The lack of backdrivability can be advantageous when one is interested in precise control of each joint individually. Hence, joints that are driven by combined motor–gearbox actuation units can be difficult to move from the output side – that is, the side of the gearshaft – resulting in systems that lack backdrivability. In particular, the gear reducers tend to increase the friction of the joint and to add reflected inertia, which, depending on the gear reduction ratio, can be significant. The introduction of gearboxes in the drive train, introduces dynamic effects that significantly affect the behavior of the robot. Therefore, it is common to use transmission mechanisms – often, gearboxes – to reduce the rotating speed and increase the output torque. In general, though, the ability of electric motors to generate torque is speed-dependent typically, the magnitude of the torque that can be delivered to the motorshaft is small and the rotating speed is much faster than that required in bipedal robot applications. The majority of these robots were driven by electric motors controlled by computers with small time delays. The bipedal robot BIPER closely resembles an inverted pendulum ( Miura and Shimoyama, 1984).įollowing Miura and Shimoyama (1984), a number of researchers developed bipedal robots with more human-like morphologies than BIPER and used the inverted pendulum paradigm for designing control laws. The backstepping control methodology is explained using a recursive procedure interconnecting the selection of the candidate Lyapunov function with the design of the feedback control loop, to obtain stability and robust control under conditions less restrictive than other methods. The steps to obtain a fuzzy controller are described, and the provided example compares the fuzzy controller performance to current-mode control. The best vector is then applied to the converter by computing the minimum of a cost functional.įuzzy control needs an expert qualitative knowledge of the converter dynamics. Predictive control uses a detailed nonlinear dynamic model to forecast the converter future behavior upon application of every possible converter switching state or vector. Nonlinear state-space models and sliding-mode controllers are next used to define exactly the variables to be measured while providing the control and switching laws aiming for robust modulator and controller design.

Linear models are then used to design linear feedback controllers for converter operating in the continuous or discontinuous mode. It starts by explaining techniques to obtain linear state-space converter models, illustrating them through examples.

This chapter provides tools to control switching electronic power converters.

Pinto, in Power Electronics Handbook (Fourth Edition), 2018 Abstract * * Created by ArduinoGetStarted.Linear and Nonlinear Control of Switching Power Converters

Linear feedback