Abstract
In this paper, the design of the terminal continuous-time sliding mode controller is presented. The influence of the external disturbances is considered. The robustness for the whole regulation process is obtained by adapting the time-varying sliding line. The representative point converges to the demand state in finite time due to the selected shape of the nonlinear switching curve. Absolute values of control signal, system velocity and both of these quantities are bounded from above and considered as system constraints. In order to evaluate the dynamical performance of the system, the settling time is selected as a quality index and it is minimized. The approach presented in this paper is particularly suited for systems in which one state (or a set of states) is the derivative of the other state (or a set of states). This makes it applicable to a wide range of electromechanical systems, in which the states are the position and velocity of the mechanical parts.
Highlights
Sliding mode control has become an efficient regulation control approach due to its robustness to perturbations and computational efficiency [1,2,3,4,5,6]
Two strategies can be considered: when the switching hyperplane stops during the control process and when it moves for the whole regulation process
The convergence would only be asymptotic. Another important issue is to evaluate the dynamical performance of the control loop. It can be obtained by minimizing one of well-known quality indices used in automation, for example: regulation time, integral absolute error (IAE), integral square error (ISE), integral time absolute error (ITAE), integral time-multiplied square error (ITSE)
Summary
Sliding mode control has become an efficient regulation control approach due to its robustness to perturbations and computational efficiency [1,2,3,4,5,6]. The work [19] analyzes the control of electric drive systems with sliding modes, namely controlling the speed of an induction motor. A six-phase induction motor is controlled in a cascade structure, with a PI speed controller and the proposed terminal sliding mode current controller. When dealing with control systems in which maintaining constraints is one of the main factors, model predictive control (MPC) [23,24] is one of the main solutions It has some drawbacks, as it requires online optimization, which makes it difficult to apply to complex systems with short time constants (as the computational power required to perform the optimization can become prohibitively expensive in these cases).
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
