The aim of the optimal safety controller synthesis problem is to synthesize a feedback controller that results in closed-loop trajectories that meet certain criteria, namely, the state or output trajectories terminate...
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ISBN:
(纸本)9781479901784
The aim of the optimal safety controller synthesis problem is to synthesize a feedback controller that results in closed-loop trajectories that meet certain criteria, namely, the state or output trajectories terminate in a goal set without entering an unsafe set while optimizing some function. Our previous work presented a method for using finitely many human generated trajectories to synthesize a non-optimal safety controller. We propose a formal method for optimizing the human generated trajectories used to synthesize the controller. Our method is based on the calculus of variations, but is different from other similar algorithms in that it uses a gradient descent based approach to directly solve the optimization problem without formulating the optimality conditions given by the Pontryagin Minimum Principle. This method provides a tool for improving the performance of a controller synthesized using the methods outlined in our previous work. We present an example of optimizing a human generated trajectory for a nonlinear system, specifically a quadrotor, and quantify the improvements it is able to generate.
PID (proportional integral derivative) control is one of the most popular control strategies. However the optimal PID parameters are difficult to obtain and is highly sensitive to the initial guess. This paper is abou...
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ISBN:
(纸本)9781479931170
PID (proportional integral derivative) control is one of the most popular control strategies. However the optimal PID parameters are difficult to obtain and is highly sensitive to the initial guess. This paper is about tuning PID controllers, to meet the desired response. For this goal, three cost functions have been defined resembling the plant error over the time and the Krill Herd optimization algorithm was used to obtain the optimal solution to cost functions by searching the PID parameter space for global minimum and thus tuning the controller effectively. The details of applying the proposed method are given and the numerical results show the proposed strategy is effective.
Two control strategies that allow the control of source and load currents for direct matrix converters are presented in this study. Both methods use the switching state of the converter in the subsequent sampling time...
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Two control strategies that allow the control of source and load currents for direct matrix converters are presented in this study. Both methods use the switching state of the converter in the subsequent sampling time, based on an optimisation algorithm given by a simple cost function and the discrete system model. The control goals include regulation of load currents according to an arbitrary reference and good tracking of the source currents to their references. In the first method, the input current reference is given as a function of the instantaneous active power. In the second case, the source current reference is given as a function of the output current reference and system parameters. Experimental results with an experimental prototype support the theoretical approach.
The fast-track method is one of the most recognized methodologies for reducing construction project schedules. However, due to the lack of definitive research to date pertaining to the effects of fast-track applicatio...
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The fast-track method is one of the most recognized methodologies for reducing construction project schedules. However, due to the lack of definitive research to date pertaining to the effects of fast-track application in terms of time and cost, it has been difficult for project owners to determine its correct application. This paper presents the time and cost optimized decision support (TACTICS) model, and it was developed based on the fast-track methodology and genetic algorithms (GAs). TACTICS was applied to two case studies, and the results indicated that the fast-track method could be expected to deliver more efficient projects compared with using the traditional method. In particular, (1) the average reduction in project duration by applying the fast-track method was 40.48% (Case I) and 18.59% (Case II) compared with using the traditional method, and (2) the average project costs were reduced by as much as 0.39% (Case I) and 4.48% (Case II). Consequently, TACTICS could be expected to help in making a decision regarding the fast-track application and further contribute to the project scheduling expertise in the construction engineering and management body of knowledge. DOI: 10.1061/(ASCE)CO.1943-7862.0000570. (C) 2013 American Society of Civil Engineers.
The feedforward control canal problem is stated as a nonlinear optimization problem with constraints on the gate movements. It is numerically solved with the use of the sequential quadratic problem (SQP) method and th...
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The feedforward control canal problem is stated as a nonlinear optimization problem with constraints on the gate movements. It is numerically solved with the use of the sequential quadratic problem (SQP) method and the active set. The main objective of the resulting GoRoSo algorithm is the scheduling of the gate openings over a programmed operation scenario, and their calculation relies on the use of the Saint-Venant's complete model over a prediction horizon. A numerical and analytical procedure is developed to quantify the influence of any gate movement over the canal flow conditions for a prediction time horizon. All these influences are lumped together in a global matrix, which is referred to as the hydraulic influence matrix. The GoRoSo algorithm is validated by means of a series of test developed by the ASCE task committee on canal automation algorithms. DOI: 10.1061/(ASCE)IR.1943-4774.0000507. (C) 2013 American Society of Civil Engineers.
This paper presents a hybrid stochastic/deterministic optimisation algorithm to solve the target optimisation problem of vibration-based damage detection. The use of a numerical solution of the representation formula ...
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This paper presents a hybrid stochastic/deterministic optimisation algorithm to solve the target optimisation problem of vibration-based damage detection. The use of a numerical solution of the representation formula to locate the region of the global solution, i.e., to provide a starting point for the local optimiser, which is chosen to be the Nelder-Mead algorithm (NMA), is proposed. A series of numerical examples with different damage scenarios and noise levels was performed under impact and ambient vibrations. Thereafter, an experimental study of three cantilever beams with several different damage scenarios was conducted. To test the accuracy and efficiency of the optimisation algorithm, its results were compared to previous procedures available in the literature, which employed different solutions such as the genetic algorithm (GA), the harmony search algorithm (HS) and the particle swarm optimisation (PSO) algorithm. The performance of the proposed optimisation scheme was more accurate and required a lower computational cost than the GA, HS and PSO algorithms, emphasising the capacity of the proposed methodology for its use in damage diagnosis and assessment In addition, the methodology was able to handle incomplete measurements and truncated mode shapes, which is of paramount importance for dealing with operational conditions in long-term structural health monitoring (SHM) applications. (C) 2013 Elsevier Ltd. All rights reserved.
This paper presents the use of different artificial life-based optimization algorithms and cerebellar model articulation controllers (CMACs) in aircraft automatic landing control. The proposed intelligent control syst...
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This paper presents the use of different artificial life-based optimization algorithms and cerebellar model articulation controllers (CMACs) in aircraft automatic landing control. The proposed intelligent control system can act as an experienced pilot and guide the aircraft landed safely in wind disturbance condition. Lyapunov theory is applied to obtain adaptive learning rule and stability analysis is also provided The proposed controllers have better performance than conventional controller.
A quasi-optimal algorithm for correlation processing of noiselike signals with minimum frequency-shift keying is proposed and its noise immunity is analyzed. It is shown that the immunity of the quasi-optimal receiver...
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A quasi-optimal algorithm for correlation processing of noiselike signals with minimum frequency-shift keying is proposed and its noise immunity is analyzed. It is shown that the immunity of the quasi-optimal receiver to a structural noise is the same as that of the optimal correlation receiver and, in the case of a fluctuation noise, the loss in the signal-to-noise ratio is 1 dB relative to the optimal algorithm.
Inspired by the neighbourhood cooperation, a new discrete optimisation algorithm is proposed. The so-called binary neighbourhood field optimisation (BNFO), utilises the attractive field of the superior neighbour and t...
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Inspired by the neighbourhood cooperation, a new discrete optimisation algorithm is proposed. The so-called binary neighbourhood field optimisation (BNFO), utilises the attractive field of the superior neighbour and the repulsive field of the inferior neighbour. As a kind of local search, BNFO is able to deliver promising results efficiently within acceptable computational time. BNFO is applied to solve the unit commitment problem (UCP), whose objective is to minimise the operation cost of the generation units over the scheduling horizon. After numerical tests on several benchmark UCP cases, the obtained costs are less expensive compared with conventional Lagrangian relaxation, genetic algorithm, evolutionary programming, particle swarm optimisation and differential evolutionary. BNFO can converge to promising results with less computation times, especially for the large-scale UCPs.
In modern civilization, water distribution network has a substantial role in preserving the desired living standard. It has different components such as pipe, pump, and control valve to convey water from the supply so...
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In modern civilization, water distribution network has a substantial role in preserving the desired living standard. It has different components such as pipe, pump, and control valve to convey water from the supply source to the consumer withdrawal points. Among these elements, optimal sizing of pipes has great importance because more than 70% of the project cost is incurred on it. Unfortunately, optimal pipe sizing falls in the category of nonlinear polynomial time hard (NP-hard) problems. Hence, solid research activities march on because of two facts, namely, importance and complexity of the problem. The literature revealed that the stochastic optimization algorithms are successful in exploring the combination of least-cost pipe diameters from the commercially available discrete diameter set, but with the expense of significant computational effort. The hybrid model PSO-GA, presented in this paper aimed to effectively utilize local and global search capabilities of particle swarm optimization (PSO) and genetic algorithm (GA), respectively, to reduce the computational burden. The analyses on different water distribution networks uncover that the proposed hybrid model is capable of exploring the optimal combination of pipe diameters with minimal computational effort. DOI: 10.1061/(ASCE)PS.1949-1204.0000113. (C) 2013 American Society of Civil Engineers.
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