Robust multivariable strategy and its application to a powered wheelchair

The paper proposes a systematic robust multivariable control strategy based on combination of systematic triangularization technique and robust control strategies. Two design stages are required. In the first design stage, multivariable control problem is reduced into a series of scalar control problems via triangularization technique. For each specific scalar system, two advanced control strategies are proposed and implemented in the second design stage. The first one is based on model predictive control, which is an iterative, finite horizon optimization procedure. The second control strategy is known as neuro-sliding mode control, which integrates sliding mode control (SMC) and neural network design to achieve both chattering-free and system robustness. Real-time implementation on a powered wheelchair system confirms that robustness and desired performance of a multivariable system under model uncertainties and unknown external disturbances can indeed be achieved by the combination of triangularization technique and neuro-sliding mode control.