Optimal Control Problem Research Papers (original) (raw)

The tremendous advances in wireless networks, mobile computing, and sensor networks, along with the rapid growth of small, portable and powerful computing devices, offers more and more opportunities for pervasive computing and... more

The tremendous advances in wireless networks, mobile computing, and sensor networks, along with the rapid growth of small, portable and powerful computing devices, offers more and more opportunities for pervasive computing and communications. This topic deals with cutting-edge research in various aspects related to the theory and practice of mobile computing or wireless and mobile networking. These aspects include architectures, algorithms, networks, protocols, modeling and performance issues, data management, ...

A pseudospectral method for generating optimal trajectories of linear and nonlinear constrained dynamic systems is proposed. The method consists of representing the solution of the optimal control problem by an mth degree interpolating... more

A pseudospectral method for generating optimal trajectories of linear and nonlinear constrained dynamic systems is proposed. The method consists of representing the solution of the optimal control problem by an mth degree interpolating polynomial, using Chebyshev nodes, and then discretizing the problem using a cell-averaging technique. The optimal control problem is thereby transformed into an algebraic nonlinear programming problem. Due to its dynamic nature, the proposed method avoids many of the numerical difficulties typically encountered in solving standard optimal control problems. Furthermore, for discontinuous optimal control problems, we develop and implement a Chebyshev smoothing procedure which extracts the piecewise smooth solution from the oscillatory solution near the points of discontinuities. Numerical examples are provided, which confirm the convergence of the proposed method. Moreover, a comparison is made with optimal solutions obtained by closed-form analysis and/or other numerical methods in the literature.

Chemical process control requires intelligent monitoring due to the dynamic nature of the chemical reactions and the non-linear functional relationship between the input and output variables involved. CSTR is one of the major processing... more

Chemical process control requires intelligent monitoring due to the dynamic nature of the chemical reactions and the non-linear functional relationship between the input and output variables involved. CSTR is one of the major processing unit in many chemical, pharmaceutical and petroleum industries as well as in environmental and waste management engineering. In spite of continuing advances in optimal solution techniques for optimization and control problems, many of such problems remain too complex to be solved by the known techniques. Thus, a heuristic approach is often a viable alternative. Neural Network models offer the most unified approach to building truly intelligent systems, which can provide good optimal solution for many applications. In this work we propose a hybrid (KohKal) neural network algorithm which is being used to model and solve a continuous stirred tank mixer/reactor (CSTM/R) problem which is non-linear and stochastic in nature. This hybrid algorithm is robust...

In the classical discrete-time mean-variance context, a method for portfolio optimisation using conditioning information was introduced in 2001 by Ferson and Siegel ([1]). The fact that there are many possible signals that could be used... more

In the classical discrete-time mean-variance context, a method for portfolio optimisation using conditioning information was introduced in 2001 by Ferson and Siegel ([1]). The fact that there are many possible signals that could be used as conditioning information, and a number of empirical studies that suggest measurable relationships between signals and returns, causes this type of portfolio optimisation to be of practical as well as theoretical interest. Ferson and Siegel obtain analytical formulae for the basic unconstrained portfolio optimisation problem. We show how the same problem, in the presence of a riskfree asset and given a single conditioning information time series, may be expressed as a general constrained infinite-horizon optimal control problem which encompasses the results in [1] as a special case. Variants of the problem not amenable to closed-form solutions can then be solved using standard numerical optimal control techniques. We extend the standard finite-hori...

Numerical methods and software packages for solving dynamic optimization or optimal control problems require a suitable initial estimation of the solution. This paper focuses on problems that arise in chemical processes described by... more

Numerical methods and software packages for solving dynamic optimization or optimal control problems require a suitable initial estimation of the solution. This paper focuses on problems that arise in chemical processes described by complex dynamics. We present a very simple method, based on Pontryagin’s Minimum Principle, to obtain an initial guess for the solution. Our method presents numerous advantages: it is very easy to programme, it allows a wide range of problems to be addressed, the computation time is very short, the initial guess is very close to the solution and is attracted to a global minimum.

Model predictive control is a form of control in which the current control action is obtained by solving, at each sampling instant, a" nite horizon open-loop optimal control problem, using the current state of the plant as the... more

Model predictive control is a form of control in which the current control action is obtained by solving, at each sampling instant, a" nite horizon open-loop optimal control problem, using the current state of the plant as the initial state; the optimization yields an ...

This paper presents a new way to derive an optimal control system for a specific optimisation problem, based on bond graph formalism. The procedure proposed concerns the optimal control of linear time invariant MIMO systems and can deal... more

This paper presents a new way to derive an optimal control system for a specific optimisation problem, based on bond graph formalism. The procedure proposed concerns the optimal control of linear time invariant MIMO systems and can deal with both cases of the integral performance index, these correspond to dissipative energy minimization and output error minimization. An augmented bond graph model is obtained starting from the bond graph model of the system associated with the optimal control problem. This augmented bond graph, consisting of the original model representation coupled to an optimizing bond graph, supplies, by its bicausal exploitation, the set of differential-algebraic equations that analytically give the solution to the optimal control problem without the need to develop the analytical steps of Pontryagin’s method. The proof uses the Pontryagin Maximum Principle applied to the port-Hamiltonian formulation of the system.

New first-order necessary conditions for optimality for control problems with pathwise state constraints are given. These conditions are a variant of a nonsmooth maximum principle which includes a joint subdifferential of the Hamiltonian... more

New first-order necessary conditions for optimality for control problems with pathwise state constraints are given. These conditions are a variant of a nonsmooth maximum principle which includes a joint subdifferential of the Hamiltonian – a condition called Euler–Lagrange inclusion (ELI). The main novelty of the result provided here is the ability to address state constraints while using an ELI. The ELI conditions have a number of desirable properties. Namely, they are, in some cases, able to convey more information about minimizers, and for the normal convex problems they are sufficient conditions of optimality. It is shown that these strengths are retained in the presence of state constraints.

In the past ten years the Web has attracted many educators for purposes of teaching and learning. The main advantage of the Web lies in its non-linear interaction. That is, students can have more control over their learning paths.... more

In the past ten years the Web has attracted many educators for purposes of teaching and learning. The main advantage of the Web lies in its non-linear interaction. That is, students can have more control over their learning paths. However, this freedom of control may cause, for some students problems such as disorientation, cognitive overload and control problems. To investigate these problems researchers have shifted there focus towards finding how is web-based learning used by learners with different characteristics and styles. In this paper, we outline the findings of some research on individual differences in the context of web-based learning. We also address how webbased learning systems can be adapted to learners ’ needs and styles. And then we suggest an adaptive web-based learning model, based on the analysis of findings obtained from these studies. Individual differences, web-based learning, instructional strategies, education computer, learners ’ needs, learning style

Based on a recently developed notion of physical realizability for quantum linear stochastic systems, we formulate a quantum LQG optimal control problem for quantum linear stochastic systems where the controller itself may also be a... more

Based on a recently developed notion of physical realizability for quantum linear stochastic systems, we formulate a quantum LQG optimal control problem for quantum linear stochastic systems where the controller itself may also be a quantum system and the plant output signal can be fully quantum. Such a control scheme is often referred to in the quantum control literature as "coherent feedback control.'' It distinguishes the present work from previous works on the quantum LQG problem where measurement is performed on the plant and the measurement signals are used as input to a fully classical controller with no quantum degrees of freedom. The difference in our formulation is the presence of additional non-linear and linear constraints on the coefficients of the sought after controller, rendering the problem as a type of constrained controller design problem. Due to the presence of these constraints our problem is inherently computationally hard and this also distinguish...

This paper is concerned with the state-constrained optimal control of the two- dimensional thermistor problem, a quasi-linear coupled system of a parabolic and elliptic PDE with mixed boundary conditions. This system models the heating of... more

This paper is concerned with the state-constrained optimal control of the two- dimensional thermistor problem, a quasi-linear coupled system of a parabolic and elliptic PDE with mixed boundary conditions. This system models the heating of a conducting material by means of direct current. Existence, uniqueness and continuity for the state system are derived by employing maximal elliptic and parabolic regularity.