Search results for "optimal"
showing 10 items of 706 documents
Feasibility Analysis For Constrained Model Predictive Control Based Motion Cueing Algorithm
2019
International audience; This paper deals with motion control for an 8-degree-of-freedom (DOF) high performance driving simulator. We formulate a constrained optimal control that defines the dynamical behavior of the system. Furthermore, the paper brings together various methodologies for addressing feasibility issues arising in implicit model predictive control-based motion cueing algorithms.The implementation of different techniques is described and discussed subsequently. Several simulations are carried out in the simulator platform. It is observed that the only technique that can provide ensured closed-loop stability by assuring feasibility over all prediction horizons is a braking law t…
Optimality Conditions for Non-Qualified Parabolic Control Problems
1994
We consider parabolic state constrained optimal control problems where the usual Slater condition is not necessarily satisfied. Instead, a weaker interiority property is assumed. Optimality conditions with a Lagrange multiplier are given. As an application we present an augmented Lagrangian algorithm. Numerical test results are included.
Optimizing MRI contrast with B1 pulses using optimal control theory
2016
The variety of achievable contrasts by MRI makes it a highly flexible and valuable diagnostic tool. Contrast results from relaxation time differences, which are intrinsic properties of each tissue. Using optimal control theory, one can control the obtained contrast by applying excitation pulses that bring the magnetization in a user-defined target state. Simulation results are presented to illustrate the feasibility and the flexibility of using optimal contrast pulses. The robustness to experimental variable parameters such as field inhomogeneities is also studied. Finally, an in-vitro contrast experiment is performed on a small-animal MRI showing a reasonable match with the simulation resu…
A novel clustering-based algorithm for solving spatially-constrained robotic task sequencing problems
2021
The robotic task sequencing problem (RTSP) appears in various forms across many industrial applications and consists of developing an optimal sequence of motions to visit a set of target points defined in a task space. Developing solutions to problems involving complex spatial constraints remains challenging due to the existence of multiple inverse kinematic solutions and the requirements for collision avoidance. So far existing studies have been limited to relaxed RTSPs involving a small number of target points and relatively uncluttered environments. When extending existing methods to problems involving greater spatial constraints and large sets of target points, they either require subst…
Optimal control of discrete-time interval type-2 fuzzy-model-based systems with D-stability constraint and control saturation
2016
This paper investigates the optimal control problem for discrete-time interval type-2 (IT2) fuzzy systems with pole constraints. An IT2 fuzzy controller is characterized by two predefined functions, and the membership functions and the premise rules of the IT2 fuzzy controller can be chosen freely. The pole assignment is considered, which is constrained in a presented disk region. Based on Lyapunov stability theory, sufficient conditions of asymptotic stability with an H ∞ performance are obtained for the discrete-time IT2 fuzzy model based (FMB) system. Based on the criterion, the desired IT2 state-feedback controller is designed to guarantee that the closed-loop system is asymptotically s…
A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms
2017
Evolutionary algorithms are widely used for solving multiobjective optimization problems but are often criticized because of a large number of function evaluations needed. Approximations, especially function approximations, also referred to as surrogates or metamodels are commonly used in the literature to reduce the computation time. This paper presents a survey of 45 different recent algorithms proposed in the literature between 2008 and 2016 to handle computationally expensive multiobjective optimization problems. Several algorithms are discussed based on what kind of an approximation such as problem, function or fitness approximation they use. Most emphasis is given to function approxim…
Opinion Dynamics and Stubbornness via Multi-Population Mean-Field Games
2016
This paper studies opinion dynamics for a set of heterogeneous populations of individuals pursuing two conflicting goals: to seek consensus and to be coherent with their initial opinions. The multi-population game under investigation is characterized by (i) rational agents who behave strategically, (ii) heterogeneous populations, and (iii) opinions evolving in response to local interactions. The main contribution of this paper is to encompass all of these aspects under the unified framework of mean-field game theory. We show that, assuming initial Gaussian density functions and affine control policies, the Fokker---Planck---Kolmogorov equation preserves Gaussianity over time. This fact is t…
Game Theoretic Decentralized Feedback Controls in Markov Jump Processes
2017
This paper studies a decentralized routing problem over a network, using the paradigm of mean-field games with large number of players. Building on a state-space extension technique, we turn the problem into an optimal control one for each single player. The main contribution is an explicit expression of the optimal decentralized control which guarantees the convergence both to local and to global equilibrium points. Furthermore, we study the stability of the system also in the presence of a delay which we model using an hysteresis operator. As a result of the hysteresis, we prove existence of multiple equilibrium points and analyze convergence conditions. The stability of the system is ill…
Decomposition and Mean-Field Approach to Mixed Integer Optimal Compensation Problems
2016
Mixed integer optimal compensation deals with optimization problems with integer- and real-valued control variables to compensate disturbances in dynamic systems. The mixed integer nature of controls could lead to intractability in problems of large dimensions. To address this challenge, we introduce a decomposition method which turns the original n-dimensional optimization problem into n independent scalar problems of lot sizing form. Each of these problems can be viewed as a two-player zero-sum game, which introduces some element of conservatism. Each scalar problem is then reformulated as a shortest path one and solved through linear programming over a receding horizon, a step that mirro…
Strategic Thinking under social influence: Scalability, stability and robustness of allocations
2016
This paper studies the strategic behavior of a large number of game designers and studies the scalability, stability and robustness of their allocations in a large number of homogeneous coalitional games with transferable utilities (TU). For each TU game, the characteristic function is a continuous-time stochastic process. In each game, a game designer allocates revenues based on the extra reward that a coalition has received up to the current time and the extra reward that the same coalition has received in the other games. The approach is based on the theory of mean-field games with heterogeneous groups in a multi-population regime.