2,014 research outputs found

    Fuzzy switching systems: minimizing discontinuities and ripple magnitude and energy

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    This paper presents an efficient and effective method to determine optimal switching instants of fuzzy switching systems such that both the ripple magnitude and energy of the fuzzy switching systems are minimized. The method is based on optimal switching control techniques, where an optimal enhancing control method is used. This method has several advantages over the traditional methods. Firstly, it does not require the process of linearization. Secondly, it guarantees to achieve optimality. For illustration, a practical example of an optimal pulse width modulated fuzzy control of a switched-capacitor DC/DC power converter is presented

    The control parameterization method for nonlinear optimal control: A survey

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    The control parameterization method is a popular numerical technique for solving optimal control problems. The main idea of control parameterization is to discretize the control space by approximating the control function by a linear combination of basis functions. Under this approximation scheme, the optimal control problem is reduced to an approximate nonlinear optimization problem with a finite number of decision variables. This approximate problem can then be solved using nonlinear programming techniques. The aim of this paper is to introduce the fundamentals of the control parameterization method and survey its various applications to non-standard optimal control problems. Topics discussed include gradient computation, numerical convergence, variable switching times, and methods for handling state constraints. We conclude the paper with some suggestions for future research

    Optimal PWM control of switched-capacitor DC/DC power converters via model transformation and enhancing control techniques

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    Abstract—This paper presents an efficient and effective method for an optimal pulse width modulated (PWM) control of switched-capacitor DC/DC power converters. Optimal switching instants are determined based on minimizing the output ripple magnitude, the output leakage voltage and the sensitivity of the output load voltage with respect to both the input voltage and the load resistance. This optimal PWM control strategy has several advantages over conventional PWM control strategies: 1) It does not involve a linearization, so a large signal analysis is performed. 2) It guarantees the optimality. The problem is solved via both the model transformation and the optimal enhancing control techniques. A practical example of the PWM control of a switched-capacitor DC/DC power converter is presented

    Optimal Control of Nonlinear Switched Systems: Computational Methods and Applications

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    A switched system is a dynamic system that operates by switching between different subsystems or modes. Such systems exhibit both continuous and discrete characteristics—a dual nature that makes designing effective control policies a challenging task. The purpose of this paper is to review some of the latest computational techniques for generating optimal control laws for switched systems with nonlinear dynamics and continuous inequality constraints. We discuss computational strategiesfor optimizing both the times at which a switched system switches from one mode to another (the so-called switching times) and the sequence in which a switched system operates its various possible modes (the so-called switching sequence). These strategies involve novel combinations of the control parameterization method, the timescaling transformation, and bilevel programming and binary relaxation techniques. We conclude the paper by discussing a number of switched system optimal control models arising in practical applications

    Dynamic optimization of dual-mode hybrid systems with state-dependent switching conditions

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    This paper presents a computational approach for optimizing a class of hybrid systems in which the state dynamics switch between two distinct modes. The times at which the mode transitions occur cannot be specified directly, but are instead governed by a state-dependent switching condition. The control variables, which should be chosen optimally by the system designer, consist of a set of continuous-time input signals. By introducing an auxiliary binary-valued control function to represent the system's current mode, we show that any dual-mode hybrid system with state-dependent switching conditions can be transformed into a standard dynamic system subject to path constraints. We then develop a computational algorithm, based on control parameterization, the time-scaling transformation, and an exact penalty method, for determining the optimal piecewise constant input signals for the original hybrid system. A numerical example on cancer chemotherapy is included to demonstrate the effectiveness of the proposed algorithm

    Computational Method for a Class of Switched System Optimal Control Problems

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    A Hybrid Time-Scaling Transformation for Time-Delay Optimal Control Problems

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    In this paper, we consider a class of nonlinear time-delay optimal control problems with canonical equality and inequality constraints. We propose a new computational approach, which combines the control parameterization technique with a hybrid time-scaling strategy, for solving this class of optimal control problems. The proposed approach involves approximating the control variables by piecewise constant functions, whose heights and switching times are decision variables to be optimized. Then, the resulting problem with varying switching times is transformed, via a new hybrid time-scaling strategy, into an equivalent problem with fixed switching times, which is much preferred for numerical computation. Our new time-scaling strategy is hybrid in the sense that it is related to two coupled time-delay systems—one defined on the original time scale, in which the switching times are variable, the other defined on the new time scale, in which the switching times are fixed. This is different from the conventional time-scaling transformation widely used in the literature, which is not applicable to systems with time-delays. To demonstrate the effectiveness of the proposed approach, we solve four numerical examples. The results show that the costs obtained by our new approach are lower, when compared with those obtained by existing optimal control methods

    Optimal control of impulsive switched systems with minimum subsystem durations

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    This paper presents a new computational approach for solving optimal control problems governed by impulsive switched systems. Such systems consist of multiple subsystems operating in succession, with possible instantaneous state jumps occurring when the system switches from one subsystem to another. The control variables are the subsystem durations and a set of system parameters influencing the state jumps. In contrast with most other papers on the control of impulsive switched systems, we do not require every potential subsystem to be active during the time horizon (it may be optimal to delete certain subsystems, especially when the optimal number of switches is unknown). However, any active subsystem must be active for a minimum non-negligible duration of time. This restriction leads to a disjoint feasible region for the subsystem durations. The problem of choosing the subsystem durations and the system parameters to minimize a given cost function is a non-standard optimal control problem that cannot be solved using conventional techniques. By combining a time-scaling transformation and an exact penalty method, we develop a computational algorithm for solving this problem. We then demonstrate the effectiveness of this algorithm by considering a numerical example on the optimization of shrimp harvesting operations

    Stochastic-based adaptive control vibration control for MACE II

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76388/1/AIAA-2001-4644-483.pd
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