Data-driven occupant-centric rules of automated shade adjustments: Luxembourg case study

This study presents key findings of observed datasets in a nearly zero-energy office building for over 66 working days from June to mid-September in 2019, Luxembourg. Measurements of indoor and outdoor environmental parameters as well as user-shade override adjustments were extracted from the KNX-based building management system (BMS) in 47 office rooms located in three typical floor levels. Relative frequency and “rate of change” of blind use were analysed in terms of window orientation, occupancy level, and the time of the day. Logistic regression and data mining techniques were used to identify potentially useful and understandable occupant behaviour patterns and reveal the main triggers behind blind adjustments. The well-designed automation system together with the inner glare protection formed the base of very low user-shade interactions. A mean of 0.184 manual blind adjustments per day per office. Eight regression sub-models were developed and all were incapable of predicting user-shade lowering and raising events. Alternatively, two user profiles were mined based on 20 rules gained from clustering analysis: user (ß) was representing the passive user, and user (μ) the medium user. Overall, we conclude that the automated shading system in this building is satisfactory, user-friendly, and a robust control system.

Development of Fuzzy Based Autoregressive Moving Average Exogenous Input Model for Water Flow in Nigerian Kanji Hydro-Power Dam

Design of robust control system for any system requires model-driven approach. Therefore, it becomes imperative to develop a dynamic model suitable for controller design on safety operation of hydropower dam for power production in Kanji dam in Nigeria. Model for reservoir flow was developed in MATLAB environment using Fuzzy Based Autoregressive Moving Average Exogenous Input (FARMAX) model structure in this study. The data used for model development covered a period of ten years (2003-2013). It consists of water inflow (WI), water outflow (WO) and spillage (S). WI and S are input variables while WO was the output variable. The model obtained using the unsmoothed data with an outlier gave -14.115%, -0.302 and 610.317 for fit, R2 and RMSE, respectively. Unsmoothed data with no outlier gave -13.802%, -0.295 and 608.643 corresponding to fit, R2 and RMSE, respectively. The model obtained using the smoothed data in the presence of an outlier gave 80.533%, 0.962 and 104.113 for fit, R2 and RMSE, respectively. Smoothed data in the absence of outlier gave 81.533%, 0.962 and 99.637 for to fit, R2 and RMSE, respectively. FARMAX has the best fit value of 87.8774% when number of rules was equal to 3 with optima model order of 3 1 4 3. The model can serve as a decision support system in evaluating the optimal reservoir operation policies in real time.

Robust control strategy for improving the performance of a soft robotic link

The robotic neck mechanism considered in this paper has as main element a soft link that emulates a human neck with two DOF (flexion, extension and lateral bending). The mechanism is based on a Cable-Driven Parallel Mechanism (CDPM) with components easy to manufacture in a 3D printer.Due to the soft link properties and the platform mechanics, it is important to provide a robust control system. Two designs, a robust PID controller and a Fractional Order PI controller (FOPI) are proposed and compared, the fractional order control showing an enhanced performance. Both control approaches are tested in the real prototype, validating the soft neck feasibility and showing the robustness of the platform to mass changes at the neck tip.

Improved Neural Network Adaptive Control for Compound Helicopter with Uncertain Cross-Coupling in Multimodal Maneuver

The main goal of this study was to create a robust control system that could guide or replace the pilots in tracking of commanded velocity and attitude in multimodal maneuver, while complex dynamics and uncertain aerodynamic cross-coupling among control surfaces of compound helicopter are considered. To this end, a Pi-Sigma neural network (PSNN) adaptive controller is proposed based upon the certainty-equivalence (CE) principle, where a novel Lyapunov-based weight self-tuning algorithm augmented with e-modification is designed to realize efficient uncertainty approximation and guarantee robustness of convergence process. Compared with traditional neural networks in control field, stronger generalization ability of PSNN must be balanced against weaker stability, which leads to inevitable parameters perturbation. Therefore, an incremental nonlinear dynamic inversion (INDI) framework is established to decouple original overactuated system and reject parameters perturbation in PSNN. Meanwhile, by incorporating Lagrang- multiplier method into allocation, an original incremental allocation method is designed to get globally ideal control input according to time-varying working capability of each surface. In terms of Lyapunov theorem, it is demonstrated that the closed-loop augmented system driven by the proposed control scheme is semi-global uniformly ultimately bounded (SGUUB). Finally, the simulation result validates the effectiveness of proposed control scheme.

Nonlinear robust control of large-scale system with input saturation

The article studies control algorithms of multiply connected system for dynamic plants with control saturation and nonlinear cross-connections. The authors of the article offer a decentralized control law based on the hyperstability criterion. They also use this law to constuct the MIMO servo system with input saturation. To illustrate the capability of the proposed decentralized robust control system the authors use an inverted pendulums connected by a spring.

Cascade control for heterogeneous multirotor UAS

PurposeDespite of the numerous characteristics of the multirotor unmanned aircraft systems (UASs), they have been termed as less energy-efficient compared to fixed-wing and helicopter counterparts. The purpose of this paper is to explore a more efficient multirotor configuration and to provide the robust and stable control system for it.Design/methodology/approachA heterogeneous multirotor configuration is explored in this paper, which employs a large rotor at the centre to provide majority of lift and three small tilted booms rotors to provide the control. Design provides the combined characteristics of both quadcopters and helicopters in a single UAS configuration, providing endurance of helicopters keeping the manoeuvrability, simplicity and control of quadcopters. In this paper, rotational as well as translational dynamics of the multirotor are explored. Cascade control system is designed to provide an effective solution to control the attitude, altitude and position of the rotorcraft.FindingsOne of the challenging tasks towards successful flight of such a configuration is to design a stable and robust control system as it is an underactuated system possessing complex non-linearities and coupled dynamics. Cascaded proportional integral (PI) control approach has provided an efficient solution with stable control performance. A novel motor control loop is implemented to ensure enhanced disturbance rejection, which is also validated through Dryden turbulence model and 1-cosine gust model.Originality/valueRobustness and stability of the proposed control structure for such a dynamically complex UAS configuration is demonstrated with stable attitude and position performance, reference tracking and enhanced disturbance rejection.

Stability analysis of Automatic Voltage Regulator using Fractional Order Controller

We aim to design a fractional order robust control system. It is an advanced model of classic PID controller whose order will be non-integer.PID controller that we generally use has many advantages and disadvantages with respect to the disadvantages like, it doesn’t give accurate values of constants, exact values of the time domain parameters as well as frequency domain parameters of the control system and we have more robust problem. Wearable electronic based an automatic voltage regulator can automatically preservesthe terminal voltage of generator at a fixed value under varyingly load and operating temperature. AVR controls output by sensing the output voltage at a power-generating coil and compares it to a stable reference. The combination of fractional order controller with an automatic voltage regulator is proved to be better than conventional controllers.