A Darwinian approach to control-structure design

Genetic algorithms (GA's), as introduced by Holland (1975), are one form of directed random search. The form of direction is based on Darwin's 'survival of the fittest' theories. GA's are radically different from the more traditional design optimization techniques. GA's work with a coding of the design variables, as opposed to working with the design variables directly. The search is conducted from a population of designs (i.e., from a large number of points in the design space), unlike the traditional algorithms which search from a single design point. The GA requires only objective function information, as opposed to gradient or other auxiliary information. Finally, the GA is based on probabilistic transition rules, as opposed to deterministic rules. These features allow the GA to attack problems with local-global minima, discontinuous design spaces and mixed variable problems, all in a single, consistent framework

Active vibration control (AVC) of a satellite boom structure using optimally positioned stacked piezoelectric actuators

In this paper, results for active vibration control predicted from experimental measurements on a lightweight structure are compared with purely computational predictions. The structure studied is a 4.5m long satellite boom consisting of 10 identical bays with equilateral triangular cross sections. First, the results from a Fortran code that is based on a receptance analysis are validated against the experimental forced response of the boom structure. Exhaustive searches are then carried out to find the optimum positions for one and two actuators. Finally, a genetic algorithm is employed to find high-quality positions for three actuators on the structure that will achieve the greatest reductions in vibration transmission. Having found these actuator positions, experiments are then carried out to verify the quality of the theoretical predictions. It was found that the attenuation achievable in practice for one, two and three actuators were, respectively, 15.1, 26.1 and 33.5 dB

Active vibration control (AVC) of a satellite boom structure using optimally positioned stacked piezoelectric actuators

In this paper, results for active vibration control predicted from experimental measurements on a lightweight structure are compared with purely computational predictions. The structure studied is a 4.5m long satellite boom consisting of 10 identical bays with equilateral triangular cross sections. First, the results from a Fortran code that is based on a receptance analysis are validated against the experimental forced response of the boom structure. Exhaustive searches are then carried out to find the optimum positions for one and two actuators. Finally, a genetic algorithm is employed to find high-quality positions for three actuators on the structure that will achieve the greatest reductions in vibration transmission. Having found these actuator positions, experiments are then carried out to verify the quality of the theoretical predictions. It was found that the attenuation achievable in practice for one, two and three actuators were, respectively, 15.1, 26.1 and 33.5 dB

Distributed multilevel optimization for complex structures

Optimization problems concerning complex structures with many design variables may entail an unacceptable computational cost. This problem can be reduced considerably with a multilevel approach: A structure consisting of several components is optimized as a whole (global) as well as on the component level. In this paper, an optimization method is discussed with applications in the assessment of the impact of new design considerations in the development of a structure. A strategy based on fully stressed design is applied for optimization problems in linear statics. A global model is used to calculate the interactions (e.g., loads) for each of the components. These components are then optimized using the prescribed interactions, followed by a new global calculation to update the interactions. Mixed discrete and continuous design variables as well as different design configurations are possible. An application of this strategy is presented in the form of the full optimization of a vertical tail plane center box of a generic large passenger aircraft. In linear dynamics, the parametrization of the component interactions is problematic due to the frequency dependence. Hence, a modified method is presented in which the speed of component mode synthesis is used to avoid this parametrization. This method is applied to a simple test case that originates from noise control. \u

Techniques for Optimum Design of Actively Controlled Structures Including Topological Considerations

The design and performance of complex engineering systems often depends on several conflicting objectives which, in many cases, cannot be represented as a single measure of performance. This thesis presents a multi-objective formulation for a comprehensive treatment of the structural and topological considerations in the design of actively controlled structures. The dissertation addresses three main problems. The first problem deals with optimum placement of actuators in actively controlled structures. The purpose of control is to reduce the vibrations when the structure is subjected to a disturbance. In order to mitigate the structural vibrations as quickly as possible, it is necessary to place the actuators at locations such that their ability to control the vibrations is maximized. Since the actuator locations are discrete (0-1) variables, a genetic algorithm based approach is used to solve the resulting optimization problem. The second problem this dissertation addresses is the multi-objective design of actively controlled structures. Structural weight, controller performance index and energy dissipated by the actuators are considered as the objective functions. It is assumed that a hierarchical structure exist between the actuator placement and structural-control design objective functions with the actuator placement problem considered being more important. The resulting multi-objective optimization problem is solved using Stackelberg game and cooperative game theory approaches. The exchange of information between different levels of the multi-level problem is done by constructing the rational reaction set of follower solution using design of experiments and response surface methods. The third problem addressed in this dissertation is the optimization of structural topology in the context of structural/control system design. Despite the recognition that an optimization of topology can significantly improve structural performance, most of the work in design of actively controlled structures has been done with structures of a known topology. The combined topology and sizing optimization of actively controlled structures is also considered in this thesis. The approach presented involves the determination of optimum topology followed by a sizing and control system optimization of the optimum topology. Using two numerical examples, it is shown that a simultaneous consideration of topological, control and structural aspects yields solutions that outperform designs when topological considerations are neglected

New methodology for optimal placement of piezoelectric sensor/actuator pairs for active vibration control of flexible structures

This paper describes a computationally efficient method to determine optimal locations of sensor/actuator (s/a) pairs for active vibration reduction of a flexible structure. Previous studies have tackled this problem using heuristic optimization techniques achieved with numerous combinations of s/a locations and converging on a suboptimal or optimal solution after multithousands of generations. This is computationally expensive and directly proportional to the number of sensors, actuators, possible locations on structures, and the number of modes required to be suppressed (control variables). The current work takes a simplified approach of modeling a structure with sensors at all locations, subjecting it to external excitation force or structure base excitation in various modes of interest and noting the locations of n sensors giving the largest average percentage sensor effectiveness. The percentage sensor effectiveness is measured by dividing all sensor output voltage over the maximum for each mode using time and frequency domain analysis. The methodology was implemented for dynamically symmetric and asymmetric structures under external force and structure base excitations to find the optimal distribution based on time and frequency responses analysis. It was found that the optimized sensor locations agreed well with the published results for a cantilever plate, while with very much reduced computational effort and higher effectiveness. Furthermore, it was found that collocated s/a pairs placed in these locations offered very effective active vibration reduction for the structure considered

Post-Westgate SWAT : C4ISTAR Architectural Framework for Autonomous Network Integrated Multifaceted Warfighting Solutions Version 1.0 : A Peer-Reviewed Monograph

Police SWAT teams and Military Special Forces face mounting pressure and challenges from adversaries that can only be resolved by way of ever more sophisticated inputs into tactical operations. Lethal Autonomy provides constrained military/security forces with a viable option, but only if implementation has got proper empirically supported foundations. Autonomous weapon systems can be designed and developed to conduct ground, air and naval operations. This monograph offers some insights into the challenges of developing legal, reliable and ethical forms of autonomous weapons, that address the gap between Police or Law Enforcement and Military operations that is growing exponentially small. National adversaries are today in many instances hybrid threats, that manifest criminal and military traits, these often require deployment of hybrid-capability autonomous weapons imbued with the capability to taken on both Military and/or Security objectives. The Westgate Terrorist Attack of 21st September 2013 in the Westlands suburb of Nairobi, Kenya is a very clear manifestation of the hybrid combat scenario that required military response and police investigations against a fighting cell of the Somalia based globally networked Al Shabaab terrorist group.Comment: 52 pages, 6 Figures, over 40 references, reviewed by a reade

Active vibration control of flexible structures by optimally placed sensors and actuators

PhD ThesisThe active vibration reduction of plane and stiffened plates was investigated using a genetic algorithm based on finite element modelling to optimise the location of sensors and actuators. The main aspects of this work were: Development of a finite element model for a plate stiffened by beams with discrete sensors and actuators bonded to its surface. Development of a finite element program for steel plates with various symmetrical and asymmetrical stiffening and edge conditions. Development of a genetic algorithm program based on the finite element modelling for the optimisation of the location and number of sensor/actuator pairs and feedback gain. Determination of optimum locations and feedback gain for collocated piezoelectric sensors and actuators on steel plates with various symmetrical and asymmetrical stiffening and edge conditions. Development of fitness and objective functions to locate sensors and actuators. Development of fitness and objective functions to determine the optimal number of sensors and actuators. Development of a reduced search space technique for symmetrical problems. Optimisation of vibration reduction control scheme parameters using the genetic algorithm. Optimisation of the number and location of sensor/actuator pairs and feedback gain to reduce material costs and structural weight and to achieve effective vibration reduction. The modelling was validated by comparison with conventional finite element analysis using ANSYS, and by experiment. The modelling was developed using a quadrilateral isoparametric finite element, based on first order shear deformation theory and Hamilton’s principle, which may be arbitrarily stiffened by beams on its edges. The model can be applied to flat plates with or without stiffening, with discrete piezoelectric sensors and actuators bonded to its surfaces. The finite element modelling was tested for flat and stiffened plates with different boundary conditions and geometries, and the results of the first six natural frequencies were validated with the ANSYS package and experimentally. A genetic algorithm placement strategy is proposed to find the global optimal distribution of two, four, six and ten sensor/actuator pairs and feedback gain based on the minimisation of optimal linear quadratic index as an objective function, and applied to a cantilever plate to attenuate the first six modes of vibration. The configuration of this global optimum was found to be symmetrically distributed about the dynamic axes of symmetry and gave higher vibration attenuation than previously published results with an asymmetrical distribution which was claimed to be optimal. Another genetic algorithm placement strategy is proposed to optimise sensor/actuator locations using new fitness and objective functions based on . This is applied to the same cantilever plate, and was also found to give a symmetrical optimal sensor/actuator configuration. As before, it was found that the optimal transducer locations are distributed with the same axes of symmetry and in agreement with the ANSYS results. A program to simulate the active vibration reduction of stiffened plates with piezoelectric sensors and actuators was written in the ANSYS Parametric Design Language (APDL). This makes use of the finite element capability of ANSYS and incorporates an estimator based on optimal linear quadratic and proportional differential control schemes to investigate the open and closed loop time responses. The complexity of the genetic algorithm problem is represented by the number of finite elements, sensor/actuator pairs and modes required to be suppressed giving a very large search space. In this study, this problem was reduced by the development of a new half and quarter chromosomes technique exploiting the symmetries of the structure. This greatly reduces the number of generations, and hence the computing time, required for the genetic algorithm to converge on the global optimal solution. This could be significant when the technique is applied to large and complex structures. Finally, new fitness and objective functions were proposed to optimise the number of sensor/actuator pairs required for effective active vibration reduction in order to reduce the added cost and weight. The number, location and feedback gain were optimised for the same cantilever plate and it was found that two sensor/actuator pairs in optimal locations could be made to give almost as much vibration reduction as ten pairs.Ministry of Higher Education and Scientific Research of Iraq

Turbulent separated shear flow control by surface plasma actuator: experimental optimization by genetic algorithm approach

The potential benefits of active flow control are no more debated. Among many others applications, flow control provides an effective mean for manipulating turbulent separated flows. Here, a nonthermal surface plasma discharge (dielectric barrier discharge) is installed at the step corner of a backward-facing step (U 0 = 15 m/s, Re h  = 30,000, Re θ  = 1650). Wall pressure sensors are used to estimate the reattaching location downstream of the step (objective function #1) and also to measure the wall pressure fluctuation coefficients (objective function #2). An autonomous multi-variable optimization by genetic algorithm is implemented in an experiment for optimizing simultaneously the voltage amplitude, the burst frequency and the duty cycle of the high-voltage signal producing the surface plasma discharge. The single-objective optimization problems concern alternatively the minimization of the objective function #1 and the maximization of the objective function #2. The present paper demonstrates that when coupled with the plasma actuator and the wall pressure sensors, the genetic algorithm can find the optimum forcing conditions in only a few generations. At the end of the iterative search process, the minimum reattaching position is achieved by forcing the flow at the shear layer mode where a large spreading rate is obtained by increasing the periodicity of the vortex street and by enhancing the vortex pairing process. The objective function #2 is maximized for an actuation at half the shear layer mode. In this specific forcing mode, time-resolved PIV shows that the vortex pairing is reduced and that the strong fluctuations of the wall pressure coefficients result from the periodic passages of flow structures whose size corresponds to the height of the step model

Optimal dimensional synthesis of force feedback lower arm exoskeletons

This paper presents multi-criteria design optimization of parallel mechanism based force feedback exoskeletons for human forearm and wrist. The optimized devices are aimed to be employed as a high fidelity haptic interfaces. Multiple design objectives are discussed and classified for the devices and the optimization problem to study the trade-offs between these criteria is formulated. Dimensional syntheses are performed for optimal global kinematic and dynamic performance, utilizing a Pareto front based framework, for two spherical parallel mechanisms that satisfy the ergonomic necessities of a human forearm and wrist. Two optimized mechanisms are compared and discussed in the light of multiple design criteria. Finally, kinematic structure and dimensions of an optimal exoskeleton are decided