality Conditions for Singular Extremals.- Synthesis of Adaptive Optimal Controls for Linear Dynamic Systems.- Control Applications of Reduced SQP Methods.- Time Optimal Control of Mechanical Systems.- 3 Algorithms for Optimal Control Calculations.- Second Order Algorithm for Time Optimal Control of a Linear System.- An SQP-type Solution Method for Constrained Discrete-Time Optimal Control Problems.- Numerical Methods for Solving Differential Games, Prospective Applications to Technical Problems.- Construction of the Optimal Feedback Controller for Constrained Optimal Control Problems with Unknown Disturbances.- Repetitive Optimization for Predictive Control of Dynamic Systems under Uncertainty.- Optimal Control of Multistage Systems Described by High-Index Differential-Algebraic Equations.- A New Class of a High Order Interior Point Method for the Solution of Convex Semiinfinite Optimization Problems.- A Structured Interior Point SQP Method for Nonlinear Optimal Control Problems.- 4 Software for Optimal Control Calculations.- Automated Approach for Optimizing Dynamic Systems.- ANDECS: A Computation Environment for Control Applications of Optimization.- Application of Automatic Differentiation to Optimal Control Problems.- OCCAL: A mixed symbolic-numeric Optimal Control CALculator.- 5 Applications of Optimal Control.- A Robotic Satellite with Simplified Design.- Nonlinear Control under Constraints of a Biological System.- An Object-Oriented Approach to Optimally Describe and Specify a SCADA System Applied to a Power Network.- Near-Optimal Flight Trajectories Generated by Neural Networks.- Performance of a Feedback Method with Respect to Changes in the Air-Density during the Ascent of a Two-Stage-To-Orbit Vehicle.- Linear Optimal Control for Reentry Flight.- Steady-State Modelling of Turbine Engine with Controllers.- Shortest Paths for Satellite Mounted Robot Manipulators.- Optimal Control of the Industrial Robot Manutec r3.

A trigonometric approximation scheme for optimal periodic control problems with state and control dependent delays is considered. The formulation of approximate problems is here adapted to a specific form of state equation with variable time delays. Sufficient conditions for the sequence of nearly optimal solutions of approximate problems to be a generalized minimizing sequence for the basic problem are given. The application of the method proposed to a periodic control of chemical reactors with recycles and controlled piping is pointed out.

A shooting type numerical optimization technique is developed by taking into account the particular characteristics of the periodic optimal control problem. The algorithm first closes a starting trajectory to one that satisfies all of the first order necessary conditions except the transversality condition associated with free period. Then a one-dimensional family is traced in the direction of improved cost criterion. A previously developed second order sufficiency condition is used to insure weak local optimality. The points where families of periodic paths cross (bifurcation points), which are related to the eigenvalues of the monodromy matrix, are used as starting points to trace new families. In this way a systematic investigation of the optimality of the numerous families that fill the state space is possible. A numerical example, which is composed of a two-degree of freedom Hamiltonian system, is constructed to yield periodic paths and to illustrate the method. Since this problem contains certain symmetries in the initial condition space that are used to simplify the numerical effort, an extensive investigation is performed demonstrating numerous theoretical results.

An efficient method is introduced for solving optimal control and optimal parameter selection problems of nonlinear differential-algebraic systems involving general constraints. These infinite dimensional problems are converted into the finite dimensional optimization problems by using the control parametrization technique. Moreover, the transformed time locations for the control variables are included in such problems. As a result, optimal control problems become acausal optimal parameter selection problems. A modified version of differential evolution is introduced to solve these problems. The integration of the penalty functions is used to ensure the solution onto the feasible domain of the problems. Two industrial systems, a chemical reactor and a robotics arm, are used to illustrate the robustness and effectiveness of the method. The control effects can be improved by selecting the proper time locations as observed from the simulated results.

This article presents a unified approach to simultaneous solution of optimization and optimal control problems in batch distillation, operating under different modes of operation: variable, constant, or optimal reflux. The simplified, computationally efficient short‐cut method and a novel algorithm to solve the optimal control problems in batch distillation is the basis of this unified approach. The short‐cut method identifies the feasible region of operation essential for optimization and optimal control problems, and provides analytical partial derivatives of the model parameters crucial to the solution.The new algorithm for the solution of optimal combination of the maximum principle and NLP optimization techniques. It circumvents the problems associated with the maximum principle approach (iterative solution of a two‐point boundary value problem, undounded control variables, and inability to handle the simultaneous optimization and optimal control problem), and the coupled ODE discretization‐NLP optimization scheme for nonlinear models (higher system nonlinearities, multiplicity of solutions, sensitivity of convergence to initial guesses). This algorithm reduces the dimensionality of the problem, and the nature of the algorithm allows a common platform to optimal solutions of different operating conditions. This article also shows that different categories of the optimal control problems in batch distillation essentially involve the solution of the maximum distillate problem.

This paper presents an equivalence theorem for three different kinds of optimal control problems, which are optimal target control problems, optimal time control problems, and optimal norm control problems. Controlled systems in this study are internally controlled heat equations. With the aid of this theorem, we establish an optimal norm feedback law and build up some explicit algorithms for solutions of optimal norm and optimal time control problems.

In this paper, an iterative adaptive dynamic programming (ADP) algorithm is developed to solve the optimal cooperative control problems for residential multi-battery systems. To avoid solving high-dimensional optimal control problems, we first constrain all the batteries at their worst performance, which transforms the multi-input optimal control problem into a single-input one. Based on the worst-performance optimal control law, the optimal cooperative control law for the residential multi-battery systems is obtained, where in each iteration, only a single-input optimization problem is implemented. Finally, numerical results are given to illustrate the performance of the developed algorithm.

Decomposition method for solving two optimal control problems and one optimization problem in batch fermentation is proposed. The problems are formulated based on a nonstructured mathematical model with slowly varying parameters and a finite cost criterion of maximum end production. Dependence of the model parameters on one physical or chemical parameter, which could easily be used as a control input is introduced analytically in the model equations and three model descriptions are obtained by nonlinear difference equations. Sensitivity functions of state trajectories towards slowly varying coefficients are introduced to account for model uncertainties. Based on them extended optimal control and optimization problems are formulated.

In this paper, we consider a class of optimal switching control problems with multiple time-delays and a cost on changing control and subject to terminal state constraints. A computational method involving three stages is developed to solve this class of optimal control problems. First, by parameterizing the control function with piecewise-constant functions, the optimal switching control problem is approximated by a sequence of finite-dimensional optimization problems, where the original switching times, the control heights and the control switching times are decision variables. Second, by introducing new variables, the total variation of the control variables is transformed into an equivalently smooth function. Third, we convert the constrained optimization problem into one only with box constraints by an exact penalty function method. The gradients of the cost functional are then derived, which can be combined with any gradient-based optimization method to determine the optimal solution. Finally, a numerical example is given to illustrate the effectiveness of the proposed algorithm.

Optimal control problems involving time-dependent decisions from a finite set have gained much interest lately, as they occur in practical applications with a high potential for optimization. A typical application is automobile driving with gear shifts. Recent work [7], [8], [9] lead to a tremendous speedup in computational times to obtain optimal solutions, allowing for more complex scenarios. In this paper we extend a benchmark mixed-integer optimal control problem to a more complicated case in which a periodic solution on a closed track is considered. Our generic solution approach is based on a convexification and relaxation of the integer control constraint. It may also be used for other objectives, such as energy minimization. Using the direct multiple shooting method we solve the new benchmark problem and present numerical results.

Quasistationary and High Frequency Periodic Control of Continuous Processes