There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Self-Organizing Map

With construction of new large-scale water storage projects on the wane in the U.S. and other developed countries, attention must focus on improving the operational effectiveness and efficiency of existing reservoir systems for maximizing the beneficial uses of these projects. Optimal coordination of the many facets of reservoir systems requires the assistance of computer modeling tools to provide information for rational management and operational decisions. The purpose of this review is to assess the state-of-the-art in optimization of reservoir system management and operations and consider future directions for additional research and application. Optimization methods designed to prevail over the high-dimensional, dynamic, nonlinear, and stochastic characteristics of reservoir systems are scrutinized, as well as extensions into multiobjective optimization. Application of heuristic programming methods using evolutionary and genetic algorithms are described, along with application of neural networks and fuzzy rule-based systems for inferring reservoir system operating rules.

Optimal Operation of Multireservoir Systems: State-of-the-Art Review

This paper forms the second part of the series on application of artificial neural networks (ANNs) in hydrology. The role of ANNs in various branches of hydrology has been examined here. It is foun...

Artificial Neural Networks in Hydrology. II: Hydrologic Applications

Modeling and adaptive control of redundant robots

A principal component stochastic dynamic programming algorithm for stochastic multireservoir hydropower system operation optimization was proposed by Saad and Turgeon (1988). The dimension of the state space of the system is reduced by using only the major principal components of the system's state as determined by a principal component analysis of the results of a deterministic optimization. A significant refinement of the procedure is to employ censored-data principal component analysis. The more sophisticated statistical analysis provides a better model of the full dynamic range of the reservoir system's state, explains more observed variability of the reservoir volumes, and provides more accurate estimates of the statistical description's parameters. In an example presented of a four-reservoir system, the first component of the censored-data principal component analysis, for a given month, explained all but 7% of the uncensored system's variability, whereas the standard analysis for the same month left 12% of the observed system's variability unexplained.

Censored‐data correlation and principal component dynamic programming

This manuscript presents a decentralised control scheme for coordinated SVC (CSVC) of large-scale power networks. In this way, for each area of the power grid, a model predictive controller (MPC) which modifies the set points of reactive power compensators participating in CSVC algorithm is designed. The proposed controller takes into account reactive power limits of these compensation devices. The novelty of the method lies in the consideration of measured reactive power deviation on tie-lines between neighbouring areas as measured disturbance and compensation of the disturbance by regional MPC controllers. As another contribution of this work, the validation of the proposed algorithm is done in real-time simulation environment in which the decentralised MPC controllers are run in parallel on separate computational cores. The stability and robustness of the presented algorithm is validated for a large-scale realistic transmission network with 5000 buses considering standard communication protocols to send and receive the data. Simulation results show that the proposed method can regulate the voltages on the pilot buses at the desired values in the presence of load variations and communication delays. Finally, the computational burden of the proposed method is evaluated in real time.

Decentralised coordinated secondary voltage control of multi-area power grids using model predictive control

Passengers' comfort in long road trips is of crucial importance; as a result, active suspension control became a vital subject in recent researches. This paper studies the control of an electro-hydraulic active suspension, based on the backstepping control strategy. Our goal is to control the car vertical motion and keep it to zero, in order to ensure passengers' comfort. The active suspension model is highly non-linear and non-differentiable due to the hydraulic components, especially the servo-valve. Moreover, in most studies, it was always assumed that the chamber volume of the hydraulic actuator is constant, while in fact the volume varies with the piston motion. This induces an additional non-linear term to the classic model. Therefore, a powerful control strategy is needed, and the backstepping is used here for being a powerful non-linear approach able to overwhelm all these facets. However, choosing the car vertical motion as the control variable results in an unstable zero dynamics; hence, it is often combined with another variable such as the suspension travel or the vertical acceleration. To remedy this problem, we introduced a damping term in the mathematical model to ensure that zero dynamics will remain stable regardless of the control variable choice. As it will be demonstrated, the backstepping used with the model we established is an ideal drive by wire control to compensate road fluctuations

Drive by wire control of an electro-hydraulic active suspension a backstepping approach

This paper presents an upper extremity (UE) wearable robot, ETS-MARSE and its control strategy to provide movement assistance and active rehabilitation exercises to physically disabled individuals having impaired UE function. The ETS-MARSE was designed to be worn on the lateral side of UE and is able to assist arm movements at the level of shoulder, elbow, forearm and wrist joint movements. Considering the dynamic modelling of the robot system and the UE motion which are non-linear in nature, a non-linear sliding mode control with exponential reaching law was used to manoeuvre the ETS-MARSE and to provide both passive and assisted arm movement therapy. To provide passive arm movement therapy, pre-programmed trajectories corresponding to recommended passive rehabilitation exercises were used to manoeuvre the ETS-MARSE, whereas in case of assisted rehabilitation therapy user interaction wrist force sensor signals were used to steer the ETS-MARSE in assisting the UE movements. Experiments involving healthy human subjects were performed with the developed ETS-MARSE to evaluate the controller’s performance and that of the ETS-MARSE in regards to providing the therapeutic exercises. Experimental results indicate that with the proposed control strategy, ETS-MARSE can effectively deliver rehabilitation exercises.

Maarouf Saad

Papers

Modeling and adaptive control of redundant robots

Censored‐data correlation and principal component dynamic programming

Decentralised coordinated secondary voltage control of multi-area power grids using model predictive control

Drive by wire control of an electro-hydraulic active suspension a backstepping approach

Force-position control of a robotic exoskeleton to provide upper extremity movement assistance