Optimal H∞ insulin injection control for blood glucose regulation in diabetic patients

The theory of H/sup /spl infin// optimal control has the feature of minimizing the worst-case gain of an unknown disturbance input. When appropriately modified, the theory can be used to design a "switching" controller that can be applied to insulin injection for blood glucose (BG) regulation. The "switching" controller is defined by a collection of basic insulin rates and a rule that switches the insulin rates from one value to another. The rule employed an estimation of BG from noisy measurements, and the subsequent optimization of a performance index that involves the solution of a "jump" Riccati differential equation and a discrete-time dynamic programming equation. With an appropriate patient model, simulation studies have shown that the controller could correct BG deviation using clinically acceptable insulin delivery rates.

Direct method for optimal power management in hybrid electric vehicles

Hybrid electric vehicles are powered by an electric system and an internal combustion engine. The components of a hybrid electric vehicle need to be coordinated in an optimal manner to deliver the desired performance. This paper presents an approach based on direct method for optimal power management in hybrid electric vehicles with inequality constraints. The approach consists of reducing the optimal control problem to a set of algebraic equations by approximating the state variable which is the energy of electric storage, and the control variable which is the power of fuel consumption. This approximation uses orthogonal functions with unknown coefficients. In addition, the inequality constraints are converted to equal constraints. The advantage of the developed method is that its computational complexity is less than that of dynamic and non-linear programming approaches. Also, to use dynamic or non-linear programming, the problem should be discretized resulting in the loss of optimization accuracy. The propsed method, on the other hand, does not require the discretization of the problem producing more accurate results. An example is solved to demonstrate the accuracy of the proposed approach. The results of Haar wavelets, and Chebyshev and Legendre polynomials are presented and discussed. © 2011 The Korean Society of Automotive Engineers and Springer-Verlag Berlin Heidelberg.

Robust optimal motion cueing algorithm based on the linear quadratic regulator method and a genetic algorithm

The aim of this paper is to design and develop an optimal motion cueing algorithm (MCA) based on the genetic algorithm (GA) that can generate high-fidelity motions within the motion simulator's physical limitations. Both, angular velocity and linear acceleration are adopted as the inputs to the MCA for producing the higher order optimal washout filter. The linear quadratic regulator (LQR) method is used to constrain the human perception error between the real and simulated driving tasks. To develop the optimal MCA, the latest mathematical models of the vestibular system and simulator motion are taken into account. A reference frame with the center of rotation at the driver's head to eliminate false motion cues caused by rotation of the simulator to the translational motion of the driver's head as well as to reduce the workspace displacement is employed. To improve the developed LQR-based optimal MCA, a new strategy based on optimal control theory and the GA is devised. The objective is to reproduce a signal that can follow closely the reference signal and avoid false motion cues by adjusting the parameters from the obtained LQR-based optimal washout filter. This is achieved by taking a series of factors into account, which include the vestibular sensation error between the real and simulated cases, the main dynamic limitations, the human threshold limiter in tilt coordination, the cross correlation coefficient, and the human sensation error fluctuation. It is worth pointing out that other related investigations in the literature normally do not consider the effects of these factors. The proposed optimized MCA based on the GA is implemented using the MATLAB/Simulink software. The results show the effectiveness of the proposed GA-based method in enhancing human sensation, maximizing the reference shape tracking, and reducing the workspace usage.

Constrained coordinated distributed control of smart grid with asynchronous information exchange

Smart grid constrained optimal control is a complex issue due to the constant growth of grid complexity and the large volume of data available as input to smart device control. In this context, traditional centralized control paradigms may suffer in terms of the timeliness of optimization results due to the volume of data to be processed and the delayed asynchronous nature of the data transmission. To address these limits of centralized control, this paper presents a coordinated, distributed algorithm based on distributed, local controllers and a central coordinator for exchanging summarized global state information. The proposed model for exchanging global state information is resistant to fluctuations caused by the inherent interdependence between local controllers, and is robust to delays in information exchange. In addition, the algorithm features iterative refinement of local state estimations that is able to improve local controller ability to operate within network constraints. Application of the proposed coordinated, distributed algorithm through simulation shows its effectiveness in optimizing a global goal within a complex distribution system operating under constraints, while ensuring network operation stability under varying levels of information exchange delay, and with a range of network sizes.

Path planning for sensor data collecting mobile robot

A mobile robot employed for data collection is faced with the problem of travelling from an initial location to a final location while maintaining as close a distance as possible to all the sensors at a given time in the journey. Here we employ optimal control ideas in forming the necessary control commands for such a robot resulting not only the necessary acceleration commands for the underlying robot, but also the resulting trajectory. This approach can also be easily extended for the case of producing the optimal trajectory for an ariel vehicle used for data collection from indiscriminately scattered ad-hoc sensors located on the ground. We demonstrate the implementation of our algorithm using a Pioneer 3-AT robot.

Dynamic advertising under vertical product differentiation

We investigate a dynamic advertising model where product quality is endogenous. In the differential game between single-product firms, there exists a parameter range where the low-quality firm uses a more efficient advertising technology and earns higher profits than the rival. Moreover, we show that equilibrium qualities are the same under duopoly, multiproduct monopoly, and social planning, the only distortion being concerned with the output levels.

Joint velocity redistribution for fault tolerant manipulators

If the end-effector of a robotic manipulator moves on a specified trajectory, then for the fault tolerant operation, it is required that the end-effector continues the trajectory with a minimum velocity jump when a fault occurs within a joint. This problem is addressed in the paper. A way to tolerate the fault is to find new joint velocities for the faulty manipulator in which results into the same end-effector velocity provided by the healthy manipulator. The aim of this study is to find a strategy which optimally redistributes the joint velocities for the remained healthy joints of the manipulators. The optimality is defined by the minimum end-effector velocity jump. A solution of the problem is presented and it is applied to a robotics manipulator. Then through a case study and a simulation study it is validated. The paper shows that if would be possible the joint velocity redistribution results into a zero velocity jump.

Image reconstruction using Loop subdivision

It is an ultimate objective to reconstruct an image with high quality using a compact representation, which is the basic step in image-manipulation fields. We propose an effective vectorization based approach to reconstruct an image using a triangular mesh associated with Loop subdivision scheme in the present paper. With an initial control mesh obtained by simplifying a dense mesh from a quality-preserved triangulation, we produce the final optimal control mesh by optimizing a mesh over topologies and colors to approximate the given image. The main advantages of the approach include: (1) the reconstruction of an image is not restricted to be aligned with image coordinate axes; (2) a high order continuous function is defined over a triangle instead of a bilinear interpolation; (3) it is a compact and vector-based representation easy to edit and transmit. Experimental results are presented to confirm the effectiveness of the method. Comparisons with the bi-cubic spline and the mesh simplification methods demonstrate the merits of our method in reconstruction quality and representation size.

Survival misperception, time inconsistency, and implications for life-cycle saving and welfare

Some empirical studies firmly reveal that people tend to form overly pessimistic survival expectations for relatively less distant ages and overly optimistic survival expectations for relatively more distant ages. We incorporate this observation into a life-cycle continuous time overlapping-generations model of consumption/saving with a general form for a subjective survival function. Resulting time-inconsistent optimal control problem has been analytically solved. At the micro level, time inconsistency leads to higher consumption at young and old ages, but this alone fails to improve lifetime well-being since micro-level decisions made with a lack of information about true mortality are suboptimal. In general equilibrium, however, such time inconsistent behavior with survival misperception is conducive to aggregate capital accumulation and greater equilibrium bequest income. The latter effects can produce substantial welfare gains. We also note that empirically observed old age optimistic bias is an important phenomenon, as it helps to avoid unrealistic very old-age debt accumulation within a life-cycle model. In addition, if for a given level of optimistic bias we increase early-life pessimism, this would result in slower capital accumulation, lower bequest income, and thus be detrimental to welfare. Since recent literature reports that young-age survival pessimism has grown over time, it raises some concerns.

Stability analysis and resource allocation for space-based multi-access systems

In space-based networks, the data relay satellites can assist low-earth-orbit satellites in relaying data to other satellites or the ground station and improve the real time system throughput. To take full advantage of transmission resource of the cooperative relays, this paper proposes a multiple access and resource allocation strategy, in which relays can receive and transmit simultaneously according to channel characteristics of space-based systems. Based on the queueing theoretic formulation, the stability of the proposed protocol is analyzed and the maximum stable throughput region is derived, which would provide the appropriate guidance for the design of the system optimal control. Simulation results exhibit multiple factors that affect the stable throughput and verify the theoretical analysis.

Transient stability enhancement of multimachine power systems using nonlinear observer-based excitation controller

This paper presents an approach to design a nonlinear observer-based excitation controller for multimachine power systems to enhance the transient stability. The controller is designed based on the partial feedback linearization of a nonlinear power system model which transforms the model into a reducedorder linear one with an autonomous dynamical part. Then a linear state feedback stabilizing controller is designed for the reduced-order linear power system model using optimal control theory which enhances the stability of the entire system. The states of the feedback stabilizing controller are obtained from the nonlinear observer and the performance of this observer-based controller is independent of the operating points of power systems. The performance of the proposed observer-based controller is compared to that of an exact feedback linearizing observer-based controller and a partial feedback linearizing controller without observer under different operating conditions.

Labor-leisure choice : is everything as straightforward as one might have thought?

We argue that a full understanding of a rational labor supply choice in a standard dynamic life cycle framework is obscure, despite the framework’s being seemingly self-explanatory, straightforward, and intuitively sensible. In a completely friction-free environment, we, to our knowledge, are the first to provide a complete analytic solution to the benchmark model that presumes a kind of labor supply behavior that is typically taken as the standard in economic studies. We find thatsuch standard behavior holds only for a narrow set of parameters. For many alternative parameterizations, the labor supply behavior of a rational agent is either highly unrealistic, or extremely hard to predict and interpret. A complete understanding of a rational, intertemporal labor supply choice requires further analysis.