Showing papers by "Abdul Rashid Husain published in 2015"

Enhanced Backstepping Controller Design with Application to Autonomous Quadrotor Unmanned Aerial Vehicle

Abstract: Quadrotor unmanned aerial vehicle (UAV) is an underactuated multi-input and multi-output (MIMO) system which has nonlinear dynamic behavior such as high coupling degree and unknown nonlinearities. It is a great challenge to design a quadrotor control system due to these features. In this paper, the contribution is focused on the backstepping-based robust control design of the quadrotor UAV. Firstly, the dynamic model of the aerial vehicle is mathematically formulated. Then, a robust controller is designed for the stabilization and tracking control of the vehicle. The developed robust control system comprises a backstepping and a proportional-derivative (PD) controller. Backstepping is a recursive design methodology that uses Lyapunov theorem which can guarantee the stability of the nominal model system, while PD control is used to attenuate the effects caused by system uncertainties. For the problem of determining the backstepping control parameters, particle swarm optimization (PSO) algorithm has been employed. In addition, the genetic algorithm (GA) technique is also adopted for the purpose of performance comparison with PSO scheme. Finally, the designed controller is experimentally evaluated on a quadrotor simulation environment to demonstrate the effectiveness and merits of the theoretical development.

Intelligent adaptive backstepping control for MIMO uncertain non-linear quadrotor helicopter systems:

Abstract: Designing a controller for multi-input-multi-output (MIMO) uncertain non-linear systems is one of the most important challenging works. In this paper, the contribution is focused on the design and analysis of an intelligent adaptive backstepping control for a MIMO quadrotor helicopter perturbed by unknown parameter uncertainties and external disturbances. The design approach is based on the backstepping technique and uses a radial basis function neural network (RBFNN) as a perturbation approximator. First, a backstepping controller optimized by the particle swarm optimization is developed for a nominal helicopter dynamic model. Then, the unknown perturbations are approximated based on the universal approximation property of the RBFNN. The parameters of the RBFNN are adjusted through online learning. To improve the control design performance further, a fuzzy compensator is introduced to eliminate the approximation error produced by the neural approximator. Asymptotical stability of the closed-loop control system is analytically proven via the Lyapunov theorem. The main advantage of the proposed methodology is that no prior knowledge of parameter uncertainties and disturbances is required. Simulations of hovering and trajectory tracking missions of a quadrotor helicopter are conducted. The results demonstrate the effectiveness and feasibility of the proposed approach

Stabilization and trajectory tracking control for underactuated quadrotor helicopter subject to wind-gust disturbance

Abstract: The control of quadrotor helicopter has been a great challenge for control engineers and researchers since quadrotor is an underactuated and a highly unstable nonlinear system. In this paper, the dynamic model of quadrotor has been derived and a so-called robust optimal backstepping control (ROBC) is designed to address its stabilization and trajectory tracking problem in the existence of external disturbances. The robust controller is achieved by incorporating a prior designed optimal backstepping control (OBC) with a switching function. The control law design utilizes the switching function in order to attenuate the effects caused by external disturbances. In order to eliminate the chattering phenomenon, the sign function is replaced by the saturation function. A new heuristic algorithm namely Gravitational Search Algorithm (GSA) has been employed in designing the OBC. The proposed method is evaluated on a quadrotor simulation environment to demonstrate the effectiveness and merits of the theoretical development. Simulation results show that the proposed ROBC scheme can achieve favorable control performances compared to the OBC for autonomous quadrotor helicopter in the presence of external disturbances.

A hybrid optimal backstepping and adaptive fuzzy control for autonomous quadrotor helicopter with time-varying disturbance:

Abstract: In this paper, a hybrid control system called as backstepping adaptive fuzzy control system, which integrates nominal and compensation controller is developed for autonomous quadrotor helicopter with inherent time-varying disturbance. In this hybrid control system, the nominal controller based on backstepping technique is the main controller, and the compensation controller containing a fuzzy control approach is used to eliminate the effect of uncertainties caused by external disturbance. In addition, in order to relax the requirement of prior knowledge on the bound of external disturbance, an online adaptation law is derived. Asymptotical stability of the closed-loop control system is analytically proven via the Lyapunov theorem. For the problem of determining the backstepping control parameters, particle swarm optimization algorithm has been employed. Finally, the designed controller is experimentally evaluated on a quadrotor simulation environment to demonstrate the effectiveness and merits of the theoretical development.

Robust precision control for a class of electro-hydraulic actuator system based on disturbance observer

Abstract: This paper presents a new robust control scheme for a class of electro-hydraulic actuator using dynamic sliding mode control associated with nonlinear disturbance observer. Switching-gain of the sliding mode is designed to be adaptable on the estimated disturbance. A switching-gain adaptation mechanism is proposed to obtain as small as possible switching-gain to minimize chattering effect. The scheme is developed to guarantee the tracking precision of the system with robust and smooth control actions in the existence of uncertainties and the changes of external disturbance. Capability of the proposed scheme is enhanced by varying boundary layers algorithm to assist the scheme to return to its ability in a larger change of external disturbance. Capability and effectiveness of the proposed scheme are validated through experiment, where the results indicate that the proposed scheme ensures the tracking precision of the system with robust and smooth control actions in a large change of external load disturbance. Moreover, smooth control actions that are produced by the proposed control scheme offer a significant efficiency of energy in the control of electro-hydraulic actuator systems.

Lyapunov-Krasovskii stability condition for system with bounded delay - An application to steer-by-wire system

Abstract: This work presents a study on the stabilization of a class of linear systems with bounded delays in the control input and system states. A methodology for the stabilization expressed in linear matrix inequalities (LMIs), where it is shown that the proposed stabilization theorem is able to maintain the system stability under some bounded time delay. LMI approach is the most popular due to it can be formulated into a convex optimization problem. Finally, the technique is applied to the steer-by-wire problem as a test bed, showing how it is possible to derive efficient controllers for realistic problems, using the proposed technique.

A Comparative Study of Linear ARX and Nonlinear ANFIS Modeling of an Electro-Hydraulic Actuator System

Abstract: The existence of a high degree of nonlinearity in Electro-Hydraulic Actuator (EHA) has imposed a challenge in development of a representable model for the system such as that significant control performance can be proposed. In this work, linear Autoregressive with Exogenous (ARX) model and nonlinear Adaptive Neuro-Fuzzy Inference System (ANFIS) model of an EHA system are obtained based on the mathematical model of the system. Linear ARX modeling technique has been widely applied on EHA system and satisfying result has been obtained. On the other hand, ANFIS modeling technique can model nonlinear system at high accuracy. Both models are validated offline using data set obtained and using different stimulus signals when doing online validation. Offline validation test shows that ANFIS model has 99.37% best fitting accuracy, which is more accurate than 93.75% in ARX model. ARX model fails in some online validation tests, while ANFIS model has been consistently accurate in all tests with RMSE lower than 0.25.

GSA-based optimal backstepping controller with a fuzzy compensator for robust control of an autonomous quadrotor UAV

Abstract: Purpose – The purpose of this paper is to propose a new approach for robust control of an autonomous quadrotor unmanned aerial vehicle (UAV) in automatic take-off, hovering and landing mission and also to improve the stabilizing performance of the quadrotor with inherent time-varying disturbance. Design/methodology/approach – First, the dynamic model of the aerial vehicle is mathematically formulated. Then, a combination of a nonlinear backstepping scheme with the intelligent fuzzy system as a new key idea to generate a robust controller is designed for the stabilization and altitude tracking of the vehicle. For the problem of determining the backstepping control parameters, a new heuristic algorithm, namely, Gravitational Search Algorithm has been used. Findings – The control law design utilizes the backstepping control methodology that uses Lyapunov function which can guarantee the stability of the nominal model system, whereas the intelligent system is used as a compensator to attenuate the effects cau...

Model and analysis of wind speed profile using artificial neural network - feasibility study in Peninsular Malaysia

Abstract: Accurate modeling of wind speed profile is crucial as the wind speed dynamics are non-deterministic, having chaotic behavior and highly nonlinear in nature. Therefore, obtaining mathematical model of such wind speed profile is rather difficult and vague. In this brief manuscript, the wind speed distribution in Peninsular Malaysia is modeled via the real-time wind data obtained from the Malaysian Meteorological Services (MMS). Artificial neural network (ANN) has been exploited to train the data such that the exact model of wind speed can be identified. The induced wind speed model worthwhile for control engineers to develop control apparatus for wind turbine systems at the selected area of studies. With the wind speed distribution profile, turbine output power can be analyzed and were discussed thoroughly.

Nonlinear stabilization with bounded controller

Abstract: This In this paper, an extension of the Sontag's universal formula is proposed. For benchmark, the proposed method is compared with two other approaches, i.e. a universal Sontag's formula and a direct Lyapunov with comparing square. To observe the efficacy of the proposed method, a numerical nonlinear system with cubic damping is stabilized. The effectiveness of the proposed method is shown that the magnitude of the control signal can be bounded without a catastrophic effect to the closed loop stability. Other appealing features of the proposed method is that the stabilization cost can be reduced, and the elimination of the useful nonlinear terms can be avoided.

Adaptive input shaping for sway control of 3D crane using a pole-zero cancellation method

Abstract: This paper presents an adaptive input shaping based on pole-zero cancellation (APZC) technique to suppress load sway of a crane system. In this method, a reference system is selected and the proposed adaptive shaper is made to force the actual system to adapt to the changes in natural frequency and damping ratio as the cable length increases or decreases. Simulation results are compared with a zero vibration derivative input shaper designed based on average travel length (ATL) to investigate the performance of the proposed shaper. Simulation using three cable length of 0.7 m, 0.5 m and 0.3 m shows that APZC gives better payload sway reduction with smallest maximum sway.

LMI-based state feedback controller design for vibration control of a negative imaginary system

Abstract: This paper presents state feedback control via linear matrix inequality (LMI) for vibration control of a flexible link manipulator (FLM) system. FLM is a negative imaginary (NI) system with high amplitude vibration and oscillation. In this work, pole placement controller (PPC) which is NI controller is used to control the FLM vibration, to achieve a precise hub angle positioning with minimum tip deflection. A decay rate is introduced to improve the speed of the system and investigate the effect on the system performance. LMI optimization technique is used to obtain the optimal and best control gains of PPC using Matlab LMI toolbox with different values of the decay rate. Simulation results show that satisfactory hub angle and tip deflection responses are achieved using the proposed controller. Damping is successfully added into the system and reduces the system vibration at the first two vibration modes by 40 dB. Hub angle positioning is achieved with minimum tip deflection by changing the value of decay rate.

Development of a strict feedback two-mass horizontal axis wind turbine model with empirical power coefficient and external stiffness

Abstract: For a variable speed wind turbine, the control approach requires the exact dynamical model of such wind turbine to be under controlled. The established wind turbine dynamics neglect the external stiffness as an integrator to the system dynamics is introduced. In addition, many approaches assume a constant value for the coefficient, which is practically not a valid choice. Hence, this paper proposed a strict feedback model of a two-mass wind turbine system that focused on external stiffness, and also embedded empirical power coefficient in the system dynamics. The model represented in this study is a "ready-to-be-used" form that benefits the control system engineers when the feedback control approaches are taken into account.

A Universal Formula for Asymptotic Stabilization with Bounded Controls

Abstract: Motivated by Artstein and Sontag universal formula, this brief paper presents an explicit proof of the universal formula for asymptotic stabilization and asymptotic disturbance rejection of a nonlinear system with mismatched uncertainties and time varying disturbances. We prove the stability via Lyapunov stability criteria. We also prove that the control law satisfies small control property such that the magnitude of the control signal can be bounded without the catastropic effect to the closed loop stability. For clarity, we benchmark the proposed approach with other method namely a Lyapunov redesign with nonlinear damping function. We give a numerical example to verify the results.

A time-varying saturated synchronous formation controller for nonholonomic mobile robots

Abstract: In this paper, a new saturated synchronous controller is proposed for multiple nonholonomic wheeled mobile robots to perform a time-varying formation task. Each robot is controlled to track its desired trajectory, while synchronized its motion with the two neighboring robots. A novel dynamic model of the wheeled mobile robot is derived based on Lagrange method. The Lagrange multipliers of the robot are determined based on the input torques and the robot's velocities. The dynamic model is divided into translational and rotational model. A saturated synchronous translational controller is proposed to guarantee the asymptotic stability of both position and synchronization errors. A rotational controller is developed such that each robot always oriented towards its desired position. A simulation results verified the efficiency of the proposed saturated synchronous controller in the formation tasks.