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Underactuated systems are widely used in practice. Due to actuator saturation and transient performance requirements, it is necessary to keep the control inputs and system states within safe limits. However, with fewer control inputs, the state constraints, especially for unactuated states, are usually difficult to guarantee. Model predictive control (MPC), as a method that can handle constraints naturally, unfortunately, still struggles to deal with unactuated variable constraints directly. To this end, this article proposes a general MPC algorithm for a class of underactuated systems . First, an MPC method considering actuator saturation constraints is designed, based on which, different velocity constraint-related matrices are constructed to convert both actuated and unactuated velocity constraints into control input constraints. Then, by delicately analyzing the coupling relationship between actuated and unactuated variables, the displacement/angle constraints of unactuated variables are theoretically ensured. To our best knowledge, it is the first MPC approach designed for a class of underactuated systems with both actuated and unactuated state constraints as well as actuator saturation. Finally, the proposed MPC approach is applied to two typical underactuated systems, i.e., tower cranes and boom cranes, and a series of experiments are investigated to verify the effectiveness and superiority of this approach.
Zhai et al. (Wed,) studied this question.