sliding mode control

Sliding mode control can be used in the design of state observers.

Figure 1 shows an example trajectory of a system under sliding mode control.

The main strength of sliding mode control is its robustness.

Hence, sliding mode control is a variable structure control method.

Sliding mode control forces the system trajectories into this subspace and then holds them there so that they slide along it.

Sliding mode control of autonomous spacecraft.

Sliding mode control must be applied with more care than other forms of nonlinear control that have more moderate control action.

Bang-bang control - Sliding mode control is often implemented as a bang-bang control.

In contrast with conventional sliding mode control, the system motion under integral sliding mode has a dimension equal to that of the state space.

The invariance property of sliding mode control to certain disturbances and model uncertainties is its most attractive feature; it is strongly robust.

Under certain common conditions, optimality requires the use of bang-bang control; hence, sliding mode control describes the optimal controller for a broad set of dynamic systems.

These, e.g., feedback linearization, backstepping, sliding mode control, trajectory linearization control normally take advantage of results based on Lyapunov's theory.

Intuitively, sliding mode control uses practically infinite gain to force the trajectories of a dynamic system to slide along the restricted sliding mode subspace.

W. C. Ho, and James Lam, Robust integral sliding mode control for uncertain stochastic systems with time-varying delay.

In 1996, V. Utkin and J. Shi proposed an improved sliding control method named integral sliding mode control (ISMC).

The principle of sliding mode control is to forcibly constrain the system, by suitable control strategy, to stay on the sliding surface on which the system will exhibit desirable features.

Because sliding mode control laws are not continuous, it has the ability to drive trajectories to the sliding mode in finite time (i.e., stability of the sliding surface is better than asymptotic).

However, real implementations of sliding mode control approximate this theoretical behavior with a high-frequency and generally non-deterministic switching control signal that causes the system to "chatter" in a tight neighborhood of the sliding surface.

In the early 1990s, a new type of sliding mode control, named terminal sliding modes (TSM) was invented at the Jet Propulsion Laboratory (JPL) by Venkataraman and Gulati.

Additionally, white zero-mean symmetric measurement noise (e.g., Gaussian noise) only affects the switching frequency of the control , and hence the noise will have little effect on the equivalent sliding mode control .

The main idea of terminal sliding mode control evolved out of seminal work on terminal attractors done by Zak in the JPL, and is evoked by the concept of terminal attractors which guarantee finite time convergence of the states.

In control theory, sliding mode control, or SMC, is a nonlinear control method that alters the dynamics of a nonlinear system by application of a discontinuous control signal that forces the system to "slide" along a cross-section of the system's normal behavior.

Sliding mode control systems Other applications are found in Systems and Control (hybrid systems, differential inclusions, optimal control with state constraints), Optimization (Complementarity systems and Variational inequalities) Biology Gene regulatory network, Fluid Mechanics and Computer graphics, ...

For example, sliding mode control can be used to design an observer that brings one estimated state's error to zero in finite time even in the presence of measurement error; the other states have error that behaves similarly to the error in a Luenberger observer after peaking has subsided.