Regression between headmaster leadership, task load and job satisfaction of special education integration program teacher

Managing school is a daunting task for a headmaster. This responsibility is exacerbated when it involves the Special Education Integration Program (SEIP). This situation requires appropriate and effective leadership in addressing some of the issues that are currently taking place at SEIP such as task load and job satisfaction. This study aimed to identify the influence of headmaster leadership on task load and teacher job satisfaction at SEIP. This quantitative study was conducted by distributing 400 sets of randomized questionnaires to SEIP teachers across Malaysia through google form. The data obtained were then analyzed using Structural Equation Modeling (SEM) and AMOS software. The results show that there is a significant positive effect on the leadership of the headmaster and the task load of the teacher. Likewise, the construct of task load and teacher job satisfaction has a significant positive effect. However, for the construct of headmaster leadership and teacher job satisfaction, there was no significant positive relationship. This finding is very important as a reference to the school administration re-evaluating their leadership so as not to burden SEIP teachers and to give them job satisfaction. In addition, the findings of this study can also serve as a guide for SEIP teachers to increase awareness of the importance of managing their tasks. This study also focused on education leadership in general and more specifically on special education leadership

Development of deep reinforcement learning for inverted pendulum

This paper presents a modification of the deep Q-network (DQN) in deep reinforcement learning to control the angle of the inverted pendulum (IP). The original DQN method often uses two actions related to two force states like constant negative and positive force values which apply to the cart of IP to maintain the angle between the pendulum and the Y-axis. Due to the changing of too much value of force, the IP may make some oscillation which makes the performance system could be declined. Thus, a modified DQN algorithm is developed based on neural network structure to make a range of force selections for IP to improve the performance of IP. To prove our algorithm, the OpenAI/Gym and Keras libraries are used to develop DQN. All results showed that our proposed controller has higher performance than the original DQN and could be applied to a nonlinear system

Neural controller for the trajectory tracking control of an inertia wheel pendulum

En este trabajo de investigación, se estudia el problema de control de seguimiento de trayectorias en un péndulo de rueda inercial. Los resultados son presentados de una forma constructiva. Primero, se obtiene un controlador basado en el modelo utilizando la técnica de linealización por retroalimentación de salida. Posteriormente, el controlador es rediseñado al incorporar una red neuronal con el propósito de evitar el conocimiento de los parámetros exactos del péndulo de rueda inercial, y se obtiene un diseño robusto. Se usa un perceptrón de dos capas, cuyos pesos de salida son actualizados en tiempo real utilizando una ley de adaptación derivada del análisis de convergencia de las soluciones del sistema de lazo cerrado. El lema de Barbalat se utiliza para concluir que las trayectorias del error de seguimiento del péndulo convergen a cero. Se presentan simulaciones numéricas y experimentos en tiempo real, que confirman los resultados teóricos.In this paper, the problem of trajectory tracking control in an inertia wheel pendulum is studied. Results are presented in a constructive form. First, a model-based controller is obtained by using the output feedback linearization technique. Then, the controller is redesigned by incorporating a neural network with the aim of avoiding the exact parameters knowledge of the inertia wheel pendulum, obtaining a robust control scheme. A two-layer perceptron is used, whose output weights are updated in real-time using an adaption law derived from the analysis of convergence of the closed-loop system solutions. Barbalats lemma is used to conclude that the pendulum tracking error trajectory converges to zero. Numerical simulations and real-time experiments are presented, which confirm the theoretical results.Peer Reviewe

CONTROL OF A PENDULUM USING HEDGE ALGEBRAS CONTAINING ACTUATOR SATURATION

In this study, the control problem of a pendulum using hedge-algebras-based fuzzy controller (HAC) containing actuator saturation is presented. In HAC, linguistic values of linguistic terms are obtained through semantically quantifying mappings (SQMs) based on several fuzzy parameters of each linguistic variable without using any fuzzy set and inherent order relationships between linguistic values are always ensured. Hence, the design of a HAC leads to determining parameters of SQMs. Numerical results of HAC are compared with those of an analogical conventional fuzzy controller (FC) in order to show advantages of the proposed method.In this study, the control problem of a pendulum using hedge-algebras-based fuzzy controller (HAC) containing actuator saturation is presented. In HAC, linguistic values of linguistic terms are obtained through semantically quantifying mappings (SQMs) based on several fuzzy parameters of each linguistic variable without using any fuzzy set and inherent order relationships between linguistic values are always ensured. Hence, the design of a HAC leads to determining parameters of SQMs. Numerical results of HAC are compared with those of an analogical conventional fuzzy controller (FC) in order to show advantages of the proposed method

Optimal fuzzy control using hedge algebras of a damped elastic jointed inverted pendulum

In this paper, three controllers including OFCHA (optimal fuzzy control using hedge algebras-HAs), FCHA (fuzzy control using HAs) and CFC (conventional fuzzy control) are designed. Our attention is paid to the stability in the vertical position of a damped-elastic-jointed inverted pendulum subjected to a time-periodic follower force. Different values of the pendulum length are considered. Simulation results are exposed to illustrate the effect of OFCHA in comparison with FCHA and CFC

Lifting and stabilizing of two-wheeled wheelchair system using interval type-2 fuzzy logic control based spiral dynamic algorithm

The current study emphasizes on improving an interval type-2 fuzzy logic control (IT2FLC) system through the use of spiral dynamics algorithm (SDA) optimization in stabilizing a transformational two-wheeled wheelchair. The main contribution of this research is to reduce vibrations while performing the lifting and stabilization of a wheelchair from its standard four-wheeled to two-wheeled transformation. IT2FLC based SDA was used to enhance the system’s stability performance by obtaining the optimized value for input and output controller gains and IT2FLC parameters for IT2FLC. System modeling was done through development within the SimWise 4D software environment, which was then integrated with MATLAB/SIMULINK for control purposes. The proposed algorithm has demonstrated improved tilt angle performance with reduced noise and lower torque when various disturbances were applied, as compared to a system solely controlled by IT2FLC without any optimization. Moreover, the proposed algorithm has also comprehensively outperformed previous controllers in terms of system’s stability, further demonstrated its superiority as a system controller within transformational wheelchairs

Stability analysis of non-holonomic inverted pendulum system

The inverted pendulum is doubtlessly one of the most famous control problems found in most control text books and laboratories worldwide. This popularity comes from the fact that the inverted pendulum exhibits nonlinear, unstable and non-minimum phase dynamics. The basic control objective of the study is to design a controller in order to maintain the upright position of the pendulum while also controlling the position of the cart. In our study we explored the relationship that the tuning parameters (weight on the position of the car and the angle that the pendulum makes with the vertical) of a classical inverted pendulum on a cart has on the pole placement and hence on the stability of the system. We then present a family of curves showing the local root-locus and develop relationships between the weight changes and the system performance. We describe how these locus trends provide insight that is useful to the control designer during the effort to optimize the system performance. Finally, we use our general results to design an effective feedback controller for a new system with a longer pendulum, and present experiment results that demonstrate the effectiveness of our analysis. We then designed a simulation-based study to determine the stability characteristics of a holonomic inverted pendulum system. Here we decoupled the system using geometry as two independent one dimensional inverted pendulum and observed that the system can be stabilized using this method successfully with and without noise added to the system. Next, we designed a linear system for the highly complex inverted pendulum on a non-holonomic cart system. Overall, the findings will provide valuable input to the controller designers for a wide range of applications including tuning of the controller parameters to design of a linear controller for nonlinear systems

On Stabilization of Cart-Inverted Pendulum System: An Experimental Study

The Cart-Inverted Pendulum System (CIPS) is a classical benchmark control problem. Its dynamics resembles with that of many real world systems of interest like missile launchers, pendubots, human walking and segways and many more. The control of this system is challenging as it is highly unstable, highly non-linear, non-minimum phase system and underactuated. Further, the physical constraints on the track position control voltage etc. also pose complexity in its control design. The thesis begins with the description of the CIPS together with hardware setup used for research, its dynamics in state space and transfer function models. In the past, a lot of research work has been directed to develop control strategies for CIPS. But, very little work has been done to validate the developed design through experiments. Also robustness margins of the developed methods have not been analysed. Thus, there lies an ample opportunity to develop controllers and study the cart-inverted pendulum controlled system in real-time. The objective of this present work is to stabilize the unstable CIPS within the different physical constraints such as in track length and control voltage. Also, simultaneously ensure good robustness. A systematic iterative method for the state feedback design by choosing weighting matrices key to the Linear Quadratic Regulator (LQR) design is presented. But, this yields oscillations in cart position. The Two-Loop-PID controller yields good robustness, and superior cart responses. A sub-optimal LQR based state feedback subjected to H∞ constraints through Linear Matrix Inequalities (LMIs) is solved and it is observed from the obtained results that a good stabilization result is achieved. Non-linear cart friction is identified using an exponential cart friction and is modeled as a plant matrix uncertainty. It has been observed that modeling the cart friction as above has led to improved cart response. Subsequently an integral sliding mode controller has been designed for the CIPS. From the obtained simulation and experiments it is seen that the ISM yields good robustness towards the output channel gain perturbations. The efficacies of the developed techniques are tested both in simulation and experimentation. It has been also observed that the Two-Loop PID Controller yields overall satisfactory response in terms of superior cart position and robustness. In the event of sensor fault the ISM yields best performance out of all the techniques

Avaliação de marcha e postura em reabilitação

Tese de mestrado integrado. Bioengenharia (Engenharia Biomédica). Universidade do Porto. Faculdade de Engenharia. 201

Optimal control of wind energy conversion systems with doubly-fed induction generators

Wind energy conversion systems (WECSs) have become the interesting topic over recent years for the renewable electrical power source. They are a more environmentally friendly and sustainable resource in comparison with the fossil energy resource. The WECS using a doubly-fed induction generator (DFIG) to convert mechanical power into electrical power has a significant advantage. This WECS requires a smaller power converter in comparison with a squirrel cage induction generator. Efficiency of the DFIG-WECS can be improved by a suitable control system to maximise the output power from WECS. A maximum power point tracking (MPPT) controller such as tip-speed ratio (TSR)control and power signal feedback (PSF) control is use to maximise mechanical power from wind turbine and a model-based loss minimisation control (MBLC) is used to minimise electrical losses of the generator. However, MPPT and MBLC require the parameters of the wind turbine and the generator for generating the control laws like optimal generator speed reference and d-axis rotor current reference. The Efficiencies of the MPPT and MBLC algorithms deteriorate when wind turbine and generator parameters change from prior knowledge. The field oriented control for a DFIG in the WECS is extended by introducing a novel control layer generating online optimal generator speed reference and d-axis rotor current reference in order to maximise power produced from the WECS under wind turbine and DFIG parameter uncertainties, which is proposed. The single input rule modules (SIRMs) connected fuzzy inference model is applied to the control algorithm for optimal power control for variable-speed fixed-pitch wind turbine in the whole wind speed range by generating an online optimal speed reference to achieve optimal power under wind turbine parameter uncertainties. The proposed control combines a hybrid maximum power point tracking (MPPT) controller, a constant rotational speed controller for below-rated wind speed and a limited-power active stall regulation by rotational speed control for above-rated wind speed. The three methods are appropriately organised via the fuzzy controller based SIRMs connected fuzzy inference model to smooth transition control among the three methods. The online parameter estimation by using Kalman filter is applied to enhance model-based loss minimisation control (MBLC). The d-axis rotor current reference of the proposed MBLC can adapt to the accurate determination of the condition of minimum electrical losses of the DFIG when the parameters of the DFIG are uncertain. The proposed control algorithm has been verified by numerical simulations in Matlab/Simulink and it has been demonstrated that the energy generated for typical wind speed profiles is greater than that of a traditional control algorithm based on PSF MPPT and MBLC