Robust constrained linear regulator problem

^** Email: mesquine{at}ucam.ac.ma^*** Email: a.benlamkadem{at}ucam.ac.ma The robust constrained state and control regulator problem isconsidered. Necessary and sufficient conditions of positiveinvariance are established. A linear programming approach ispresented in order to construct, for an uncertain constrainedlinear system, a stabilizing linear state feedback control.The control law transfers asymptotically to the origin any initialstate belonging to a given set, while constraints on the stateand the control vectors are respected.     

The regulator problem for linear systems with constrained control: an LMI approach

^** Email: benzaouia{at}ucam.ac.ma A new methodology of the partial eigenstructure assignment bystate feedback via linear matrix inequality (LMI) is extendedto obtain a solution of the constrained regulator problem forlinear continuous-time and discrete-time systems by using theLMI formulation.     

Optimal feedback control of bilinear systems

Feedback synthesis of optimal constrained controls for single-input bilinear systems is considered. Quadratic cost functionals (with and without quadratic control penalization) are modified by the inclusion of additional nonnegative state penalizing functions in the respective cost integrands. The latter functions are chosen so as to regularize the problems, in the sense that feedback solutions of particularly simple form are obtained. Finite and infinite time horizon problem formulations are treated, and associated aspects of feedback stabilization of bilinear systems are discussed.     

A GRASP for the biquadratic assignment problem

The biquadratic assignment problem (BiQAP) is a generalization of the quadratic assignment problem (QAP). It is a nonlinear integer programming problem where the objective function is a fourth degree multivariable polynomial and the feasible domain is the assignment polytope. BiQAP problems appear in VLSI synthesis. Due to the difficulty of this problem, only heuristic solution approaches have been proposed. In this paper, we propose a new heuristic for the BiQAP, a greedy randomized adaptive search procedure (GRASP). Computational results on instances described in the literature indicate that this procedure consistently finds better solutions than previously described algorithms.     

Optimal feedback control for constrained mechanical systems

An approach to minimize the control costs and ensuring a stable deviation control is the Riccati controller and we want to use it to control constrained dynamical systems (differential algebraic equations of Index 3). To describe their discrete dynamics, a constrained variational integrators [1] is used. Using a discrete version of the Lagrange-d’Alembert principle yields a forced constrained discrete Euler-Lagrange equation in a position-momentum form that depends on the current and future time steps [2]. The desired optimal trajectory (q_opt, p_opt) and according control input u_opt is determined solving the discrete mechanics and optimal control (DMOC) algorithm [3] based on the variational integrator. Then, during time stepping of the perturbed system, the discrete Riccati equation yields the optimal deviation control input u_R. Adding u_opt and u_R to the discrete Euler-Lagrange equation causes a structure preserving trajectory as both DMOC and Riccati equations are based on the same variational integrator. Furthermore, coordinate transformations are implemented (minimal, redundant and nullspace) enabling the choice of different coordinates in the feedback loop and in the optimal control problem. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Optimal control for the dam problem

Consider the variational inequality for the rectangular dam problem and assume that fluid can be withdrawn from the bottom at a rate proportional tok(x). Denote byp(x, y) the pressure of the fluid in the dam corresponding to a particular choice ofk. Consideringk(x) as a control variable varying in a class {0k(x)N, k(x)dxM}, we introduce the functionalJ(k)=g(y)p(x, y) whereg(y) is a given positive and monotone nondecreasing function. We characterize the controlsk ₀ which minimizeJ(k). This work is partially supported by National Science Foundation MCS-8300293     

Constructive solution of a bilinear control problem

We present an optimization method of a quantum control problem giving rise to a sequence of controls increasing monotonically the values of a cost functional. We first claim some results about the regularity of this cost functional. Those enable to extend an inequality due to ?ojasiewicz to the infinite dimensional case. Lastly, a sequence of inequalities proving the Cauchy character of the monotonic sequence is obtained, and we can also estimate the rate of convergence. The detailed proof will be given in [L. Baudouin, J. Salomon, Constructive solution of a bilinear quantum control problem, 2005, in preparation. [3]]. To cite this article: L. Baudouin, J. Salomon, C. R. Acad. Sci. Paris, Ser. I 342 (2006).     

Semidefinite programming hierarchies for constrained bilinear optimization

Mathematical Programming - We give asymptotically converging semidefinite programming hierarchies of outer bounds on bilinear programs of the form $${mathrm {Tr}}big [H(Dotimes E)big ]$$ ,...     

On the regulator problem for linear degenerate control systems

In this paper, we study the finite-time regulator problem for linear, autonomous, degenerate systems, i.e., systems described by the differential equation with det(K)=0. Two investigations of the regulator problem are presented, which depend on the quadratic cost associated with the differential equation.This work was performed under the auspices of the National Research Council of Italy, Gruppo Nazionale per l'Analisi Funzionale e le Sue Applicazioni, Rome, Italy.     

Dynamic mean-variance problem with constrained risk control for the insurers

In this paper, we study optimal reinsurance/new business and investment (no-shorting) strategy for the mean-variance problem in two risk models: a classical risk model and a diffusion model. The problem is firstly reduced to a stochastic linear-quadratic (LQ) control problem with constraints. Then, the efficient frontiers and efficient strategies are derived explicitly by a verification theorem with the viscosity solutions of Hamilton–Jacobi–Bellman (HJB) equations, which is different from that given in Zhou et al. (SIAM J Control Optim 35:243–253, 1997). Furthermore, by comparisons, we find that they are identical under the two risk models. This work was supported by National Basic Research Program of China (973 Program) 2007CB814905 and National Natural Science Foundation of China (10571092).     

Optimal synthesis in a control problem with Lipschitz input data

We propose a numerical algorithm for constructing an optimal synthesis in the control problem for a nonlinear system on a fixed time interval. We estimate the difference between the values of the cost functional on optimal trajectories and on the trajectories constructed according to this algorithm. The operation of the algorithm is illustrated by solving model examples on the plane.     

Optimal synthesis in a two-dimensional problem with asymmetric constraints on the control

A two-dimensional optimal control problem is considered on the assumption that the terminal time of the process is not fixed and the integral objective functional depends on a parameter. Asymmetric constraints are imposed on the control parameter. Two cases are considered: constraints of the same sign and constraints of different signs. In the case of constraints of different signs, if the parameters of the problem satisfy certain relations, one obtains chattering control, alternating with a control with two switchings and a first-order singular are when these relations are violated. In the case of sign-definite control the controllability domain is part of the plane bounded by two semiparabolas. Three types of control law are then possible, in two of which the system will hit the boundary of the controllability domain and move along it, while the third features a first-order singular are. As the parameter of the problem is varied, the phase portrait undergoes evolution and one of these three types is interchanged with another. The optimality of these control laws is rigorously established using a dynamic programming method.     

Optimal times for constrained nonlinear control problems without local controllability

We study optimal times to reach a given closed target for controlled systems with a state constraint. Our goal is to characterize these optimal time functions in such a way that it is possible to compute them numerically and we do not need to compute trajectories of the controlled system. In this paper we provide new results using viability theory. This allows us to study optimal time functions free from the controllability assumptions classically made in the partial differential equations approach.     

Optimal control problem for viscous Cahn-Hilliard equation

This paper is concerned with the viscous Cahn-Hilliard equation, which arises in the dynamics of viscous first order phase transitions in cooling binary solutions. The optimal control under boundary condition is given and the existence of optimal solution to the equation is proved.     

Optimal control problem for an automatic transmission

Attention is given to the control-theoretic aspects of the operation of an automatic transmission for a road vehicle. A differential game model for vehicle control is presented and analyzed; furthermore, the approach leads to a synthesis of the optimal feedback strategy for the selection of the transmission ratio of the automatic gearbox.This work was partially supported by a grant from Control Data.     

Optimal constrained control of a linear nonstationary end-position control system

We obtain simple expressions for a control action of an end-position linear nonstationary system that is optimal according to a quadratic criterion and has a constrained control. We also consider the special case of a system with one output coordinate and scalar optimal control with feedback requiring knowledge of the current state of the system at all times and the weight function from the point of application of the control to the output coordinate. It is assumed that the external perturbation is known on the entire interval of time during which the system functions. The proposed approach has been successfully used in synthesizing practical algorithms for control of moving objects. Translated fromDinamicheskie Sistemy, No. 13, 1994, pp. 36–39.     

The regulator problem for parabolic equations with Dirichlet boundary control

This paper considers the regulator problem for a parabolic equation (generally unstable), defined on an open, bounded domain , with control functionu acting in the Dirichlet boundary condition: minimize the quadratic functional which penalizes theL ₂(0, ; L₂())-norm of the solutiony and theL ₂(0, ; L₂())-norm of the Dirichlet controlu. The paper is divided in two parts. Part I derives, in a constructive way, the algebraic Riccati equation satisfied by the candidate Riccati operator solution (unique in our case) and, moreover, studies the regularity properties of the optimal pairu ⁰, y⁰. Part II studies a Galerkin approximation of the regulator problem. It shows first the uniform analyticity and the uniform exponential stability of the underlying discrete (approximating) semigroups. Then it establishes the desired convergence properties, in particular, pointwise Riccati operators convergence and, as a final goal, convergence of the original dynamics acted upon by the discrete feedbacks.Research partially supported by the National Science Foundation under Grant DMS-8301668.