Forwarding Control Strategy And Its Application To A Class Of Nonlinear Systems

Forwarding control technology we studied is proposed within the framework of system immersion and invariance manifold(I&I),which is a constructive control approach for a class of high-order nonlinear systems in strict-feedback form.Forwarding control strategy immersed the lower-order target dynamics into the controlled plant by selecting a mapping,such that two systems have the compliant responses.Differing from the standard backstepping method,forwarding control does not require Lyapunov function in principle from the perspective of manifold,and its controller design procedures are simplified to great extent.The plant is extended to a class of high-order full-information nonlinear systems with regard to affine input,and after the study of system immersion and invariance manifold,we are able to realize the system's order reduction via forwarding control technology.This novel nonlinear control strategy does not require model linearization,but only needs to select target dynamics,mapping and virtual controller to ensure the boundedness of all signals of closed-loop systems,such that the system responses in the immersion conditions can be transmitted.However,controller design will become more complex as the degree of freedom of system increases.Analogous to backstepping design,forwarding control needs to compute analytic derivatives at each step of the design,and the higher the order of plant is,the larger computation load is.This is so-called “complexity of explosion”.To solve this problem,a filter is introduced into each virtual controller design to compute the mapping and its analytic derivatives such that controller is not involved with direct differential computation.This modification greatly improves controller's computation efficiency.Meanwhile,the boundedness of all signals can be derived by using the internal stability of filters,and all functions in the model are not required differential.Uncertainties and external disturbances satisfying mismatched condition are considered in the full-information nonlinear systems and robust forwarding controller is presented.First,adaptive controller is designed for systems in the linear parameterization form by combining with traditional adaptive theory;second,when disturbance and uncertainties occur,a robust forwarding strategy based on disturbance observer is proposed,which can estimate such uncertainties by using disturbance observer;third,uncertainties and the derivatives of mappings are approximated by using racial basis function(RBF)-based neural network with arbitrary precision,and a neural network-based robust adaptive forwarding controller is proposed.This control procedure obviate to employ multiple of filters and does not require model in the form of linear parameterization.After ensuring the stabilization of closed-loop system,a new forwarding controller is proposed to improve the system performance by using the relationship between plant and target dynamics.Since forwarding control is developed within I&I's framework,system performance will keep compliant by selecting appropriate target dynamics and mappings after system's order reduction.Synthesizing the controller of target system,such as firstorder or second-order linear system,to obtain the desired response behavior,the original high-order system is able to have the same system performance.Therefore,with the implementation of quasi-finite-time forwarding controller,the speed of convergence will be faster,tracking precision will be higher and the attenuation of disturbance will be stronger from both regulation and trajectory tracking's view.In particular,response speed depends on the gain of virtual controller.On the other hand,when actuator saturation occurs in the high-order nonlinear systems,robust forwarding controller is developed by using hyperbolic tangent function to approximate the saturation nonlinearity.Finally,the I&I-based robust forwarding control approaches mentioned above are applied to antagonistic tendon-driven robot,then standard forwarding controller,adaptive forwarding controller and quasi-finite-time forwarding controller are obtained.All these controllers with the nonlinear model of this robot are carried out in the simulation platform,and after verification of simulation,robust forwarding control method we discussed in this thesis makes the robot insensitive to external disturbances and uncertainties,especially tracks the expected reference signal with a fast speed.