The parametric formulation is a systematic method of designing joint profiles for bipedal systems using constraint functions, which are cast in terms of coherent physical characteristics of gait. For continuous and st...
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ISBN:
(纸本)1889335193
The parametric formulation is a systematic method of designing joint profiles for bipedal systems using constraint functions, which are cast in terms of coherent physical characteristics of gait. For continuous and steady bipedal walking, acceptable joint profiles must produce repeatable gait. This paper presents a parametric study to correlate the locomotion parameters with initial angles for each step. Furthermore, a necessary and sufficient condition for repeatable gait is proposed, which can be used as a guideline for selecting constraint functions to achieve acceptable joint profiles. This research not only provides valuable insights into the bipedal walking, but also serves as a stepping stone for employing the parametric formulation with various constraint functions.
Analytical target cascading is a relatively new methodology for the design of engineering systems. Analytical target cascading deals with the issue of propagating desirable top-level product-design specifications (or ...
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Analytical target cascading is a relatively new methodology for the design of engineering systems. Analytical target cascading deals with the issue of propagating desirable top-level product-design specifications (or targets) to appropriate targets at lower levels in a consistent and efficient manner. Most existing problem formulations for multilevel design often exhibit convergence difficulties. It is proved that the analytical target cascading process converges to a point that satisfies the necessary optimality conditions of the original design target problem.
An adaptive fuzzy neural network (FNN) control scheme is proposed for a marine vessel with time-varying constraints, guaranteed transient response and unknown dynamics. A series of continuous constraint functions are ...
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An adaptive fuzzy neural network (FNN) control scheme is proposed for a marine vessel with time-varying constraints, guaranteed transient response and unknown dynamics. A series of continuous constraint functions are introduced to shape the motion of a marine vessel. To deal with the constraint problems and transient response problems, an asymmetric time-varying barrier Lyapunov function is designed to ensure that the system states are upper bounded by the considered constraint functions. FNNs are constructed to identify the unknown dynamics. Considering existing approximation errors when FNNs approximating the unknown dynamics, an adaptive term is designed to compensate the approximation errors in order to obtain accurate control. Via Lyapunov stability theory, it has been proved that all the states in the closed-loop system are uniformly bounded ultimately without violating the corresponding prescribed constraint region. Two comparative simulations are carried out to verify the effectiveness of the proposed control.
Due to the non-linearity of current-voltage of solar cell model, the conventional methods are incapable to extract the parameters of solar cell with high accuracy. The implicit non-linear equation describing the singl...
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ISBN:
(纸本)9781509051601
Due to the non-linearity of current-voltage of solar cell model, the conventional methods are incapable to extract the parameters of solar cell with high accuracy. The implicit non-linear equation describing the single and double diodes solar cell in five and seven parameters is rewritten as optimization problems with constraint functions and it is solved by using a firefly algorithm optimization. The firefly algorithm is a nature-inspired stochastic optimization algorithm, and able to solve modern global optimization for nonlinear and complex system, based on the flashing patterns and behavior of firefly's swarm. Moreover, this paper develops a unique solar cell modelling approach that incorporates search and optimization techniques for the determination of equivalent circuit parameters of RTC France Company mono-crystalline silicon solar cell single and double diodes at 33 degrees C and 1000W/m(2) from experimental current-voltage. The statistical errors are used to verify the accuracy of the results. Finally, accuracy of the extracted parameters is verified by comparing the current-voltage curve generated from simulation with those provided by determined experimentally and with different recent algorithms.
In this thesis, we develop numerical methods for solving five nonstandard optimal control problems. The main idea of each method is to reformulate the optimal control problem as, or approximate it by, a nonlinear prog...
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In this thesis, we develop numerical methods for solving five nonstandard optimal control problems. The main idea of each method is to reformulate the optimal control problem as, or approximate it by, a nonlinear programming problem. The decision variables in this nonlinear programming problem influence its cost function (and constraints, if it has any) implicitly through the dynamic system. Hence, deriving the gradient of the cost and the constraint functions is a difficult task. A major focus of this thesis is on developing methods for computing these gradients. These methods can then be used in conjunction with a gradient-based optimization technique to solve the optimal control problem efficiently.%%%%The first optimal control problem that we consider has nonlinear inequality constraints that depend on the state at two or more discrete time points. These time points are decision variables that, together with a control function, should be chosen in an optimal manner. To tackle this problem, we first approximate the control by a piecewise constant function whose values and switching times (the times at which it changes value) are decision variables. We then apply a novel time-scaling transformation that maps the switching times to fixed points in a new time horizon. This yields an approximate dynamic optimization problem with a finite number of decision variables. We develop a new algorithm, which involves integrating an auxiliary dynamic system forward in time, for computing the gradient of the cost and constraints in this approximate problem.%%%%The second optimal control problem that we consider has nonlinear continuous inequality constraints. These constraints restrict both the state and the control at every point in the time horizon. As with the first problem, we approximate the control by a piecewise constant function and then transform the time variable. This yields an approximate semi-infinite programming problem, which can be solved using a penalty functi
Due to the non-linearity of current-voltage of solar cell model, the conventional methods are incapable to extract the parameters of solar cell with high accuracy. The implicit non-linear equation describing the singl...
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ISBN:
(纸本)9781509051618
Due to the non-linearity of current-voltage of solar cell model, the conventional methods are incapable to extract the parameters of solar cell with high accuracy. The implicit non-linear equation describing the single and double diodes solar cell in five and seven parameters is rewritten as optimization problems with constraint functions and it is solved by using a firefly algorithm optimization. The firefly algorithm is a nature-inspired stochastic optimization algorithm, and able to solve modern global optimization for nonlinear and complex system, based on the flashing patterns and behavior of firefly's swarm. Moreover, this paper develops a unique solar cell modelling approach that incorporates search and optimization techniques for the determination of equivalent circuit parameters of RTC France Company mono-crystalline silicon solar cell single and double diodes at 33℃ and 1000W/m~2 from experimental current-voltage. The statistical errors are used to verify the accuracy of the results. Finally, accuracy of the extracted parameters is verified by comparing the current-voltage curve generated from simulation with those provided by determined experimentally and with different recent algorithms.
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