Conditions for triangular decoupling control

The main purpose of this article is to explore the relationship of two existing conditions for the triangular decoupling problem. The first one is the triangular-diagonal-dominance condition proposed by Hung and Anderson. The second one is the stable coprime factorisation-described condition proposed by Gomez and Goodwin, which has been proven as a necessary and sufficient condition for the triangular decoupling problem. This article proves that the two conditions are actually equivalent. It also provides easy-to-use criteria for assessment of the solvability of the triangular decoupling problem

Laboratory demonstration for model predictive multivariable control with a coupled drive system

Teaching multivariable control usually involves a certain level of mathematical sophistication and hence requires some labaratorial exemplification of the material given in formal lectures. This paper reports on a hands-on approach to multivariable control education via the implementation of a model predictive controller on a two-input, two output coupled drive apparatus. This scaled-down system represents many industrial processes while provides an excellent set-up for demonstrating the cross-coupled effects in multi-input multi-output systems. Here, a model predictive controller (MPC) is developed and implemented on the basis of a constrained optimization problem to show control performance via the belt tension and velocity outputs, demonstrate the decoupling capability, and also illustrate such issues as control input saturation, the selection of operating point, reference inputs, and system robustness to external disturbance and varying parameters. The implementation is based on Labview and MATLAB Model Predictive Control Toolbox. ©2010 IEEE. Model predictive Control

Neuro-sliding mode multivariable control of a powered wheelchair.

This paper proposes a neuro-sliding mode multivariable control approach for the control of a powered wheelchair system. In the first stage, a systematic decoupling technique is applied to the wheelchair system in order to reduce the multivariable control problem into two independent scalar control problems. Then two Neuro-Sliding Mode Controllers (NSMCs) are designed for these independent subsystems to guarantee system robustness under model uncertainties and unknown external disturbances. Both off-line and on-line trainings are involved in the second stage. Real-time experimental results confirm that robust performance for this multivariable wheelchair control system under model uncertainties and unknown external disturbances can indeed be achieved

Neural Network Based Diagonal Decoupling Control of Powered Wheelchair Systems

This paper proposes an advanced diagonal decou- pling control method for powered wheelchair systems. This control method is based on a combination of the systematic diagonaliza- tion technique and the neural network control design. As such, this control method reduces coupling effects on a multivariable system, leading to independent control design procedures. Using an obtained dynamic model, the problem of the plants Jacobian calculation is eliminated in a neural network control design. The effectiveness of the proposed control method is verified in a real-time implementation on a powered wheelchair system. The obtained results confirm that robustness and desired performance of the overall system are guaranteed, even under parameter uncertainty effects

Optimal path-following control of a smart powered wheelchair.

This paper proposes an optimal path-following control approach for a smart powered wheelchair. Lyapunov's second method is employed to find a stable position tracking control rule. To guarantee robust performance of this wheelchair system even under model uncertainties, an advanced robust tracking is utilised based on the combination of a systematic decoupling technique and a neural network design. A calibration procedure is adopted for the wheelchair system to improve positioning accuracy. After the calibration, the accuracy is improved significantly. Two real-time experimental results obtained from square tracking and door passing tasks confirm the performance of proposed approach

The hybrid bio-inspired aerial vehicle: Concept and SIMSCAPE flight simulation

© 2016 IEEE. This paper introduces a Silver Gull-inspired hybrid aerial vehicle, the Super Sydney Silver Gull (SSSG), which is able to vary its structure, under different manoeuvre requirements, to implement three flight modes: the flapping wing flight, the fixed wing flight, and the quadcopter flight (the rotary wing flight of Unmanned Air Vehicle). Specifically, through proper mechanism design and flight mode transition, the SSSG can imitate the Silver Gull's flight gesture during flapping flight, save power consuming by switching to the fixed wing flight mode during long-range cruising, and hover at targeted area when transferring to quadcopter flight mode. Based on the aerodynamic models, the Simscape, a product of MathWorks, is used to simulate and analyse the performance of the SSSG's flight modes. The entity simulation results indicate that the created SSSG's 3D model is feasible and ready to be manufactured for further flight tests

Neural network based diagonal decoupling control of powered wheelchair systems

This paper proposes an advanced diagonal decoupling control method for powered wheelchair systems. This control method is based on a combination of the systematic diagonalization technique and the neural network control design. As such, this control method reduces coupling effects on a multivariable system, leading to independent control design procedures. Using an obtained dynamic model, the problem of the plant's Jacobian calculation is eliminated in a neural network control design. The effectiveness of the proposed control method is verified in a real-time implementation on a powered wheelchair system. The obtained results confirm that robustness and desired performance of the overall system are guaranteed, even under parameter uncertainty effects. © 2013 IEEE

Experimental study on a smart wheelchair system using a combination of stereoscopic and spherical vision

This paper is concerned with the experimental study performance of a smart wheelchair system named TIM (Thought-controlled Intelligent Machine), which uses a unique camera configuration for vision. Included in this configuration are stereoscopic cameras for 3-Dimensional (3D) depth perception and mapping ahead of the wheelchair, and a spherical camera system for 360-degrees of monocular vision. The camera combination provides obstacle detection and mapping in unknown environments during real-time autonomous navigation of the wheelchair. With the integration of hands-free wheelchair control technology, designed as control methods for people with severe physical disability, the smart wheelchair system can assist the user with automated guidance during navigation. An experimental study on this system was conducted with a total of 10 participants, consisting of 8 able-bodied subjects and 2 tetraplegic (C-6 to C-7) subjects. The hands-free control technologies utilized for this testing were a head-movement controller (HMC) and a brain-computer interface (BCI). The results showed the assistance of TIM's automated guidance system had a statistically significant reduction effect (p-value = 0.000533) on the completion times of the obstacle course presented in the experimental study, as compared to the test runs conducted without the assistance of TIM. © 2013 IEEE

Development of a Bayesian recursive algorithm to find free-spaces for an intelligent wheelchair

This paper introduces a new shared control strategy for an intelligent wheelchair using a Bayesian recursive algorithm. Using the local environment information gathered by a laser range finder sensor and commands acquired through a user interface, a Bayesian recursive algorithm has been developed to find the most appropriate free-space, which corresponds to the highest posterior probability value. Then, an autonomous navigation algorithm will assist to manoeuvre the wheelchair in the chosen free-space. Experiment results demonstrate that the new method provides excellent performance with great flexibility and fast response. © 2011 IEEE

Advanced robust tracking control of a powered wheelchair system.

In this paper, the dynamic multivariable model of the wheelchair system is obtained including the presence of transportation lags. The triangular diagonal dominance (TDD) decoupling technique is applied to reduce this multivariable control problem into two independent scalar control problems. An advanced robust control technique for the wheelchair has been developed based on the combination of a TDD decoupling strategy and neural network controller design. The results obtained from the real-time implementation confirm that robust performance for this multivariable wheelchair control system can indeed be achieved