A Methodology for Designing a Nonlinear Feedback Controller via Parametric Optimization: State-Parameterized Nonlinear Programming Control

2021 ◽  
Author(s):  
Ying-Kuan Tsai ◽  
Richard J. Malak
Keyword(s):  
Nonlinear Programming ◽  
Parametric Optimization ◽  
Alternative Methods ◽  
Nonlinear Feedback ◽  
Optimal Control Strategy ◽  
Feedback Controllers ◽  
Highly Nonlinear ◽  
System States ◽  
A New Technique ◽  
Future Work

Abstract This paper introduces a new technique for designing nonlinear feedback controllers that can effectively and efficiently control nonlinear and unstable dynamical systems. The technique, called State-Parameterized Nonlinear Programming Control (sp-NLPC), constructs an optimal control strategy that is a function of dynamical system states. This is achieved through an offline parametric optimization process using the predictive parameterized Pareto genetic algorithm (P3GA) and representing the optimized state-varying policy using radial basis function (RBF) metamodeling. The sp-NLPC technique avoids many limitations of alternative methods, such as the need to make strong assumptions about model form (e.g., linearity) and the demands of online optimization processes. The proposed method is benchmarked on the problems of controlling the highly nonlinear and inherently unstable systems: single and double inverted pendulums on a cart. Performance and computational efficiency are compared to several competing control design techniques. Results show that sp-NLPC outperforms and is more efficient than competing methods. The parametric solution strategy for sp-NLPC lends itself to use in Control Co-Design (CCD). Such extensions are discussed as part of future work.

scholarly journals Convex optimization of nonlinear feedback controllers via occupation measures

2014 ◽  
Vol 33 (9) ◽  
pp. 1209-1230 ◽  
Author(s):  
Anirudha Majumdar ◽  
Ram Vasudevan ◽  
Mark M. Tobenkin ◽  
Russ Tedrake
Keyword(s):  
Convex Optimization ◽  
Nonlinear Feedback ◽  
Feedback Controllers ◽  
Occupation Measures

Nonlinear Stochastic Feedback Controllers for Vibratory Energy Harvesters With Power Flow Constraints

2011 ◽  
Author(s):  
Ian L. Cassidy ◽  
Jeffrey T. Scruggs ◽  
Sam Behrens
Keyword(s):  
Power Generation ◽  
Power Flow ◽  
Flow Direction ◽  
Average Power ◽  
Control Input ◽  
Stochastic Disturbances ◽  
Feedback Controllers ◽  
Energy Harvesters ◽  
System States ◽  
Feedback Laws

This study addresses the formulation of feedback controllers for stochastically-excited vibratory energy harvesters. Maximizing power generation from stochastic disturbances can be accomplished using LQG control theory, with the transducer current treated as the control input. For the case where the power flow direction is unconstrained, an electronic drive capable of extracting as well as delivering power to the transducer is required to implement the optimal controller. It is demonstrated that for stochastic disturbances characterized by second-order, bandpass-filtered white noise, energy harvesters can be passively tuned such that optimal stationary power generation only requires half of the system states for feedback in the active circuit. However, there are many applications where the implementation of a bi-directional power electronic drive is infeasible, due to the higher parasitic losses they must sustain. If the electronics are designed to be capable of only single-directional power flow (i.e., where the electronics are incapable of power injection), then these parasitics can be reduced significantly, which makes single-directional converters more appropriate at smaller power scales. The constraint on the directionality of power flow imposes a constraint on the feedback laws that can be implemented with such converters. In this paper, we present a sub-optimal nonlinear control design technique for this class of problems, which exhibits an analytically computable upper bound on average power generation.

scholarly journals Resistance of melon cultivars to Bemisia tabaci biotype B

2012 ◽  
Vol 30 (4) ◽  
pp. 600-606 ◽  
Author(s):  
Edson LL Baldin ◽  
José Paulo GF da Silva ◽  
Luiz Eduardo R Pannuti
Keyword(s):  
Bemisia Tabaci ◽  
Plant Resistance ◽  
Chemical Control ◽  
Alternative Methods ◽  
Silverleaf Whitefly ◽  
Trichome Density ◽  
Breeding Programs ◽  
Biotype B ◽  
Future Work ◽  
Bemisia Tabaci Biotype B

The silverleaf whitefly, Bemisia tabaci biotype B, is currently one of the most important pests of melon, causing direct and indirect damage to plants, and significantly reducing production in the field. Due to the need for alternative methods of chemical control in melon crops, the melon cultivars AF-646, AF-682, Don Luis, Frevo, Jangada, Nilo, Vereda, Amarelo Ouro and Hales Best were assessed at field, greenhouse, and laboratory trials for resistance to whitefly B. tabaci biotype B. In general, 'Hales Best' and 'Amarelo Ouro' were the most resistant, showing oviposition non-preference against whitefly. The trichome density is associated with the variation in oviposition on the cultivars and should be further investigated in future work. These results may be helpful in melon breeding programs, focusing on plant resistance to B. tabaci biotype B.

Judgments of Learning

2015 ◽  
Author(s):  
Matthew G. Rhodes
Keyword(s):  
Memory Performance ◽  
Methodological Approach ◽  
Judgments Of Learning ◽  
Alternative Methods ◽  
Theoretical Frameworks ◽  
Theoretical Approaches ◽  
History Of Research ◽  
History Of ◽  
Combine Information ◽  
Future Work

Several decades of research have examined predictions of future memory performance—typically referred to as judgments of learning (JOLs). In this chapter, I first discuss the early history of research on JOLs and their fit within a leading metacognitive framework. A common methodological approach has evolved that permits the researcher to investigate the correspondence between JOLs and memory performance, as well as the degree to which JOLs distinguish between information that is or is not remembered. Factors that influence each aspect of the accuracy of JOLs are noted and considered within theoretical approaches to JOLs. Thus far, research on JOLs had yielded a number of findings and promising theoretical frameworks that will continue to be refined. Future work will benefit by considering how learners combine information to arrive at a judgment, the implications of alternative methods of measuring JOLs, and the potential for JOLs to influence memory.

Investigation of the thermal conductivity of the pentatellurides (Hf1-XZrXTe5) using the parallel thermal conductance technique.

2000 ◽  
Vol 626 ◽  
Author(s):  
B. M. Zawilski ◽  
R. T. Littleton ◽  
Terry M. Tritt ◽  
D. R. Ketchum ◽  
J. W. Kolis
Keyword(s):  
Thermal Conductivity ◽  
Low Temperature ◽  
Radiation Effects ◽  
Thermal Conductance ◽  
Small Samples ◽  
Formidable Challenge ◽  
Conductance Technique ◽  
Small Needle ◽  
A New Technique ◽  
Future Work

ABSTRACTThe pentatelluride materials (Hf1-XZrXTe5) have recently garnered much interest as a potential low temperature thermoelectric material. Their power factor exceeds that of the current Bi2Te3 materials over the temperature range 150 K < T < 350 K. A formidable challenge has been the capability of measuring the thermal conductivity of small needle-like samples (2.0 × 0.05 × 0.1 mm3) such as pentatellurides (HfXZr1-XTe5) due to heat loss and radiation effects. However in order to fully evaluate any material for potential thermoelectric use, the determination of the thermal conductivity of the material is necessary. We have recently developed a new technique called the parallel thermal conductance (PTC) technique to measure the thermal conductivity of such small samples. In this paper we describe the PTC method and measurements of the thermal conductivity of the pentatelluride materials will be presented for the first time. The potential of these materials for low temperature thermoelectric applications will be further evaluated given these results as well as future work and directions will be discussed.

Three-Stage Feedback Controller Design With Applications to a Three Time-Scale System

2016 ◽  
Author(s):  
Verica Radisavljevic-Gajic ◽  
Milos Milanovic
Keyword(s):  
Time Scale ◽  
Controller Design ◽  
Feedback Controller ◽  
Linear Feedback ◽  
Feedback Controllers ◽  
Linear Feedback Controller ◽  
Full State ◽  
Full State Feedback ◽  
A New Technique ◽  
Natural Decomposition

A new technique was presented that facilitates design of independent full-state feedback controllers at the subsystem levels. Different types of local controllers, for example, eigenvalue assignment, robust, optimal (in some sense L1, H2, H∞, ...) may be used to control different subsystems. This feature has not been available for any known linear feedback controller design. In the second part of the paper, we specialize the results obtained to the three time-scale linear systems (singularly perturbed control systems) that have natural decomposition into slow, fast, and very fast subsystems. The proposed technique eliminates numerical ill-condition of the original three-time scale problems.

scholarly journals Visual Demand Evaluation Methods for In-Vehicle Interfaces

2010 ◽  
Vol 2 (4) ◽  
pp. 45-57 ◽  
Author(s):  
Michael Pettitt ◽  
Gary Burnett
Keyword(s):  
Economic Evaluation ◽  
Human Performance ◽  
Evaluation Method ◽  
Empirical Studies ◽  
Alternative Methods ◽  
Task Time ◽  
Level Model ◽  
Occlusion Technique ◽  
Vehicle Information ◽  
Future Work

The primary aim of the research presented in this paper is developing a method for assessing the visual demand (distraction) afforded by in-vehicle information systems (IVIS). In this respect, two alternative methods are considered within the research. The occlusion technique evaluates IVIS tasks in interrupted vision conditions, predicting likely visual demand. However, the technique necessitates performance-focused user trials utilising robust prototypes, and consequently has limitations as an economic evaluation method. In contrast, the Keystroke Level Model (KLM) has long been viewed as a reliable and valid means of modelling human performance and making task time predictions, therefore not requiring empirical trials or a working prototype. The research includes four empirical studies in which an extended KLM was developed and subsequently validated as a means of predicting measures relevant to the occlusion protocol. Future work will develop the method further to widen its scope, introduce new measures, and link the technique to existing design practices.

Design of nonlinear feedback controllers

1981 ◽  
Vol 26 (3) ◽  
pp. 730-733 ◽  
Author(s):  
E. Polak ◽  
D. Mayne
Keyword(s):  
Nonlinear Feedback ◽  
Feedback Controllers

scholarly journals Optimization of Allocation and Launch Conditions of Multiple Missiles for Three-Dimensional Collaborative Interception of Ballistic Targets

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Burak Yuksek ◽  
N. Kemal Ure
Keyword(s):  
Search Algorithm ◽  
Three Dimensional ◽  
Allocation Problem ◽  
Alternative Methods ◽  
Mixed Integer ◽  
Use Of Resources ◽  
Highly Nonlinear ◽  
Multiple Missiles ◽  
Miss Distance ◽  
And Control

We consider the integrated problem of allocation and control of surface-to-air-missiles for interception of ballistic targets. Previous work shows that using multiple missile and utilizing collaborative estimation and control laws for target interception can significantly decrease the mean miss distance. However, most of these methods are highly sensitive to initial launch conditions, such as the initial pitch and heading angles. In this work we develop a methodology for optimizing selection of multiple missiles to launch among a collection of missiles with prespecified launch coordinates, along with their launch conditions. For the interception we use 3-DoF models for missiles and the ballistic target. The trajectory of the missiles is controlled using three-dimensional extensions of existing algorithms for planar collaborative control and estimation laws. Because the dynamics of the missiles and nature of the allocation problem is highly nonlinear and involves both discrete and continuous variables, the optimization problem is cast as a mixed integer nonlinear programming problem (MINP). The main contribution of this work is the development of a novel probabilistic search algorithm for efficiently solving the missile allocation problem. We verify the algorithm by performing extensive Monte-Carlo simulations on different interception scenarios and show that the developed approach yields significantly less average miss distance and more efficient use of resources compared to alternative methods.

Optimisation of Crane Mechanisms – Selected Problems

2013 ◽  
Vol 542 ◽  
pp. 43-58 ◽  
Author(s):  
Stefan Chwastek
Keyword(s):  
Control Strategy ◽  
Parametric Optimization ◽  
State Of The Art ◽  
Geometric Parameters ◽  
Quadratic Functional ◽  
Optimal Control Strategy ◽  
Drive Control ◽  
Multi Stage ◽  
Intended Use ◽  
Selection Of

Design of state-of-the art crane mechanisms involves a multi-stage and multi-criterial optimization. Depending on the specificity and intended use of the machine, the optimal structure and dimensions of its mechanisms are sought as well as optimal algorithms for drive control and regulation, which requires the application of optimization criteria. It appears, however, that the approach relying on the minimum of a specifically formulated quadratic functional enables the selection of optimal geometric parameters of the mechanism and, besides, proves effective as the method of drive control. Furthermore, the geometric parameters of the mechanism can be optimized for its entire working range. Simplicity, universality and efficiency of the method are demonstrated on the example of a slewing one-link jib crane system. The search for the optimal control strategy of drive mechanisms is illustrated in the study that investigates an asymmetrically loaded platform suspended on ropes and people moving with respect to it during the hoisting phase. I. Parametric optimization of slewing mechanisms in one-link crane systems

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