scholarly journals An iterative method for time optimal control of dynamic systems

2011 ◽  
Vol 21 (1) ◽  
pp. 5-23 ◽  
Author(s):  
Navvab Kashiri ◽  
Mohammad Ghasemi ◽  
Morteza Dardel
Keyword(s):  
Optimal Control ◽  
Iterative Method ◽  
Dynamic Systems ◽  
Minimum Principle ◽  
Minimum Energy ◽  
Optimal Solution ◽  
Initial Guess ◽  
Open Loop ◽  
Time Optimal Control ◽  
Time Optimal

An iterative method for time optimal control of dynamic systemsAn iterative method for time optimal control of a general type of dynamic systems is proposed, subject to limited control inputs. This method uses the indirect solution of open-loop optimal control problem. The necessary conditions for optimality are derived from Pontryagin's minimum principle and the obtained equations lead to a nonlinear two point boundary value problem (TPBVP). Since there are many difficulties in finding the switching points and in solving the resulted TPBVP, a simple iterative method based on solving the minimum energy solution is proposed. The method does not need finding the switching point so that the resulted TPBVP can be solved by usual algorithms such as shooting and collocation. Also, since the solution of TPBVPs is sensitive to initial guess, a short procedure for making the proper initial guess is introduced. To this end, the accuracy and efficiency of the proposed method is demonstrated using time optimal solution of some systems: harmonic oscillator, robotic arm, double spring-mass problem with coulomb friction and F-8 aircraft.

Time-Optimal Control of Flexible Robots Made Robust Through Wave-Based Feedback

2010 ◽  
Vol 133 (1) ◽  
Author(s):  
William J. O’Connor ◽  
David J. McKeown
Keyword(s):  
Optimal Control ◽  
Control Strategy ◽  
Robustness Analysis ◽  
Optimal Solution ◽  
Open Loop ◽  
Time Optimal Control ◽  
System Model ◽  
Optimal Control Strategy ◽  
Modeling Errors ◽  
Time Optimal

This paper presents a new, robust, time-optimal control strategy for flexible manipulators controlled by acceleration-limited actuators. The strategy is designed by combining the well-known, open-loop, time-optimal solution with wave-based feedback control. The time-optimal solution is used to design a new launch wave input to the wave-based controller, allowing it to recreate the time-optimal solution when the system model is exactly known. If modeling errors are present or a real actuator is used, the residual vibrations, which would otherwise arise when using the time-optimal solution alone, are quickly suppressed due to the additional robustness provided by the wave-based controller. A proximal time-optimal response is still achieved. A robustness analysis shows that significant improvements can be achieved using wave-based control in conjunction with the time-optimal solution. The implications and limits are also discussed.

Time-optimal control of multiple unmanned aerial vehicles with human control input

2019 ◽  
Vol 12 (1) ◽  
pp. 138-152 ◽  
Author(s):  
Tao Han ◽  
Bo Xiao ◽  
Xi-Sheng Zhan ◽  
Jie Wu ◽  
Hongling Gao
Keyword(s):  
Optimal Control ◽  
Optimal Control Problems ◽  
Minimum Principle ◽  
Time Optimal Control ◽  
Control Problems ◽  
Control Input ◽  
Content Type ◽  
Human Control ◽  
Time Optimal ◽  
The Cost

Purpose The purpose of this paper is to investigate time-optimal control problems for multiple unmanned aerial vehicle (UAV) systems to achieve predefined flying shape. Design/methodology/approach Two time-optimal protocols are proposed for the situations with or without human control input, respectively. Then, Pontryagin’s minimum principle approach is applied to deal with the time-optimal control problems for UAV systems, where the cost function, the initial and terminal conditions are given in advance. Moreover, necessary conditions are derived to ensure that the given performance index is optimal. Findings The effectiveness of the obtained time-optimal control protocols is verified by two contrastive numerical simulation examples. Consequently, the proposed protocols can successfully achieve the prescribed flying shape. Originality/value This paper proposes a solution to solve the time-optimal control problems for multiple UAV systems to achieve predefined flying shape.

scholarly journals Hidden invariant convexity for global and conic-intersection optimality guarantees in discrete-time optimal control

2021 ◽  
Author(s):  
Jorn H. Baayen ◽  
Krzysztof Postek
Keyword(s):  
Optimal Control ◽  
Power Systems ◽  
Discrete Time ◽  
Broad Class ◽  
Optimal Solution ◽  
Time Optimal Control ◽  
Exact Nature ◽  
State Variables ◽  
Numerical Experience ◽  
Time Optimal

AbstractNon-convex discrete-time optimal control problems in, e.g., water or power systems, typically involve a large number of variables related through nonlinear equality constraints. The ideal goal is to find a globally optimal solution, and numerical experience indicates that algorithms aiming for Karush–Kuhn–Tucker points often find solutions that are indistinguishable from global optima. In our paper, we provide a theoretical underpinning for this phenomenon, showing that on a broad class of problems the objective can be shown to be an invariant convex function (invex function) of the control decision variables when state variables are eliminated using implicit function theory. In this way, optimality guarantees can be obtained, the exact nature of which depends on the position of the solution within the feasible set. In a numerical example, we show how high-quality solutions are obtained with local search for a river control problem where invexity holds.

Floating Time Algorithm for Time Optimal Control of Multi-Body Dynamic Systems

2005 ◽  
Vol 219 (3) ◽  
pp. 225-236 ◽  
Author(s):  
G Nakhaie Jazar ◽  
A Naghshineh-Pour
Keyword(s):  
Optimal Control ◽  
Dynamic System ◽  
Dynamic Systems ◽  
Time Optimal Control ◽  
Coordinate Space ◽  
Algebraic Equations ◽  
Initial State ◽  
Time Optimal ◽  
Multi Body ◽  
Body Dynamic

Moving a dynamic system in minimum time from a given initial state to a desired final state on a prescribed path is one of the oldest and most enduring technological dreams of the scientific and industrial communities. In this research, the problem of bounded-input time optimal control for applied multi-body dynamic systems subject to a full nonlinear dynamical model is solved. To solve the problem, an innovative method, called the ‘floating-time’ method is introduced and utilized. Compared to traditional methods, the floating-time method is an applied method not based on variational calculus. It can be applied to the full nonlinear model of the dynamical system and can handle static and dynamic constraints defined by differential or algebraic equations. The problem of time optimal control is as follows. Find the control law of bounded inputs that drive a given multi-body dynamic system (such as the gripper of a manipulator) along a pre-specified trajectory (in either configuration space or generalized coordinate space) from a given initial position to a given final position, minimizing the time of the motion as a performance index. Using variable time increments, the equations of motion of the system will be reduced to a set of algebraic equations. Searching for a set of time increments (floating-times) that make the equations to exert the maximum available effort produces the minimum possible floating-times, and minimizes the total time of motion. The applicability of the method will be shown by using three examples: a point mass sliding on a rough surface, a 2R robotic manipulator, and the well-known Brachistochrone.

Determining Model Accuracy Requirements for Automotive Engine Coldstart Hydrocarbon Emissions Control

2012 ◽  
Vol 134 (5) ◽  
Author(s):  
Nasser L. Azad ◽  
Pannag R. Sanketi ◽  
J. Karl Hedrick
Keyword(s):  
Optimal Control ◽  
Sensitivity Analysis ◽  
Real Time ◽  
Minimum Principle ◽  
Optimal Solution ◽  
Control Performance ◽  
Automotive Engine ◽  
Engine Model ◽  
Time Optimal ◽  
Hc Emissions

In this work, a systematic method is introduced to determine the required accuracy of an automotive engine model used for real-time optimal control of coldstart hydrocarbon (HC) emissions. The engine model structure and development are briefly explained and the model predictions versus experimental results are presented. The control design problem is represented with a dynamic optimization formulation on the basis of the engine model and solved using the Pontryagin’s minimum principle (PMP). To relate the level of plant/model mismatch and the control performance degradation in practice, a sensitivity analysis using a computationally efficient method is employed. In this way, the sensitivities or the effects of small parameter variations on the optimal solution, which is the minimum of cumulative tailpipe HC emissions over the coldstart period, are calculated. There is a good agreement between the sensitivity analysis results and the experimental data. The sensitivities indicate the directions of the subsequent parameter estimation and model improvement tasks to enhance the control-relevant accuracy, and thus, the control performance. Furthermore, they provide some insights to simplify the engine model, which is critical for real-time implementation of the coldstart optimal control system.

scholarly journals Application of Minimum-time Optimal Control System in Buck-Boost Bi-linear Converters

2017 ◽  
Vol 7 (4) ◽  
pp. 1753-1758
Author(s):  
S. M. M. Shariatmadar ◽  
S. M. J. Jafarian
Keyword(s):  
Optimal Control ◽  
Control System ◽  
Output Voltage ◽  
Minimum Principle ◽  
Voltage Regulation ◽  
Minimum Time ◽  
Time Optimal Control ◽  
Optimal Switching ◽  
Optimal Control System ◽  
Time Optimal

In this study, the theory of minimum-time optimal control system in buck-boost bi-linear converters is described, so that output voltage regulation is carried out within minimum time. For this purpose, the Pontryagin's Minimum Principle is applied to find optimal switching level applying minimum-time optimal control rules. The results revealed that by utilizing an optimal switching level instead of classical switching patterns, output voltage regulation will be carried out within minimum time. However, transient energy index of increased overvoltage significantly reduces in order to attain minimum time optimal control in reduced output load. The laboratory results were used in order to verify numerical simulations.

Time-Optimal Control of Dynamic Systems Regarding Final Constraints

2020 ◽  
Author(s):  
Philipp Eichmeir ◽  
Karin Nachbagauer ◽  
Thomas Lauß ◽  
Karim Sherif ◽  
Wolfgang Steiner
Keyword(s):  
Dynamic Systems ◽  
Boundary Value ◽  
Optimal Solution ◽  
Initial Guess ◽  
Optimal Controls ◽  
Cost Functional ◽  
Novel Approach ◽  
End Conditions ◽  
Time Optimal ◽  
The Cost

Abstract Within the framework of this article, we pursue a novel approach for the determination of time-optimal controls for dynamic systems under observance of end conditions. Such problems arise in robotics, e.g. if the control of a robot has to be designed such that the time for a rest-to-rest maneuver becomes a minimum. So far, such problems have been generally considered as two-point boundary value problems, which are hard to solve and require an initial guess close to the optimal solution. The aim of this work is the development of an iterative, gradient based solution strategy which can be applied even to complex multibody systems. The so-called adjoint method is a promising way to compute the direction of the steepest descent, i.e. the variation of a control signal causing the largest local decrease of the cost functional. The proposed approach will be more robust than solving the underlying boundary value problem, as the cost functional will be minimized iteratively while approaching the final conditions. Moreover, so-called influence differential equations are formulated to relate the changes of the controls and of the final conditions. In order to meet the end conditions, we introduce a descent direction that, on the one hand, approaches the optimum of the constrained cost functional and, on the other hand, reduces the error in the prescribed final conditions.

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