Emotional models have recently gained increasing attention in the design of intelligent control systems because of their desirable properties, such as universal approximation and fast response. However, stable emotional controllers have generally been for full-state feedback linearizable systems with only matched uncertainties. They also require knowing the reference signal and its higher derivatives. In contrast, we propose here a command-filtered backstepping H1 robust adaptive emotional controller (CFBRAEC) for strict-feedback nonlinear systems with mismatched uncertainties. Our approach applies command filters to address the ‘‘explosion of complexity” in backstepping control and introduces a compensating filter consistent with the H1-based design to deal with the approximation errors of command filters. The command-filtered backstepping approach handles matched/mismatched uncertainties and disturbances while requiring only the reference signal and its first derivative to be known and continuous. Accordingly, CFBRAEC is more suitable for practical applications and applicable to a broader group of dynamic systems. The boundedness of the tracking error and other closed-loop signals are established based on Lyapunov theory. The effectiveness of CFBRAEC is shown through simulations in the presence of measurement noise and matched/mismatched disturbances with unknown bounds on two different uncertain nonlinear systems: an inverted pendulum and an electromechanical motor.

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