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The formation control problem for a group of unmanned aerial vehicles (UAVs) has attracted significant attention recently in multiple fields, such as robotics, aerospace, and wireless communication. U...
System optimization and control have become the key design philosophies in modern control system theories, where reinforcement learning (RL) algorithm has drawn considerable attention in recent litera...
Optimal control, reinforcement learning and other optimization-based methods have been widelyapplied to control synthesis for real systems in physics, biology and robotics. However, in many complicate...
CCC2016 Workshop 1: Nonlinear Systems and Control     Small-Gain Designs  Event-based Control       font style='font-size:12px;'> 2016/7/19
In natural systems (such as those in natural world) and manmade systems (such as those in engineering applications), nonlinearity, one of the fundamental characteristics exhibited in simple and comp...
A method of computing the finite-horizon control inputs for FIR plants whose parameters are only known to lie in a set is proposed. The parameter set is assumed to be described by an ellipsoidal bound...
Robust control design for ellipsoidal plant set     Robust control design  the oval plants  the parameter matrix  oval set       font style='font-size:12px;'> 2015/8/12
Presents a control design method for continuous-time plants whose uncertain parameters in the output matrix are only known to lie in an ellipsoidal set. The desired control is chosen to minimize the m...
Gives some vague ideas about useful control design tools that might be based on LMI algorithms.
This paper describes how to efficiently solve a robust optimal control problem using recently developed primal-dual interior-point methods. Among potential applications are model predictive control. T...
In this paper we present a path-following (homotopy) method for (locally) solving bilinear matrix inequality (BMI) problems in control. The method is to linearize the BMI using a first order perturbat...
Robust linear programming and optimal control     Linear programming  Convex optimization  Model-predictive control       font style='font-size:12px;'> 2015/8/11
We describe an efficient method for solving an optimal control problem that arises in robust model-predictive control. The problem is to design the input sequence that minimizes the peak tracking erro...
We describe a new method for tuning a certain family of low-bandwidth controllers for linear time-invariant and spatially-invariant (LTSI) plants. We consider LTSI controllers with a fixed structure, ...
The field of control provides the principles and methods used to design physical and information systems that maintain desirable performance by sensing and automatically adapting to changes in the env...
The field of control provides the principles and methods used to design physical and information systems that maintain desirable performance by sensing and automatically adapting to changes in the env...
When Should Control Be Shared?     Contract theory  control rights  ownership rights  shared control       font style='font-size:12px;'> 2015/7/21
A common pattern of control in firms is for management to retain a broad set of rights, while the remaining stakeholders’ contracts provide them with targeted veto rights over specific cl...
An automated procedure for optimization of proportional–integral–derivative (PID)-type controller parameters for single-input, single-output (SISO) plants with explicit model uncertainty is presente...

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