Optimal placement of piezoelectric sensor/actuators for smart structures vibration control

Smart material technology has become an area of increasing interest for the development of lighter and stronger structures that are able to incorporate actuator and sensor capabilities for collocated control. In the design of actively controlled structures, the determination of the actuator locations and the controller gains is a very important issue. For that purpose, smart material modeling, modal analysis methods, and control and optimization techniques are the most important ingredients to be taken into account. The optimization problem to be solved in this context presents two interdependent aspects. The first is related to the discrete optimal actuator location selection problem, which is solved in this paper using genetic algorithms. The second is represented by a continuous variable optimization problem, through which the control gains are determined using classical techniques. A cantilever Euler-Bernoulli beam is used to illustrate the presented methodology.

Optimal placement of sensors/actuators in truss structures with known disturbances

An important stage in the solution of active vibration control in flexible structures is the optimal placement of sensors and actuators. In many works, the positioning of these devices in systems governed for parameter distributed is, mainly, based, in controllability approach or criteria of performance. The positions that enhance such parameters are considered optimal. These techniques do not take in account the space variation of disturbances. An way to enhance the robustness of the control design would be to locate the actuators considering the space distribution of the worst case of disturbances. This paper is addressed to include in the formulation of problem of optimal location of sensors and piezoelectric actuators the effect of external disturbances. The paper concludes with a numerical simulation in a truss structure considering that the disturbance is applied in a known point a priori. As objective function the C norm system is used. The LQR (Linear Quadratic Regulator) controller was used to quantify performance of different sensors/actuators configurations.

Optimal placement of Distributed Generation for a projected load increase using Relative Electrical Distance approach

There is a lot of pressure on all the developed and second world countries to produce low emission power and distributed generation (DG) is found to be one of the most viable ways to achieve this. DG generally makes use of renewable energy sources like wind, micro turbines, photovoltaic, etc., which produce power with minimum green house gas emissions. While installing a DG it is important to define its size and optimal location enabling minimum network expansion and line losses. In this paper, a methodology to locate the optimal site for a DG installation, with the objective to minimize the net transmission losses, is presented. The methodology is based on the concept of relative electrical distance (RED) between the DG and the load points. This approach will help to identify the new DG location(s), without the necessity to conduct repeated power flows. To validate this methodology case studies are carried out on a 20 node, 66kV system, a part of Karnataka Transco and results are presented.

Optimal placement of reflective pavement markers. Final report.

Ohio Department of Transportation, Columbus

Experimental Demonstration of H{infty} Control based Active Vibration Suppression in Composite Fin-tip of Aircraft using Optimally Placed Piezoelectric Patch Actuators

The goal of this study is the multi-mode structural vibration control in the composite fin-tip of an aircraft. Structural model of the composite fin-tip with surface bonded piezoelectric actuators is developed using the finite element method. The finite element model is updated experimentally to reflect the natural frequencies and mode shapes accurately. A model order reduction technique is employed for reducing the finite element structural matrices before developing the controller. Particle swarm based evolutionary optimization technique is used for optimal placement of piezoelectric patch actuators and accelerometer sensors to suppress vibration. H{infty} based active vibration controllers are designed directly in the discrete domain and implemented using dSpace® (DS-1005) electronic signal processing boards. Significant vibration suppression in the multiple bending modes of interest is experimentally demonstrated for sinusoidal and band limited white noise forcing functions.

Placement of Small Vertical Axis Wind Turbine to Maximize Power Generation Influenced by Architectural and Geographic Interfaces in Urban Areas

Current methods for large-scale wind collection are unviable in urban areas. In order to investigate the feasibility of generating power from winds in these environments, we sought to optimize placements of small vertical-axis wind turbines in areas of artificially-generated winds. We explored both vehicular transportation and architecture as sources of artificial wind, using a combination of anemometer arrays, global positioning system (GPS), and weather report data. We determined that transportation-generated winds were not significant enough for turbine implementation. In addition, safety and administrative concerns restricted the implementation of said wind turbines along roadways for transportation-generated wind collection. Wind measurements from our architecture collection were applied in models that can help predict other similar areas with artificial wind, as well as the optimal placement of a wind turbine in those areas.

Robust control to parametric uncertainties in smart structures using linear matrix inequalities

The study of algorithms for active vibrations control in flexible structures became an area of enormous interest, mainly due to the countless demands of an optimal performance of mechanical systems as aircraft and aerospace structures. Smart structures, formed by a structure base, coupled with piezoelectric actuators and sensor are capable to guarantee the conditions demanded through the application of several types of controllers. This article shows some steps that should be followed in the design of a smart structure. It is discussed: the optimal placement of actuators, the model reduction and the controller design through techniques involving linear matrix inequalities (LMI). It is considered as constraints in LMI: the decay rate, voltage input limitation in the actuators and bounded output peak (output energy). Two controllers robust to parametric variation are designed: the first one considers the actuator in non-optimal location and the second one the actuator is put in an optimal placement. The performance are compared and discussed. The simulations to illustrate the methodology are made with a cantilever beam with bonded piezoelectric actuators.

Revisão sobre técnicas de controle em estruturas inteligentes

One of the great challenges of structural dynamics is to ally structures lighther and stronger. The great difficulty is that light systems, in general, have a low inherent damping. Besides, they contain resonance frequencies in the low frequency range. So, any external disturbance can excite the system in some resonance and the resulting effect can be drastic. The methodologies of active damping, with control algorithms and piezoelectric sensors and actuators coupled in a base structure, are attractive in current days, in order to overcome the contradictory features of these requeriments. In this sense, this article contributes with a bibliographical review of the literature on the importance of active noise and vibration control in engineering applications, models of smart structures, techniques of optimal placement of piezoelectric sensors and actuators and methodologies of structural active control. Finally, it is discussed the future perspectives in this area.

Swarm intelligence algorithms for integrated optimization of piezoelectric actuator and sensor placement and feedback gains

Swarm intelligence algorithms are applied for optimal control of flexible smart structures bonded with piezoelectric actuators and sensors. The optimal locations of actuators/sensors and feedback gain are obtained by maximizing the energy dissipated by the feedback control system. We provide a mathematical proof that this system is uncontrollable if the actuators and sensors are placed at the nodal points of the mode shapes. The optimal locations of actuators/sensors and feedback gain represent a constrained non-linear optimization problem. This problem is converted to an unconstrained optimization problem by using penalty functions. Two swarm intelligence algorithms, namely, Artificial bee colony (ABC) and glowworm swarm optimization (GSO) algorithms, are considered to obtain the optimal solution. In earlier published research, a cantilever beam with one and two collocated actuator(s)/sensor(s) was considered and the numerical results were obtained by using genetic algorithm and gradient based optimization methods. We consider the same problem and present the results obtained by using the swarm intelligence algorithms ABC and GSO. An extension of this cantilever beam problem with five collocated actuators/sensors is considered and the numerical results obtained by using the ABC and GSO algorithms are presented. The effect of increasing the number of design variables (locations of actuators and sensors and gain) on the optimization process is investigated. It is shown that the ABC and GSO algorithms are robust and are good choices for the optimization of smart structures.

Optimal application and placement of roadside reflective devices for curves on two-lane rural highways. Final report.

Ohio Department of Transportation, Columbus

Optimal allocation of a cross-connection and sectionalizers in distribution systems

In this paper, the placement of sectionalizers, as well as, a cross-connection is optimally determined so that the objective function is minimized. The objective function employed in this paper consists of two main parts, the switch cost and the reliability cost. The switch cost is composed of the cost of sectionalizers and cross-connection and the reliability cost is assumed to be proportional to a reliability index, SAIDI. To optimize the allocation of sectionalizers and cross-connection problem realistically, the cost related to each element is considered as discrete. In consequence of binary variables for the availability of sectionalizers, the problem is extremely discrete. Therefore, the probability of local minimum risk is high and a heuristic-based optimization method is needed. A Discrete Particle Swarm Optimization (DPSO) is employed in this paper to deal with this discrete problem. Finally, a testing distribution system is used to validate the proposed method.

Evolutionary placement of continuously operating reference stations of network Real-Time Kinematic

Network RTK (Real-Time Kinematic) is a technology that is based on GPS (Global Positioning System) or more generally on GNSS (Global Navigation Satellite System) observations to achieve centimeter-level accuracy positioning in real time. It is enabled by a network of Continuously Operating Reference Stations (CORS). CORS placement is an important problem in the design of network RTK as it directly affects not only the installation and running costs of the network RTK, but also the Quality of Service (QoS) provided by the network RTK. In our preliminary research on the CORS placement, we proposed a polynomial heuristic algorithm for a so-called location-based CORS placement problem. From a computational point of view, the location-based CORS placement is a largescale combinatorial optimization problem. Thus, although the heuristic algorithm is efficient in computation time it may not be able to find an optimal or near optimal solution. Aiming at improving the quality of solutions, this paper proposes a repairing genetic algorithm (RGA) for the location-based CORS placement problem. The RGA has been implemented and compared to the heuristic algorithm by experiments. Experimental results have shown that the RGA produces better quality of solutions than the heuristic algorithm.

A design methodology for selecting and placement of sensors in multimedia surveillance systems

This paper addresses the problem of how to select the optimal number of sensors and how to determine their placement in a given monitored area for multimedia surveillance systems. We propose to solve this problem by obtaining a novel performance metric in terms of a probability measure for accomplishing the task as a function of set of sensors and their placement. This measure is then used to find the optimal set. The same measure can be used to analyze the degradation in system 's performance with respect to the failure of various sensors. We also build a surveillance system using the optimal set of sensors obtained based on the proposed design methodology. Experimental results show the effectiveness of the proposed design methodology in selecting the optimal set of sensors and their placement.