Closed-loop Control Policy Research Articles

A perturbation approach in determination of closed-loop optimal-fuzzy control policy for planetary landing mission

Development of time-optimal strategy for non-linear problem of planetary landing mission by using perturbation technique is investigated on two scenarios in this study. The first scenario includes finding an optimal control policy for descent in the variable gravitational field of the target planet analytically. In the second scenario, the optimal policy is derived by considering the effect of spacecraft mass variations in an analytic solution. To validate the accuracy of each generated policy, a numeric method such as steepest descent is employed. Afterwards, the fuzzy algorithm is followed to achieve the closed-loop guidance strategy for this non-linear system. The training process of the fuzzy system is based on the achieved perturbation solution of variable mass landing problem by utilizing a set of states-related non-dimensional variables for faster convergence rate. Finally, the lunar landing mission is demonstrated as a viable example of the non-linear planetary landing mission. Simulation results show that the presented optimal guidance laws are so effective which can be utilized in the real world spacecraft applications.

Optimization of Markov jump linear system with controlled modes jump probabilities

The optimal control of a Markov jump linear quadratic model with controlled jump probabilities of modes is investigated. Two kinds of mode control policies, i.e., open-loop control policy and closed-loop control policy, are considered. Using the concepts of policy iteration and performance potential, the sufficient condition needed for the optimal closed-loop control policy to perform better than the optimal open-loop control policy is proposed. The condition is helpful for the design of an optimal controller. Furthermore, an efficient algorithm to construct a closed-loop control policy, which is better than the optimal open-loop control policy, is given with policy iteration.

Sampling schedule design towards optimal drug monitoring for individualizing therapy

We study the individualization of therapy by simultaneously taking into account the design of sampling schedule and optimal therapeutic drug monitoring. The sampling schedule design in this work is to determine the number of samples, the sampling times, the switching time from the loading to the maintenance period, and the drug dosages. A closed-loop control policy is employed to determine the sampling schedule, and an advanced stochastic global optimization algorithm, which integrates the stochastic approximation and simulated annealing techniques, is implemented to search the optimal sampling schedule. A simulated one-compartment model of intravenous theophylline therapy is used to illustrate our method. This method can be readily extended to multiple compartment systems and allow incorporating other criteria of drug control. While currently the method is mainly of theoretical interest, it offers a starting point for practical applications and thus is hopefully of great value for the clinically individualizing therapy in the future.

Comparison between closed-loop and partial open-loop feedback control policies in long term hydrothermal scheduling

Stochastic dynamic programming has been. extensively used in the optimization of long term hydrothermal scheduling problems due to its ability to cope with the nonlinear and stochastic characteristics of such problems, and the fact that it provides a closed-loop feedback control policy. Its computational requirements, however, tend to be heavy even for systems with a small number of hydroplants, requiring some sort of modeling manipulation in order to be able to handle real systems. An alternative to closed-loop optimization is an approach that combines a deterministic optimization model with an inflow forecasting model in a partial open-loop feedback control framework. At each stage in this control policy, a forecast of the inflows during the period of planning is made, and an operational decision for the following stage is obtained by a deterministic optimization model. The present paper compares such closed-loop and partial open-loop feedback control policies in long term hydrothermal scheduling, using a single hydroplant system as a case study to focus the comparison on the feedback control performance. The comparison is made by simulation using data from historical and synthetical inflow sequences in the consideration of three different Brazilian hydroplants located in different river basins. Results have demonstrated that the performance of the partial open-loop feedback control policy is similar to that of the closed-loop control policy, and is even superior in dry streamflow periods.

Comparison between Closed-Loop and Partial Open-Loop Feedback Control Policies in Long-Term Hydrothermal Scheduling

Comparison between Closed-Loop and Partial Open-Loop Feedback Control Policies in Long-Term Hydrothermal Scheduling

Closed-loop soft-constrained time-optimal control of flexible space structures

We propose numerically efficient solutions for the openand closed-loop time-optimal soft-constrained control of a linear system representing a large flexible space structure. The open-loop solution is expressed in terms of the controllability Grammian matrix, for which we have obtained a closed-form expression for the undamped system. The qualitative dependence of the control on the initial state and the existence of many solutions satisfying the necessary conditions are shown. A nominal closed-loop control policy is subsequently formulated, but it is shown to be numerically expensive due to the nonuniqueness of extremal solutions. A continuation-based algorithm is proposed to alleviate the computational problem. Finally, the openand closedloop controls are shown to exhibit a saturation property reminiscent of the hard-constrained problem.

High-power switching regulator type DC-DC converters controlled by time-sharing high-frequency thyristor choppers with energy-storage and -transfer reactors

This paper is concerned with the latest technologies on high-power switching dc-dc converters controlled by time-sharing high-frequency thyristor chopper with energy -storage and -transfer reactor coupling links, which can operate over an ultrasonic chopping frequency region in the extent of 20KHz or more than 20KHz. The possible circuit configurations of new thyristor type switching step-up and down dc-dc converters relating to magnetic-power semiconductor devices and their unique features are described and discussed from a practical point of view. The general procedures of circuit analysis and performance evaluations to offer the desirable design data are presented, and the steady-state open-loop control characteristics and a closed-loop control policy are elucidated on the basis of the theoretical and experimental results. Thyristor type high-frequency switching step-up dc-dc converter using time-sharing control technique is also originally examined and discussed herein.

A preference-ordered discrete-gaming approach to air-combat analysis

An approach to one-on-one air-combat analysis is described which employs discrete gaming of a parameterized model featuring choice between several closed-loop control policies. A preference-ordering formulation due to Falco is applied to rational choice between outcomes: win, loss, mutual capture, purposeful disengagement, draw. Approximate optimization is provided by an active-cell scheme similar to Falco's obtained by a "backing up" process similar to that of Kopp. The approach is designed primarily for short-duration duels between craft with large-envelope weaponry. Some illustrative computations are presented for an example modeled using constant-speed vehicles and very rough estimation of energy shifts.

Closed-loop multilevel control of large nonlinear systems via invariant imbedding techniques

An efficient multilevel control technique is developed whereby the closed-loop control policy is derived for a wide class of large non-linear dynamic systems using the invariant imbedding algorithms. The basic idea behind the developed technique is the decomposition-coordination procedure of hierarchical multilevel systems theory. Modification of the local subproblems at the first level results in the requirement of solving essentially the dynamic state equations as well as the Ricatti-like ordinary matrix equations. At the second level the coordinator updates the intervention parameters using a conjugate gradient algorithm. A principal feature of the developed technique is reflected in the possibility of being implemented in a real-time. Computer simulation of practical system applications greatly supports the potentiality of the developed two-level optimization technique.

The singularity structure of optimal final-value control systems†

Abstract The structure of optimal final-value control systems is developed. It is shown that the closed-loop control policies for systems that can be transformed into MIPVCF have singularities that are finite-order poles. The exact singularity structure is developed for systems which are in MIPVCF. Using this structure, a partially closed-loop control policy is developed. This policy is optimal and allows the designer to set the maximum order of the feedback gain singularity in the system between tho closed-loop maximum and zero.